Krnlx Nvidia xevan miner - 3.3+ mh on 1070, ~6mh on 80ti FREE, OPENSOURCE

[krnlx]

Hi all! This is prealpha version of my xevan miner. Tested only on linux, cuda 7.5 and 1070 & 1080ti.

https://github.com/krnlx/ccminer-xevan

Donations are welcome.


UPD. For 1060 cards intensity sets up incorrectly - you must adjust it with -i param. -i 20 is best for 1070, 1080ti

UPD2. Windows version by Palgin

x86_64
https://mega.nz/#!NhhnGahJ!dGC_LNOi_a98BuHSuLZQB7k-YT-dM7I_We_svn1hCc0
x86
https://mega.nz/#!98xj3RyD!tfWT6yKHb7gQhzJMi0YYx7wwIX75wppE3Hw7grcMR-4

[1715173229]

1715173229

[1715173229]

1715173229

[1715173229]

1715173229

[car1999]

awesome, I'm compiling it, is there a recommend pool?

[krnlx]

I tested on yiimp and suprnova

[car1999]

it works fine with cuda8, ubuntu16,suprnova, gtx1080ti get  5.6m @core clock+100, 200watts.
I'll install cuda7.5.

[du44]

Can someone share windows cuda 7.5 x32 biraries please?

[FortuneNVirtue]

I got some errors compiling "identifier ulong is undefined" (file: cuda_bmw512.cu)
Could you help me please?

PS. I am not a programmer, I tried to compile it with vs2013, cuda 7.5, windows 10.

[krnlx]

I got some errors compiling "identifier ulong is undefined" (file: cuda_bmw512.cu)
Could you help me please?

PS. I am not a programmer, I tried to compile it with vs2013, cuda 7.5, windows 10.

try adding

#define ulong uint64_t

or just replace ulong with uint64_t

[FortuneNVirtue]

Thank you so much.
I'll try it. 

[greenhope]

Are you planning to bring one for windows?

[krnlx]

Are you planning to bring one for windows?

I dont have windows PC, but someone will compile soon it under windows.

[..XyZ..]

Any Win build please!

[zjy]

Are you planning to bring one for windows?

I dont have windows PC, but someone will compile soon it under windows.

bug,if Disconnect，Can not connect again，just ctrl+c and start again,please fix it
[2017-10-05 13:22:51] submit_upstream_work stratum_send_line failed
[2017-10-05 13:22:51] ...retry after 30 seconds
[2017-10-05 13:22:51] GPU#0:NONCE FOUND
[2017-10-05 13:22:51] GPU#5:target 0 fec00000 13f
[2017-10-05 13:22:51] GPU#5:target 13ffec00000
[2017-10-05 13:22:51] GPU#0:NONCE FOUND
[2017-10-05 13:22:51] GPU#2:target 0 fec00000 13f
[2017-10-05 13:22:51] GPU#2:target 13ffec00000
[2017-10-05 13:22:51] GPU#0:NONCE FOUND
[2017-10-05 13:22:51] GPU#5:target 0 fec00000 13f
[2017-10-05 13:22:51] GPU#5:target 13ffec00000
[2017-10-05 13:22:52] GPU#0:NONCE FOUND
[2017-10-05 13:22:52] GPU#5:target 0 fec00000 13f
[2017-10-05 13:22:52] GPU#5:target 13ffec00000
[2017-10-05 13:22:52] GPU#0:NONCE FOUND
[2017-10-05 13:22:52] GPU#3:target 0 fec00000 13f
[2017-10-05 13:22:52] GPU#3:target 13ffec00000

[krnlx]

I will take a look.
As temporary solution you can use -r 0 option to manage miner exit after disconnect, and launch miner in a loop.

[NameTaken]

Hi all! This is prealpha version of my xevan miner. Tested only on linux, cuda 7.5 and 1070 & 1080ti.

https://github.com/krnlx/ccminer-xevan

Donations are welcome.

Your previous Skunk ccminer showed hashrate incorrectly so does this have the same problem?

[startsts]

Good job! Works very well at ubuntu 16 with cuda 8.
One thing:  for gtx 1060 3gb it sets too much intensity by default (22.5) so gets memory error.   with  -i 21 works well

[krnlx]

Hi all! This is prealpha version of my xevan miner. Tested only on linux, cuda 7.5 and 1070 & 1080ti.

https://github.com/krnlx/ccminer-xevan

Donations are welcome.

Your previous Skunk ccminer showed hashrate incorrectly so does this have the same problem?

I had not this issue on my rigs... anyway I mined xevan for a week on yiimp, hashrate was ok.

[krnlx]

Good job! Works very well at ubuntu 16 with cuda 8.
One thing:  for gtx 1060 3gb it sets too much intensity by default (22.5) so gets memory error.   with  -i 21 works well

ohhh it was old settings from x17... the best intensity on 1070 and 1080ti is 20, you can try it

[palgin]

Great (and big in amount) job done! You deserve every single donation

People, sponsor this Developer, he makes great things for community for free (which becomes rare these days)

You won't become poor person by sending few bucks to krnlx, he'll be pleased and this also highly motivates developement.

[..XyZ..]

Im happy to do donation but no Win buld to test here

[sp_]

There is a 0.5btc bounty waiting for him. But he needs to make a windows build. 

I am building now.

[abudfv2008]

Hi all! This is prealpha version of my xevan miner. Tested only on linux, cuda 7.5 and 1070 & 1080ti.
https://github.com/krnlx/ccminer-xevan

May be you can make a win/linux binary. Otherwise there are big chances someone very soon will share a trojan binary of your miner.
It would be much better if that binary is made by you.

[FortuneNVirtue]

Just compiled successfully (as you advised), but
I got something like :

GPU#0: NONCE FOUND
GPU#0: result for 00000128 does not validate on CPU!

Any suggestion, please ?

[krnlx]

Just compiled successfully (as you advised), but
I got something like :

GPU#0: NONCE FOUND
GPU#0: result for 00000128 does not validate on CPU!

Any suggestion, please ?

This is not good  What changes did you made to source code ?

[stas260385]

Just compiled successfully (as you advised), but
I got something like :

GPU#0: NONCE FOUND
GPU#0: result for 00000128 does not validate on CPU!

Any suggestion, please ?

Too high intensity in your case. Set -i 20
It's might help you.

Can you share your binary please?

[Gaglam]

a win binary would be highly appreciated

[rusm35]

I got some errors compiling "identifier ulong is undefined" (file: cuda_bmw512.cu)
Could you help me please?

PS. I am not a programmer, I tried to compile it with vs2013, cuda 7.5, windows 10.

try adding

#define ulong uint64_t

or just replace ulong with uint64_t

I'm not a programmer. Tell me please where to add it, I have the same mistake.

[ioglnx]

There are many issues in the windows build - I fixed already 6 and the next coming up.
Like not compiling the deps (curl etc.) krnlx may you merge the setting of your skunk version since this properly works.

[FortuneNVirtue]

Just compiled successfully (as you advised), but
I got something like :

GPU#0: NONCE FOUND
GPU#0: result for 00000128 does not validate on CPU!

Any suggestion, please ?

This is not good  What changes did you made to source code ?

1. added #define ulong uint64_t (I also tried to replace ulong with uint64_t, both result the same.)
2. changed uint ord to int ord (cuda_sha512_lbry.cu) because it show error.
3. added files cuda_x13_fugue512.cu and cuda_x13_hamsi512.cu to the project
4. copied folder "compat/curl-for-windows/out/ from somewhere else to "compat/curl-for-windows" (it asked for libcurl.x86.lib as states in linker)

I may do something wrong, but please suggest me, Thank you.

[palgin]

Stick to Linux build. Even after removing part of CPU validation from Win build yiimp rejects shares, which means hashing go wrong on Windows. Think it may be lib-related issue, maybe someone will fix

[CryptoGeneral]

There is a 3000 XLR bounty for a Windows xevan miner. I'll hope that you can make it happen.

[nax]

Just compiled successfully (as you advised), but
I got something like :

GPU#0: NONCE FOUND
GPU#0: result for 00000128 does not validate on CPU!

Any suggestion, please ?

This is not good  What changes did you made to source code ?

1. added #define ulong uint64_t (I also tried to replace ulong with uint64_t, both result the same.)
2. changed uint ord to int ord (cuda_sha512_lbry.cu) because it show error.
3. added files cuda_x13_fugue512.cu and cuda_x13_hamsi512.cu to the project
4. copied folder "compat/curl-for-windows/out/ from somewhere else to "compat/curl-for-windows" (it asked for libcurl.x86.lib as states in linker)

I may do something wrong, but please suggest me, Thank you.

same error here

[palgin]

krnlx deserves every existing bounty for this algo because he was first to release, all others will be copy-paste guys. Win binary is not obligatory, code is open and it's just a matter of time when it will become avaliable.

[}{uNdd]

Just compiled successfully (as you advised), but
I got something like :

GPU#0: NONCE FOUND
GPU#0: result for 00000128 does not validate on CPU!

Any suggestion, please ?

This is not good  What changes did you made to source code ?

1. added #define ulong uint64_t (I also tried to replace ulong with uint64_t, both result the same.)
2. changed uint ord to int ord (cuda_sha512_lbry.cu) because it show error.
3. added files cuda_x13_fugue512.cu and cuda_x13_hamsi512.cu to the project
4. copied folder "compat/curl-for-windows/out/ from somewhere else to "compat/curl-for-windows" (it asked for libcurl.x86.lib as states in linker)

I may do something wrong, but please suggest me, Thank you.

the last point error , i still finding where to copy ...

[sp_]

I have a windows build. But Xevan is not profitable. any more.

[startsts]

Can you tell me what multiplier has xevan algo?   I set to my pool multiplier 24  and my pool show more 20% hashrate than the ccminer.

[sp_]

4. copied folder "compat/curl-for-windows/out/ from somewhere else to "compat/curl-for-windows" (it asked for libcurl.x86.lib as states in linker)

Copy and replace the folder compat/curl-for-windows from the alexis 1.0 rep on github. build with cuda 7.5 and visual studio 2013

[abudfv2008]

krnlx deserves every existing bounty for this algo because he was first to release, all others will be copy-paste guys. Win binary is not obligatory, code is open and it's just a matter of time when it will become avaliable.

It is not obligatory. But do you think that coming sooner or later malware binaries are better?

[FortuneNVirtue]

Just compiled successfully (as you advised), but
I got something like :

GPU#0: NONCE FOUND
GPU#0: result for 00000128 does not validate on CPU!

Any suggestion, please ?

This is not good  What changes did you made to source code ?

1. added #define ulong uint64_t (I also tried to replace ulong with uint64_t, both result the same.)
2. changed uint ord to int ord (cuda_sha512_lbry.cu) because it show error.
3. added files cuda_x13_fugue512.cu and cuda_x13_hamsi512.cu to the project
4. copied folder "compat/curl-for-windows/out/ from somewhere else to "compat/curl-for-windows" (it asked for libcurl.x86.lib as states in linker)

I may do something wrong, but please suggest me, Thank you.

the last point error , i still finding where to copy ...

I just copied from alexis78's ccminer. (I just guessed, because it's vs2013 and cuda7.5, other versions of ccminer may work as well, I don't know)

And what palgin said is alsolutely right, krnlx deserves every bounty for opensource xevan ccminer/nvidia gpu miner.
(Solaris and Bitsend as I know)

[krnlx]

Stick to Linux build. Even after removing part of CPU validation from Win build yiimp rejects shares, which means hashing go wrong on Windows. Think it may be lib-related issue, maybe someone will fix

Can you please printout hashing result on every algo with zero input data(x17/x17.cu, commented out code) both on linux and windows to determine where is the bug related to windows version?
My rigs are headless and far away from me, I can't test it on windows ;(

[nax]

4. copied folder "compat/curl-for-windows/out/ from somewhere else to "compat/curl-for-windows" (it asked for libcurl.x86.lib as states in linker)

Copy and replace the folder compat/curl-for-windows from the alexis 1.0 rep on github. build with cuda 7.5 and visual studio 2013

How did you solve this problem?
https://ibb.co/bHPGow

[}{uNdd]

4. copied folder "compat/curl-for-windows/out/ from somewhere else to "compat/curl-for-windows" (it asked for libcurl.x86.lib as states in linker)

Copy and replace the folder compat/curl-for-windows from the alexis 1.0 rep on github. build with cuda 7.5 and visual studio 2013

thx , done
the curl problem
still (got cpu validation problem)

[nax]

4. copied folder "compat/curl-for-windows/out/ from somewhere else to "compat/curl-for-windows" (it asked for libcurl.x86.lib as states in linker)

Copy and replace the folder compat/curl-for-windows from the alexis 1.0 rep on github. build with cuda 7.5 and visual studio 2013

same problem, invalid cpu, how did you solve it, I already tried to compile in cuda 7.5 cuda 8 32bits and 64bits and everyone is giving invalid cpu

[abudfv2008]

4. copied folder "compat/curl-for-windows/out/ from somewhere else to "compat/curl-for-windows" (it asked for libcurl.x86.lib as states in linker)

Copy and replace the folder compat/curl-for-windows from the alexis 1.0 rep on github. build with cuda 7.5 and visual studio 2013

thx , done
the curl problem
if anyone needed i can share out the x64, cuda 8.0 version

Everyone need it

[sp_]

There are warnings in the compilation you need to fix. (shift count overflow warnings ) (skein) I am building with cuda 9.0 now. x86 to test.

[ioglnx]

4. copied folder "compat/curl-for-windows/out/ from somewhere else to "compat/curl-for-windows" (it asked for libcurl.x86.lib as states in linker)

Copy and replace the folder compat/curl-for-windows from the alexis 1.0 rep on github. build with cuda 7.5 and visual studio 2013

thx , done
the curl problem
if anyone needed i can share out the x64, cuda 8.0 version

Could you please be so kind to share a 32bit and 64bit build? I copied the curl libs too but no success. Thanks

[WelcomeHomeCrypto]

A compiled Windows binary would be greatly appreciated.

[}{uNdd]

Stick to Linux build. Even after removing part of CPU validation from Win build yiimp rejects shares, which means hashing go wrong on Windows. Think it may be lib-related issue, maybe someone will fix

the windows build had this problem, still need solve ....

[..XyZ..]

Any news about win build?

[xarix]

Awesome!

Finally Xevan gets some proper attention,now bring on the win miner 

[psihotoc]

Hi all! This is prealpha version of my xevan miner. Tested only on linux, cuda 7.5 and 1070 & 1080ti.

https://github.com/krnlx/ccminer-xevan

Donations are welcome.


UPD. For 1060 cards intensity sets up incorrectly - you must adjust it with -i param. -i 20 is best for 1070, 1080ti

Healthy buddy. See what the situation is, there is a Solaris coin and this coin needs a miner to Win with the algorithm Xeven. Solaris Dev pays 3000 coins to those who create. After Swop coins, its price will be very good and this amount of coins will make sozdatelya miner just rich.

[startsts]

Hi all! This is prealpha version of my xevan miner. Tested only on linux, cuda 7.5 and 1070 & 1080ti.

https://github.com/krnlx/ccminer-xevan

Donations are welcome.


UPD. For 1060 cards intensity sets up incorrectly - you must adjust it with -i param. -i 20 is best for 1070, 1080ti

Healthy buddy. See what the situation is, there is a Solaris coin and this coin needs a miner to Win with the algorithm Xeven. Solaris Dev pays 3000 coins to those who create. After Swop coins, its price will be very good and this amount of coins will make sozdatelya miner just rich.

sozdatelya

    good

@krnlx, yes please check XLR coin discussion, you deserve 3000 coins reward it's about 1500$ on current price and can grow more

[Thebestis7950]

I am excited waiting for windows miner
want to mine xevan solaris

[rednoW]

Windows compile is broken and it is not simply "add lib or typedef" problem. So I think no bounty until it is fixed.
Moreover, if someone will manage to make it work with windows it will be he (she) who could receive the XLR bounty

[palgin]

Can you please printout hashing result on every algo with zero input data(x17/x17.cu, commented out code) both on linux and windows to determine where is the bug related to windows version?
My rigs are headless and far away from me, I can't test it on windows ;(

Sorry, I'm quite far from my rigs too, ran away from rainy october to the South. Just saw topic with your miner and was curious to check. I'll try to help with Win debugging, but all I have now is weak internet connection and Anydesk running on Windows machine  

P.S : sent krnlx PM, hope we'll figure out the root of the problem. Anyway, it started raining in here too, so now it's coding time

[stas260385]

Help please!
I almost compile Win_x64 but have the next errores in the end of process:

Error   1   error LNK2001: unresolved external symbol "void __cdecl x13_hamsi512_cpu_hash_64(int,unsigned int,unsigned int *)" (?x13_hamsi512_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   2   error LNK2001: unresolved external symbol "void __cdecl x13_fugue512_cpu_hash_64(int,unsigned int,unsigned int *)" (?x13_fugue512_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   3   error LNK2001: unresolved external symbol "void __cdecl xevan_whirlpool_cpu_hash_64(int,unsigned int,unsigned int *)" (?xevan_whirlpool_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   4   error LNK2001: unresolved external symbol "void __cdecl xevan_sha512_cpu_hash_64(int,int,unsigned int *)" (?xevan_sha512_cpu_hash_64@@YAXHHPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj

What am i do wrong?

[FortuneNVirtue]

Help please!
I almost compile Win_x64 but have the next errores in the end of process:

Error   1   error LNK2001: unresolved external symbol "void __cdecl x13_hamsi512_cpu_hash_64(int,unsigned int,unsigned int *)" (?x13_hamsi512_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   2   error LNK2001: unresolved external symbol "void __cdecl x13_fugue512_cpu_hash_64(int,unsigned int,unsigned int *)" (?x13_fugue512_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   3   error LNK2001: unresolved external symbol "void __cdecl xevan_whirlpool_cpu_hash_64(int,unsigned int,unsigned int *)" (?xevan_whirlpool_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   4   error LNK2001: unresolved external symbol "void __cdecl xevan_sha512_cpu_hash_64(int,int,unsigned int *)" (?xevan_sha512_cpu_hash_64@@YAXHHPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj

What am i do wrong?

Add files cuda_x13_fugue512.cu and cuda_x13_hamsi512.cu to the project by

1. explore the solution ccminer
2. under ccminer -> source files
3. you'll see x13 folder, right click to Add ->  Existing Item
4. add cuda_x13_fugue512.cu and cuda_x13_hamsi512.cu

[stas260385]

Help please!
I almost compile Win_x64 but have the next errores in the end of process:

Error   1   error LNK2001: unresolved external symbol "void __cdecl x13_hamsi512_cpu_hash_64(int,unsigned int,unsigned int *)" (?x13_hamsi512_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   2   error LNK2001: unresolved external symbol "void __cdecl x13_fugue512_cpu_hash_64(int,unsigned int,unsigned int *)" (?x13_fugue512_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   3   error LNK2001: unresolved external symbol "void __cdecl xevan_whirlpool_cpu_hash_64(int,unsigned int,unsigned int *)" (?xevan_whirlpool_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   4   error LNK2001: unresolved external symbol "void __cdecl xevan_sha512_cpu_hash_64(int,int,unsigned int *)" (?xevan_sha512_cpu_hash_64@@YAXHHPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj

What am i do wrong?

Add files cuda_x13_fugue512.cu and cuda_x13_hamsi512.cu to the project by

1. explore the solution ccminer
2. under ccminer -> source files
3. you'll see x13 folder, right click to Add ->  Existing Item
4. add cuda_x13_fugue512.cu and cuda_x13_hamsi512.cu

Ok, it's almost helped, but now i still have the last errore:

Error   13   error LNK2001: unresolved external symbol "void __cdecl xevan_sha512_cpu_hash_64(int,int,unsigned int *)" (?xevan_sha512_cpu_hash_64@@YAXHHPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj

[palgin]

If anyone with Linux wants to help Win users, replace your x17.cu contents with this code:

Code: (x17.cu)

/**
 * X17 algorithm (X15 + sha512 + haval256)
 */

extern "C" {
#include "sph/sph_blake.h"
#include "sph/sph_bmw.h"
#include "sph/sph_groestl.h"
#include "sph/sph_skein.h"
#include "sph/sph_jh.h"
#include "sph/sph_keccak.h"

#include "sph/sph_luffa.h"
#include "sph/sph_cubehash.h"
#include "sph/sph_shavite.h"
#include "sph/sph_simd.h"
#include "sph/sph_echo.h"

#include "sph/sph_hamsi.h"
#include "sph/sph_fugue.h"

#include "sph/sph_shabal.h"
#include "sph/sph_whirlpool.h"

#include "sph/sph_sha2.h"
#include "sph/sph_haval.h"
}

#include "miner.h"
#include "cuda_helper.h"
#include "x11/cuda_x11.h"

#define NBN 2

// Memory for the hash functions
static uint32_t *d_hash[MAX_GPUS];
static uint32_t *d_resNonce[MAX_GPUS];
static uint32_t *h_resNonce[MAX_GPUS];

void print_hash(unsigned int *data, int size){
	for (int i = 0; i<size; i++)
		gpulog(LOG_WARNING, 0, "%x ", data[i]);
	//gpulog(LOG_WARNING, 0, "-------------");
}

extern void x13_hamsi_fugue512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x14_shabal512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x15_whirlpool_cpu_init(int thr_id, uint32_t threads, int mode);
extern void x15_whirlpool_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x15_whirlpool_cpu_free(int thr_id);

extern void x17_sha512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x17_haval256_cpu_hash_64_final(int thr_id, uint32_t threads, uint32_t *d_hash, uint32_t* resNonce, uint64_t target);
extern void bmw256_cpu_hash_32_full(int thr_id, uint32_t threads, uint32_t *g_hash);
extern void quark_bmw512_cpu_hash_64x(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_hash);
extern void quark_groestl512(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void groestl512_cpu_init(int thr_id, uint32_t threads);
extern void groestl512_cpu_hash(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_skein512(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void keccak_xevan_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void qubit_luffa512_cpu_hash_80(int thr_id, uint32_t threads, uint32_t startNounce, uint32_t *d_outputHash);
extern void x11_cubehash512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_shavite512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_shavite512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_echo512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_echo512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_simd512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_simd512_cpu_init(int thr_id, uint32_t threads);
extern void xevan_simd512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x13_hamsi512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x13_fugue512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_whirlpool_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_sha512_cpu_hash_64(int thr_id, int threads, uint32_t *d_hash);
extern void xevan_haval512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void quark_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_outputHash);
extern void xevan_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_haval512_cpu_hash_64_final(int thr_id, uint32_t threads, uint32_t *d_hash, uint32_t *resNonce, uint64_t target);
extern void xevan_groestl512_cpu_hash(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void keccak_xevan_cpu_hash_64_A(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void quark_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_outputHash);
extern void quark_blake512_cpu_hash_128(int thr_id, uint32_t threads, uint32_t *d_outputHash);
extern void quark_groestl512_cpu_hash_128(int thr_id, uint32_t threads,  uint32_t *d_hash);
extern void x11_luffa512_cpu_hash_128(int thr_id, uint32_t threads,uint32_t *d_hash);



// X17 CPU Hash (Validation)
extern "C" void x17hash(void *output, const void *input)
{
	uint32_t _ALIGN(64) hash[32]; // 128 bytes required
	uint32_t input_zero[20] = { 0 };
	const int dataLen = 128;

//return;
	sph_blake512_context     ctx_blake;
	sph_bmw512_context       ctx_bmw;
	sph_groestl512_context   ctx_groestl;
	sph_skein512_context     ctx_skein;
	sph_jh512_context        ctx_jh;
	sph_keccak512_context    ctx_keccak;
	sph_luffa512_context     ctx_luffa;
	sph_cubehash512_context  ctx_cubehash;
	sph_shavite512_context   ctx_shavite;
	sph_simd512_context      ctx_simd;
	sph_echo512_context      ctx_echo;
	sph_hamsi512_context     ctx_hamsi;
	sph_fugue512_context     ctx_fugue;
	sph_shabal512_context    ctx_shabal;
	sph_whirlpool_context    ctx_whirlpool;
	sph_sha512_context       ctx_sha512;
	sph_haval256_5_context   ctx_haval;

	print_hash(input_zero,20);
	gpulog(LOG_WARNING, 0, "--INPUT ZEROES--");

	sph_blake512_init(&ctx_blake);
	sph_blake512(&ctx_blake, input_zero, 80);
	sph_blake512_close(&ctx_blake, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BLAKE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	memset(&hash[16], 0, 64);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--AFTER MEMSET--");

	sph_bmw512_init(&ctx_bmw);
	sph_bmw512(&ctx_bmw, hash, dataLen);
	sph_bmw512_close(&ctx_bmw, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BMW512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_groestl512_init(&ctx_groestl);
	sph_groestl512(&ctx_groestl, hash, dataLen);
	sph_groestl512_close(&ctx_groestl, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--GROESTL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_skein512_init(&ctx_skein);
	sph_skein512(&ctx_skein, hash, dataLen);
	sph_skein512_close(&ctx_skein, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SKEIN512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_jh512_init(&ctx_jh);
	sph_jh512(&ctx_jh, hash, dataLen);
	sph_jh512_close(&ctx_jh, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--JH512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_keccak512_init(&ctx_keccak);
	sph_keccak512(&ctx_keccak, hash, dataLen);
	sph_keccak512_close(&ctx_keccak, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--KECCAK512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_luffa512_init(&ctx_luffa);
	sph_luffa512(&ctx_luffa, hash, dataLen);
	sph_luffa512_close(&ctx_luffa, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--LUFFA512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_cubehash512_init(&ctx_cubehash);
	sph_cubehash512(&ctx_cubehash, hash, dataLen);
	sph_cubehash512_close(&ctx_cubehash, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--CUBEHASH512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_shavite512_init(&ctx_shavite);
	sph_shavite512(&ctx_shavite, hash, dataLen);
	sph_shavite512_close(&ctx_shavite, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHAVITE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_simd512_init(&ctx_simd);
	sph_simd512(&ctx_simd, hash, dataLen);
	sph_simd512_close(&ctx_simd, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BLAKE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_echo512_init(&ctx_echo);
	sph_echo512(&ctx_echo, hash, dataLen);
	sph_echo512_close(&ctx_echo, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--ECHO512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_hamsi512_init(&ctx_hamsi);
	sph_hamsi512(&ctx_hamsi, hash, dataLen);
	sph_hamsi512_close(&ctx_hamsi, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--HAMSI512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_fugue512_init(&ctx_fugue);
	sph_fugue512(&ctx_fugue, hash, dataLen);
	sph_fugue512_close(&ctx_fugue, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--FUGUE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_shabal512_init(&ctx_shabal);
	sph_shabal512(&ctx_shabal, hash, dataLen);
	sph_shabal512_close(&ctx_shabal, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHABAL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_whirlpool_init(&ctx_whirlpool);
	sph_whirlpool(&ctx_whirlpool, hash, dataLen);
	sph_whirlpool_close(&ctx_whirlpool, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--WHIRLPOOL--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_sha512_init(&ctx_sha512);
	sph_sha512(&ctx_sha512,(const void*) hash, dataLen);
	sph_sha512_close(&ctx_sha512,(void*) hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHA512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_haval256_5_init(&ctx_haval);
	sph_haval256_5(&ctx_haval,(const void*) hash, dataLen);
	sph_haval256_5_close(&ctx_haval, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--HAVAL256--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	memset(&hash[8], 0, dataLen - 32);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--AFTER MEMSET--");

	sph_blake512_init(&ctx_blake);
	sph_blake512(&ctx_blake, hash, dataLen);
	sph_blake512_close(&ctx_blake, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BLAKE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_bmw512_init(&ctx_bmw);
	sph_bmw512(&ctx_bmw, hash, dataLen);
	sph_bmw512_close(&ctx_bmw, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BMW512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_groestl512_init(&ctx_groestl);
	sph_groestl512(&ctx_groestl, hash, dataLen);
	sph_groestl512_close(&ctx_groestl, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--GROESTL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_skein512_init(&ctx_skein);
	sph_skein512(&ctx_skein, hash, dataLen);
	sph_skein512_close(&ctx_skein, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SKEIN512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_jh512_init(&ctx_jh);
	sph_jh512(&ctx_jh, hash, dataLen);
	sph_jh512_close(&ctx_jh, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--JH512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_keccak512_init(&ctx_keccak);
	sph_keccak512(&ctx_keccak, hash, dataLen);
	sph_keccak512_close(&ctx_keccak, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--KECCAK512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_luffa512_init(&ctx_luffa);
	sph_luffa512(&ctx_luffa, hash, dataLen);
	sph_luffa512_close(&ctx_luffa, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--LUFFA512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_cubehash512_init(&ctx_cubehash);
	sph_cubehash512(&ctx_cubehash, hash, dataLen);
	sph_cubehash512_close(&ctx_cubehash, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--CUBEHASH512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_shavite512_init(&ctx_shavite);
	sph_shavite512(&ctx_shavite, hash, dataLen);
	sph_shavite512_close(&ctx_shavite, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHAVITE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_simd512_init(&ctx_simd);
	sph_simd512(&ctx_simd, hash, dataLen);
	sph_simd512_close(&ctx_simd, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SIMD512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_echo512_init(&ctx_echo);
	sph_echo512(&ctx_echo, hash, dataLen);
	sph_echo512_close(&ctx_echo, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--ECHO512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_hamsi512_init(&ctx_hamsi);
	sph_hamsi512(&ctx_hamsi, hash, dataLen);
	sph_hamsi512_close(&ctx_hamsi, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--HAMSI512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_fugue512_init(&ctx_fugue);
	sph_fugue512(&ctx_fugue, hash, dataLen);
	sph_fugue512_close(&ctx_fugue, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--FUGUE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_shabal512_init(&ctx_shabal);
	sph_shabal512(&ctx_shabal, hash, dataLen);
	sph_shabal512_close(&ctx_shabal, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHABAL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_whirlpool_init(&ctx_whirlpool);
	sph_whirlpool(&ctx_whirlpool, hash, dataLen);
	sph_whirlpool_close(&ctx_whirlpool, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--WHIRLPOOL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_sha512_init(&ctx_sha512);
	sph_sha512(&ctx_sha512,(const void*) hash, dataLen);
	sph_sha512_close(&ctx_sha512,(void*) hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHA512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_haval256_5_init(&ctx_haval);
	sph_haval256_5(&ctx_haval,(const void*) hash, dataLen);
	sph_haval256_5_close(&ctx_haval, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--HAVAL256--");

	for (int i = 0; i<32; i++) hash[i] = 0;

	memcpy(output, hash, 32);
}

static bool init[MAX_GPUS] = { 0 };





extern "C" int scanhash_x17(int thr_id, struct work* work, uint32_t max_nonce, unsigned long *hashes_done){

	int dev_id = device_map[thr_id];

	uint32_t *pdata = work->data;
	uint32_t *ptarget = work->target;
	const uint32_t first_nonce = pdata[19];
	uint32_t default_throughput;
	if(device_sm[dev_id]<=500) default_throughput = 1<<20;
	else if(device_sm[dev_id]<=520) default_throughput = 1<<21;
	else if(device_sm[dev_id]>520) default_throughput = (1<<22) + (1<<21);
	
	if((strstr(device_name[dev_id], "1060")))default_throughput = 1<<20;
	if((strstr(device_name[dev_id], "1070")))default_throughput = 1<<20;
	if((strstr(device_name[dev_id], "1080")))default_throughput = 1<<20;
	
	uint32_t throughput = cuda_default_throughput(thr_id, default_throughput); // 19=256*256*8;
	if (init[thr_id]) throughput = min(throughput, max_nonce - first_nonce);

	throughput&=0xFFFFFF70; //multiples of 128 due to simd_echo kernel

	if (opt_benchmark)
		((uint32_t*)ptarget)[7] = 0xff;

	gpulog(LOG_INFO,thr_id,"target %x %x %x",ptarget[5], ptarget[6], ptarget[7]);
        gpulog(LOG_INFO,thr_id,"target %llx",*(uint64_t*)&ptarget[6]);

	if (!init[thr_id])
	{
		cudaSetDevice(device_map[thr_id]);
		if (opt_cudaschedule == -1 && gpu_threads == 1) {
			cudaDeviceReset();
			// reduce cpu usage
			cudaSetDeviceFlags(cudaDeviceScheduleBlockingSync);
		}
		gpulog(LOG_INFO,thr_id, "Intensity set to %g, %u cuda threads", throughput2intensity(throughput), throughput);

		x15_whirlpool_cpu_init(thr_id, throughput, 0);
		groestl512_cpu_init(thr_id, throughput);
		x11_simd512_cpu_init(thr_id, throughput);
		CUDA_SAFE_CALL(cudaMalloc(&d_hash[thr_id], 8 * sizeof(uint64_t) * throughput));
		CUDA_SAFE_CALL(cudaMalloc(&d_resNonce[thr_id], NBN * sizeof(uint32_t)));
		h_resNonce[thr_id] = (uint32_t*) malloc(NBN  * 8 * sizeof(uint32_t));
		if(h_resNonce[thr_id] == NULL){
			gpulog(LOG_ERR,thr_id,"Host memory allocation failed");
			exit(EXIT_FAILURE);
		}		
		init[thr_id] = true;
	}

	uint32_t _ALIGN(64) endiandata[20];
	for (int k=0; k < 20; k++)
		be32enc(&endiandata[k], pdata[k]);

	quark_blake512_cpu_setBlock_80(thr_id, endiandata);
	cudaMemset(d_resNonce[thr_id], 0xff, NBN*sizeof(uint32_t));


	do {
		// Hash with CUDA

		quark_blake512_cpu_hash_80(thr_id, throughput, pdata[19], d_hash[thr_id]);//A

		quark_groestl512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);

		quark_skein512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);

		quark_jh512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);//A //fast

		x11_luffa512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);//A

		x11_cubehash512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //A 256

		xevan_shavite512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//P slow r2
		 
        x11_simd512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);  //A slow r3
		 
		x11_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//A
		 
        x13_hamsi512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		 
		x13_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast ++
		 
		//x13_hamsi_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		x14_shabal512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		 
		xevan_whirlpool_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //opt2
		 
		xevan_sha512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		 
		xevan_haval512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		 
        quark_blake512_cpu_hash_128(thr_id, throughput,  d_hash[thr_id]);//BAD
		 
        quark_bmw512_cpu_hash_64x(thr_id, throughput, NULL, d_hash[thr_id]);
		 
		quark_groestl512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);
		 
        quark_skein512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);
		 
        quark_jh512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);
		 
        x11_luffa512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);//A
		 
        x11_cubehash512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        xevan_shavite512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//move to shared
		 
        x11_simd512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); 
		 
        x11_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        x13_hamsi512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        x13_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
		//x13_hamsi_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
        x14_shabal512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        xevan_whirlpool_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        xevan_sha512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
		xevan_haval512_cpu_hash_64_final(thr_id, throughput, d_hash[thr_id],d_resNonce[thr_id],*(uint64_t*)&ptarget[6]);
		 

		cudaMemcpy(h_resNonce[thr_id], d_resNonce[thr_id], NBN*sizeof(uint32_t), cudaMemcpyDeviceToHost);

		if (h_resNonce[thr_id][0] != UINT32_MAX){
			const uint32_t Htarg = ptarget[7];
			const uint32_t startNounce = pdata[19];
			uint32_t vhash64[8];
			be32enc(&endiandata[19], startNounce + h_resNonce[thr_id][0]);
			x17hash(vhash64, endiandata);
//			*hashes_done = pdata[19] - first_nonce + throughput + 1;
//			pdata[19] = startNounce + h_resNonce[thr_id][0];
			gpulog(LOG_WARNING, 0,"NONCE FOUND ");
//			return 1;
			if (vhash64[7] <= Htarg && fulltest(vhash64, ptarget)) {
				int res = 1;
				*hashes_done = pdata[19] - first_nonce + throughput + 1;
				work_set_target_ratio(work, vhash64);
				pdata[19] = startNounce + h_resNonce[thr_id][0];
				if (h_resNonce[thr_id][1] != UINT32_MAX) {
					pdata[21] = startNounce+h_resNonce[thr_id][1];
					if(!opt_quiet)
						gpulog(LOG_BLUE,dev_id,"Found 2nd nonce: %08x", pdata[21]);
					be32enc(&endiandata[19], pdata[21]);
					x17hash(vhash64, endiandata);
					if (bn_hash_target_ratio(vhash64, ptarget) > work->shareratio[0]){
						work_set_target_ratio(work, vhash64);
						xchg(pdata[19],pdata[21]);
					}
					res++;
				}
				return res;
			}
			else {
				gpulog(LOG_WARNING, thr_id, "result for %08x does not validate on CPU!", h_resNonce[thr_id][0]);
				cudaMemset(d_resNonce[thr_id], 0xff, NBN*sizeof(uint32_t));				
			}
		}

		pdata[19] += throughput;
	} while (!work_restart[thr_id].restart && ((uint64_t)max_nonce > (uint64_t)throughput + pdata[19]));

	*hashes_done = pdata[19] - first_nonce + 1;

	return 0;
}

// cleanup
extern "C" void free_x17(int thr_id)
{
	if (!init[thr_id])
		return;

	cudaDeviceSynchronize();

	free(h_resNonce[thr_id]);
	cudaFree(d_resNonce[thr_id]);
	cudaFree(d_hash[thr_id]);

	x11_simd_echo_512_cpu_free(thr_id);
	x15_whirlpool_cpu_free(thr_id);
	cudaDeviceSynchronize();
	init[thr_id] = false;
}

Then recompile and run for a few seconds, before first rejected share. Send me your output in PM or publish it here.

Thanks for everybody in advance!

[zer0k]

Help please!
I almost compile Win_x64 but have the next errores in the end of process:

Error   1   error LNK2001: unresolved external symbol "void __cdecl x13_hamsi512_cpu_hash_64(int,unsigned int,unsigned int *)" (?x13_hamsi512_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   2   error LNK2001: unresolved external symbol "void __cdecl x13_fugue512_cpu_hash_64(int,unsigned int,unsigned int *)" (?x13_fugue512_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   3   error LNK2001: unresolved external symbol "void __cdecl xevan_whirlpool_cpu_hash_64(int,unsigned int,unsigned int *)" (?xevan_whirlpool_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   4   error LNK2001: unresolved external symbol "void __cdecl xevan_sha512_cpu_hash_64(int,int,unsigned int *)" (?xevan_sha512_cpu_hash_64@@YAXHHPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj

What am i do wrong?

Add files cuda_x13_fugue512.cu and cuda_x13_hamsi512.cu to the project by

1. explore the solution ccminer
2. under ccminer -> source files
3. you'll see x13 folder, right click to Add ->  Existing Item
4. add cuda_x13_fugue512.cu and cuda_x13_hamsi512.cu

Ok, it's almost helped, but now i still have the last errore:

Error   13   error LNK2001: unresolved external symbol "void __cdecl xevan_sha512_cpu_hash_64(int,int,unsigned int *)" (?xevan_sha512_cpu_hash_64@@YAXHHPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj

Perhaps...

1. explore the solution ccminer
2. under ccminer -> source files
3. you'll see x17 folder, right click to Add ->  Existing Item
4. add cuda_x17_sha512.cu

[stas260385]

Help please!
I almost compile Win_x64 but have the next errores in the end of process:

Error   1   error LNK2001: unresolved external symbol "void __cdecl x13_hamsi512_cpu_hash_64(int,unsigned int,unsigned int *)" (?x13_hamsi512_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   2   error LNK2001: unresolved external symbol "void __cdecl x13_fugue512_cpu_hash_64(int,unsigned int,unsigned int *)" (?x13_fugue512_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   3   error LNK2001: unresolved external symbol "void __cdecl xevan_whirlpool_cpu_hash_64(int,unsigned int,unsigned int *)" (?xevan_whirlpool_cpu_hash_64@@YAXHIPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj   
Error   4   error LNK2001: unresolved external symbol "void __cdecl xevan_sha512_cpu_hash_64(int,int,unsigned int *)" (?xevan_sha512_cpu_hash_64@@YAXHHPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj

What am i do wrong?

Add files cuda_x13_fugue512.cu and cuda_x13_hamsi512.cu to the project by

1. explore the solution ccminer
2. under ccminer -> source files
3. you'll see x13 folder, right click to Add ->  Existing Item
4. add cuda_x13_fugue512.cu and cuda_x13_hamsi512.cu

Ok, it's almost helped, but now i still have the last errore:

Error   13   error LNK2001: unresolved external symbol "void __cdecl xevan_sha512_cpu_hash_64(int,int,unsigned int *)" (?xevan_sha512_cpu_hash_64@@YAXHHPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj

Perhaps...

1. explore the solution ccminer
2. under ccminer -> source files
3. you'll see x17 folder, right click to Add ->  Existing Item
4. add cuda_x17_sha512.cu

Didn't help cause this file are allready exist in source files. If i remoove it and add again - same errore:

Error   1   error LNK2001: unresolved external symbol "void __cdecl xevan_sha512_cpu_hash_64(int,int,unsigned int *)" (?xevan_sha512_cpu_hash_64@@YAXHHPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj

I think all project are missing one important file, something like "xevan_sha512.cu" or so...

[palgin]

Didn't help cause this file are allready exist in source files. If i remoove it and add again - same errore:

Error   1   error LNK2001: unresolved external symbol "void __cdecl xevan_sha512_cpu_hash_64(int,int,unsigned int *)" (?xevan_sha512_cpu_hash_64@@YAXHHPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj

Nothing will help with Winbuild before any Linux user send hashing output using "debug" ver of x17.cu, so don't even bother. You can check yiimp bench, no ccminer-krnlx running on Win  

Think your error is caused by wrong Curl lib or Dev environment, you need VS2013 and Curl built with the same VS version, and don't forget about architecture (x86/x64).

[stas260385]

Didn't help cause this file are allready exist in source files. If i remoove it and add again - same errore:

Error   1   error LNK2001: unresolved external symbol "void __cdecl xevan_sha512_cpu_hash_64(int,int,unsigned int *)" (?xevan_sha512_cpu_hash_64@@YAXHHPEAI@Z)   D:\ccminer-xevan-master\x17.cu.obj

Nothing will help with Winbuild before any Linux user send hashing output using "debug" ver of x17.cu, so don't even bother. You can check yiimp bench, no ccminer-krnlx running on Win  

Think your error is caused by wrong Curl lib or Dev environment, you need VS2013 and Curl built with the same VS version, and don't forget about architecture (x86/x64).

All proper Curl libs, VS2013 and CUDA 7.5 are installed

[palgin]

All proper Curl libs, VS2013 and CUDA 7.5 are installed

cuda_sha512_lbry.cu - function you need is in this file, check if it's attached to your project.

[anorganix]

Finally managed to compile it for Windows x64 @ CUDA 7.5.
Of course it's not working, looking forward to the fix from the experienced ones.

[stas260385]

Finally managed to compile it for Windows x64 @ CUDA 7.5.
Of course it's not working, looking forward to the fix from the experienced ones.

https://i.imgur.com/Mgh3vBk.png

I've compiled too but the same issue...(

[integrale]

Great Job done Guys

have it succesfull compiled on Ubuntu 16.04 LTS Cuda 7.5  Nv 384.90

running on a poor small GTX 1050 @ 1.1Mh/s with  intensity of 19

[anorganix]

If anyone with Linux wants to help Win users, replace your x17.cu contents with this code:

Code: (x17.cu)

/**
 * X17 algorithm (X15 + sha512 + haval256)
 */

extern "C" {
#include "sph/sph_blake.h"
#include "sph/sph_bmw.h"
#include "sph/sph_groestl.h"
#include "sph/sph_skein.h"
#include "sph/sph_jh.h"
#include "sph/sph_keccak.h"

#include "sph/sph_luffa.h"
#include "sph/sph_cubehash.h"
#include "sph/sph_shavite.h"
#include "sph/sph_simd.h"
#include "sph/sph_echo.h"

#include "sph/sph_hamsi.h"
#include "sph/sph_fugue.h"

#include "sph/sph_shabal.h"
#include "sph/sph_whirlpool.h"

#include "sph/sph_sha2.h"
#include "sph/sph_haval.h"
}

#include "miner.h"
#include "cuda_helper.h"
#include "x11/cuda_x11.h"

#define NBN 2

// Memory for the hash functions
static uint32_t *d_hash[MAX_GPUS];
static uint32_t *d_resNonce[MAX_GPUS];
static uint32_t *h_resNonce[MAX_GPUS];

void print_hash(unsigned int *data, int size){
	for (int i = 0; i<size; i++)
		gpulog(LOG_WARNING, 0, "%x ", data[i]);
	//gpulog(LOG_WARNING, 0, "-------------");
}

extern void x13_hamsi_fugue512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x14_shabal512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x15_whirlpool_cpu_init(int thr_id, uint32_t threads, int mode);
extern void x15_whirlpool_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x15_whirlpool_cpu_free(int thr_id);

extern void x17_sha512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x17_haval256_cpu_hash_64_final(int thr_id, uint32_t threads, uint32_t *d_hash, uint32_t* resNonce, uint64_t target);
extern void bmw256_cpu_hash_32_full(int thr_id, uint32_t threads, uint32_t *g_hash);
extern void quark_bmw512_cpu_hash_64x(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_hash);
extern void quark_groestl512(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void groestl512_cpu_init(int thr_id, uint32_t threads);
extern void groestl512_cpu_hash(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_skein512(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void keccak_xevan_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void qubit_luffa512_cpu_hash_80(int thr_id, uint32_t threads, uint32_t startNounce, uint32_t *d_outputHash);
extern void x11_cubehash512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_shavite512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_shavite512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_echo512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_echo512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_simd512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_simd512_cpu_init(int thr_id, uint32_t threads);
extern void xevan_simd512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x13_hamsi512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x13_fugue512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_whirlpool_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_sha512_cpu_hash_64(int thr_id, int threads, uint32_t *d_hash);
extern void xevan_haval512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void quark_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_outputHash);
extern void xevan_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_haval512_cpu_hash_64_final(int thr_id, uint32_t threads, uint32_t *d_hash, uint32_t *resNonce, uint64_t target);
extern void xevan_groestl512_cpu_hash(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void keccak_xevan_cpu_hash_64_A(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void quark_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_outputHash);
extern void quark_blake512_cpu_hash_128(int thr_id, uint32_t threads, uint32_t *d_outputHash);
extern void quark_groestl512_cpu_hash_128(int thr_id, uint32_t threads,  uint32_t *d_hash);
extern void x11_luffa512_cpu_hash_128(int thr_id, uint32_t threads,uint32_t *d_hash);



// X17 CPU Hash (Validation)
extern "C" void x17hash(void *output, const void *input)
{
	uint32_t _ALIGN(64) hash[32]; // 128 bytes required
	uint32_t input_zero[20] = { 0 };
	const int dataLen = 128;

//return;
	sph_blake512_context     ctx_blake;
	sph_bmw512_context       ctx_bmw;
	sph_groestl512_context   ctx_groestl;
	sph_skein512_context     ctx_skein;
	sph_jh512_context        ctx_jh;
	sph_keccak512_context    ctx_keccak;
	sph_luffa512_context     ctx_luffa;
	sph_cubehash512_context  ctx_cubehash;
	sph_shavite512_context   ctx_shavite;
	sph_simd512_context      ctx_simd;
	sph_echo512_context      ctx_echo;
	sph_hamsi512_context     ctx_hamsi;
	sph_fugue512_context     ctx_fugue;
	sph_shabal512_context    ctx_shabal;
	sph_whirlpool_context    ctx_whirlpool;
	sph_sha512_context       ctx_sha512;
	sph_haval256_5_context   ctx_haval;

	print_hash(input_zero,20);
	gpulog(LOG_WARNING, 0, "--INPUT ZEROES--");

	sph_blake512_init(&ctx_blake);
	sph_blake512(&ctx_blake, input_zero, 80);
	sph_blake512_close(&ctx_blake, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BLAKE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	memset(&hash[16], 0, 64);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--AFTER MEMSET--");

	sph_bmw512_init(&ctx_bmw);
	sph_bmw512(&ctx_bmw, hash, dataLen);
	sph_bmw512_close(&ctx_bmw, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BMW512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_groestl512_init(&ctx_groestl);
	sph_groestl512(&ctx_groestl, hash, dataLen);
	sph_groestl512_close(&ctx_groestl, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--GROESTL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_skein512_init(&ctx_skein);
	sph_skein512(&ctx_skein, hash, dataLen);
	sph_skein512_close(&ctx_skein, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SKEIN512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_jh512_init(&ctx_jh);
	sph_jh512(&ctx_jh, hash, dataLen);
	sph_jh512_close(&ctx_jh, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--JH512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_keccak512_init(&ctx_keccak);
	sph_keccak512(&ctx_keccak, hash, dataLen);
	sph_keccak512_close(&ctx_keccak, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--KECCAK512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_luffa512_init(&ctx_luffa);
	sph_luffa512(&ctx_luffa, hash, dataLen);
	sph_luffa512_close(&ctx_luffa, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--LUFFA512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_cubehash512_init(&ctx_cubehash);
	sph_cubehash512(&ctx_cubehash, hash, dataLen);
	sph_cubehash512_close(&ctx_cubehash, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--CUBEHASH512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_shavite512_init(&ctx_shavite);
	sph_shavite512(&ctx_shavite, hash, dataLen);
	sph_shavite512_close(&ctx_shavite, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHAVITE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_simd512_init(&ctx_simd);
	sph_simd512(&ctx_simd, hash, dataLen);
	sph_simd512_close(&ctx_simd, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BLAKE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_echo512_init(&ctx_echo);
	sph_echo512(&ctx_echo, hash, dataLen);
	sph_echo512_close(&ctx_echo, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--ECHO512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_hamsi512_init(&ctx_hamsi);
	sph_hamsi512(&ctx_hamsi, hash, dataLen);
	sph_hamsi512_close(&ctx_hamsi, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--HAMSI512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_fugue512_init(&ctx_fugue);
	sph_fugue512(&ctx_fugue, hash, dataLen);
	sph_fugue512_close(&ctx_fugue, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--FUGUE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_shabal512_init(&ctx_shabal);
	sph_shabal512(&ctx_shabal, hash, dataLen);
	sph_shabal512_close(&ctx_shabal, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHABAL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_whirlpool_init(&ctx_whirlpool);
	sph_whirlpool(&ctx_whirlpool, hash, dataLen);
	sph_whirlpool_close(&ctx_whirlpool, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--WHIRLPOOL--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_sha512_init(&ctx_sha512);
	sph_sha512(&ctx_sha512,(const void*) hash, dataLen);
	sph_sha512_close(&ctx_sha512,(void*) hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHA512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_haval256_5_init(&ctx_haval);
	sph_haval256_5(&ctx_haval,(const void*) hash, dataLen);
	sph_haval256_5_close(&ctx_haval, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--HAVAL256--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	memset(&hash[8], 0, dataLen - 32);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--AFTER MEMSET--");

	sph_blake512_init(&ctx_blake);
	sph_blake512(&ctx_blake, hash, dataLen);
	sph_blake512_close(&ctx_blake, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BLAKE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_bmw512_init(&ctx_bmw);
	sph_bmw512(&ctx_bmw, hash, dataLen);
	sph_bmw512_close(&ctx_bmw, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BMW512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_groestl512_init(&ctx_groestl);
	sph_groestl512(&ctx_groestl, hash, dataLen);
	sph_groestl512_close(&ctx_groestl, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--GROESTL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_skein512_init(&ctx_skein);
	sph_skein512(&ctx_skein, hash, dataLen);
	sph_skein512_close(&ctx_skein, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SKEIN512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_jh512_init(&ctx_jh);
	sph_jh512(&ctx_jh, hash, dataLen);
	sph_jh512_close(&ctx_jh, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--JH512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_keccak512_init(&ctx_keccak);
	sph_keccak512(&ctx_keccak, hash, dataLen);
	sph_keccak512_close(&ctx_keccak, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--KECCAK512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_luffa512_init(&ctx_luffa);
	sph_luffa512(&ctx_luffa, hash, dataLen);
	sph_luffa512_close(&ctx_luffa, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--LUFFA512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_cubehash512_init(&ctx_cubehash);
	sph_cubehash512(&ctx_cubehash, hash, dataLen);
	sph_cubehash512_close(&ctx_cubehash, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--CUBEHASH512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_shavite512_init(&ctx_shavite);
	sph_shavite512(&ctx_shavite, hash, dataLen);
	sph_shavite512_close(&ctx_shavite, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHAVITE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_simd512_init(&ctx_simd);
	sph_simd512(&ctx_simd, hash, dataLen);
	sph_simd512_close(&ctx_simd, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SIMD512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_echo512_init(&ctx_echo);
	sph_echo512(&ctx_echo, hash, dataLen);
	sph_echo512_close(&ctx_echo, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--ECHO512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_hamsi512_init(&ctx_hamsi);
	sph_hamsi512(&ctx_hamsi, hash, dataLen);
	sph_hamsi512_close(&ctx_hamsi, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--HAMSI512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_fugue512_init(&ctx_fugue);
	sph_fugue512(&ctx_fugue, hash, dataLen);
	sph_fugue512_close(&ctx_fugue, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--FUGUE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_shabal512_init(&ctx_shabal);
	sph_shabal512(&ctx_shabal, hash, dataLen);
	sph_shabal512_close(&ctx_shabal, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHABAL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_whirlpool_init(&ctx_whirlpool);
	sph_whirlpool(&ctx_whirlpool, hash, dataLen);
	sph_whirlpool_close(&ctx_whirlpool, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--WHIRLPOOL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_sha512_init(&ctx_sha512);
	sph_sha512(&ctx_sha512,(const void*) hash, dataLen);
	sph_sha512_close(&ctx_sha512,(void*) hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHA512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_haval256_5_init(&ctx_haval);
	sph_haval256_5(&ctx_haval,(const void*) hash, dataLen);
	sph_haval256_5_close(&ctx_haval, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--HAVAL256--");

	for (int i = 0; i<32; i++) hash[i] = 0;

	memcpy(output, hash, 32);
}

static bool init[MAX_GPUS] = { 0 };





extern "C" int scanhash_x17(int thr_id, struct work* work, uint32_t max_nonce, unsigned long *hashes_done){

	int dev_id = device_map[thr_id];

	uint32_t *pdata = work->data;
	uint32_t *ptarget = work->target;
	const uint32_t first_nonce = pdata[19];
	uint32_t default_throughput;
	if(device_sm[dev_id]<=500) default_throughput = 1<<20;
	else if(device_sm[dev_id]<=520) default_throughput = 1<<21;
	else if(device_sm[dev_id]>520) default_throughput = (1<<22) + (1<<21);
	
	if((strstr(device_name[dev_id], "1060")))default_throughput = 1<<20;
	if((strstr(device_name[dev_id], "1070")))default_throughput = 1<<20;
	if((strstr(device_name[dev_id], "1080")))default_throughput = 1<<20;
	
	uint32_t throughput = cuda_default_throughput(thr_id, default_throughput); // 19=256*256*8;
	if (init[thr_id]) throughput = min(throughput, max_nonce - first_nonce);

	throughput&=0xFFFFFF70; //multiples of 128 due to simd_echo kernel

	if (opt_benchmark)
		((uint32_t*)ptarget)[7] = 0xff;

	gpulog(LOG_INFO,thr_id,"target %x %x %x",ptarget[5], ptarget[6], ptarget[7]);
        gpulog(LOG_INFO,thr_id,"target %llx",*(uint64_t*)&ptarget[6]);

	if (!init[thr_id])
	{
		cudaSetDevice(device_map[thr_id]);
		if (opt_cudaschedule == -1 && gpu_threads == 1) {
			cudaDeviceReset();
			// reduce cpu usage
			cudaSetDeviceFlags(cudaDeviceScheduleBlockingSync);
		}
		gpulog(LOG_INFO,thr_id, "Intensity set to %g, %u cuda threads", throughput2intensity(throughput), throughput);

		x15_whirlpool_cpu_init(thr_id, throughput, 0);
		groestl512_cpu_init(thr_id, throughput);
		x11_simd512_cpu_init(thr_id, throughput);
		CUDA_SAFE_CALL(cudaMalloc(&d_hash[thr_id], 8 * sizeof(uint64_t) * throughput));
		CUDA_SAFE_CALL(cudaMalloc(&d_resNonce[thr_id], NBN * sizeof(uint32_t)));
		h_resNonce[thr_id] = (uint32_t*) malloc(NBN  * 8 * sizeof(uint32_t));
		if(h_resNonce[thr_id] == NULL){
			gpulog(LOG_ERR,thr_id,"Host memory allocation failed");
			exit(EXIT_FAILURE);
		}		
		init[thr_id] = true;
	}

	uint32_t _ALIGN(64) endiandata[20];
	for (int k=0; k < 20; k++)
		be32enc(&endiandata[k], pdata[k]);

	quark_blake512_cpu_setBlock_80(thr_id, endiandata);
	cudaMemset(d_resNonce[thr_id], 0xff, NBN*sizeof(uint32_t));


	do {
		// Hash with CUDA

		quark_blake512_cpu_hash_80(thr_id, throughput, pdata[19], d_hash[thr_id]);//A

		quark_groestl512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);

		quark_skein512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);

		quark_jh512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);//A //fast

		x11_luffa512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);//A

		x11_cubehash512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //A 256

		xevan_shavite512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//P slow r2
		 
        x11_simd512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);  //A slow r3
		 
		x11_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//A
		 
        x13_hamsi512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		 
		x13_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast ++
		 
		//x13_hamsi_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		x14_shabal512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		 
		xevan_whirlpool_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //opt2
		 
		xevan_sha512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		 
		xevan_haval512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		 
        quark_blake512_cpu_hash_128(thr_id, throughput,  d_hash[thr_id]);//BAD
		 
        quark_bmw512_cpu_hash_64x(thr_id, throughput, NULL, d_hash[thr_id]);
		 
		quark_groestl512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);
		 
        quark_skein512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);
		 
        quark_jh512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);
		 
        x11_luffa512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);//A
		 
        x11_cubehash512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        xevan_shavite512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//move to shared
		 
        x11_simd512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); 
		 
        x11_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        x13_hamsi512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        x13_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
		//x13_hamsi_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
        x14_shabal512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        xevan_whirlpool_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        xevan_sha512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
		xevan_haval512_cpu_hash_64_final(thr_id, throughput, d_hash[thr_id],d_resNonce[thr_id],*(uint64_t*)&ptarget[6]);
		 

		cudaMemcpy(h_resNonce[thr_id], d_resNonce[thr_id], NBN*sizeof(uint32_t), cudaMemcpyDeviceToHost);

		if (h_resNonce[thr_id][0] != UINT32_MAX){
			const uint32_t Htarg = ptarget[7];
			const uint32_t startNounce = pdata[19];
			uint32_t vhash64[8];
			be32enc(&endiandata[19], startNounce + h_resNonce[thr_id][0]);
			x17hash(vhash64, endiandata);
//			*hashes_done = pdata[19] - first_nonce + throughput + 1;
//			pdata[19] = startNounce + h_resNonce[thr_id][0];
			gpulog(LOG_WARNING, 0,"NONCE FOUND ");
//			return 1;
			if (vhash64[7] <= Htarg && fulltest(vhash64, ptarget)) {
				int res = 1;
				*hashes_done = pdata[19] - first_nonce + throughput + 1;
				work_set_target_ratio(work, vhash64);
				pdata[19] = startNounce + h_resNonce[thr_id][0];
				if (h_resNonce[thr_id][1] != UINT32_MAX) {
					pdata[21] = startNounce+h_resNonce[thr_id][1];
					if(!opt_quiet)
						gpulog(LOG_BLUE,dev_id,"Found 2nd nonce: %08x", pdata[21]);
					be32enc(&endiandata[19], pdata[21]);
					x17hash(vhash64, endiandata);
					if (bn_hash_target_ratio(vhash64, ptarget) > work->shareratio[0]){
						work_set_target_ratio(work, vhash64);
						xchg(pdata[19],pdata[21]);
					}
					res++;
				}
				return res;
			}
			else {
				gpulog(LOG_WARNING, thr_id, "result for %08x does not validate on CPU!", h_resNonce[thr_id][0]);
				cudaMemset(d_resNonce[thr_id], 0xff, NBN*sizeof(uint32_t));				
			}
		}

		pdata[19] += throughput;
	} while (!work_restart[thr_id].restart && ((uint64_t)max_nonce > (uint64_t)throughput + pdata[19]));

	*hashes_done = pdata[19] - first_nonce + 1;

	return 0;
}

// cleanup
extern "C" void free_x17(int thr_id)
{
	if (!init[thr_id])
		return;

	cudaDeviceSynchronize();

	free(h_resNonce[thr_id]);
	cudaFree(d_resNonce[thr_id]);
	cudaFree(d_hash[thr_id]);

	x11_simd_echo_512_cpu_free(thr_id);
	x15_whirlpool_cpu_free(thr_id);
	cudaDeviceSynchronize();
	init[thr_id] = false;
}

Then recompile and run for a few seconds, before first rejected share. Send me your output in PM or publish it here.

Thanks for everybody in advance!

Bump!
Any help much appreciated.

[palgin]

If anyone with Linux wants to help Win users, replace your x17.cu contents with this code:

Code: (x17.cu)

/**
 * X17 algorithm (X15 + sha512 + haval256)
 */

extern "C" {
#include "sph/sph_blake.h"
#include "sph/sph_bmw.h"
#include "sph/sph_groestl.h"
#include "sph/sph_skein.h"
#include "sph/sph_jh.h"
#include "sph/sph_keccak.h"

#include "sph/sph_luffa.h"
#include "sph/sph_cubehash.h"
#include "sph/sph_shavite.h"
#include "sph/sph_simd.h"
#include "sph/sph_echo.h"

#include "sph/sph_hamsi.h"
#include "sph/sph_fugue.h"

#include "sph/sph_shabal.h"
#include "sph/sph_whirlpool.h"

#include "sph/sph_sha2.h"
#include "sph/sph_haval.h"
}

#include "miner.h"
#include "cuda_helper.h"
#include "x11/cuda_x11.h"

#define NBN 2

// Memory for the hash functions
static uint32_t *d_hash[MAX_GPUS];
static uint32_t *d_resNonce[MAX_GPUS];
static uint32_t *h_resNonce[MAX_GPUS];

void print_hash(unsigned int *data, int size){
	for (int i = 0; i<size; i++)
		gpulog(LOG_WARNING, 0, "%x ", data[i]);
	//gpulog(LOG_WARNING, 0, "-------------");
}

extern void x13_hamsi_fugue512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x14_shabal512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x15_whirlpool_cpu_init(int thr_id, uint32_t threads, int mode);
extern void x15_whirlpool_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x15_whirlpool_cpu_free(int thr_id);

extern void x17_sha512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x17_haval256_cpu_hash_64_final(int thr_id, uint32_t threads, uint32_t *d_hash, uint32_t* resNonce, uint64_t target);
extern void bmw256_cpu_hash_32_full(int thr_id, uint32_t threads, uint32_t *g_hash);
extern void quark_bmw512_cpu_hash_64x(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_hash);
extern void quark_groestl512(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void groestl512_cpu_init(int thr_id, uint32_t threads);
extern void groestl512_cpu_hash(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_skein512(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void keccak_xevan_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void qubit_luffa512_cpu_hash_80(int thr_id, uint32_t threads, uint32_t startNounce, uint32_t *d_outputHash);
extern void x11_cubehash512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_shavite512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_shavite512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_echo512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_echo512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_simd512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_simd512_cpu_init(int thr_id, uint32_t threads);
extern void xevan_simd512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x13_hamsi512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x13_fugue512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_whirlpool_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_sha512_cpu_hash_64(int thr_id, int threads, uint32_t *d_hash);
extern void xevan_haval512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void quark_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_outputHash);
extern void xevan_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_haval512_cpu_hash_64_final(int thr_id, uint32_t threads, uint32_t *d_hash, uint32_t *resNonce, uint64_t target);
extern void xevan_groestl512_cpu_hash(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void keccak_xevan_cpu_hash_64_A(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void quark_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_outputHash);
extern void quark_blake512_cpu_hash_128(int thr_id, uint32_t threads, uint32_t *d_outputHash);
extern void quark_groestl512_cpu_hash_128(int thr_id, uint32_t threads,  uint32_t *d_hash);
extern void x11_luffa512_cpu_hash_128(int thr_id, uint32_t threads,uint32_t *d_hash);



// X17 CPU Hash (Validation)
extern "C" void x17hash(void *output, const void *input)
{
	uint32_t _ALIGN(64) hash[32]; // 128 bytes required
	uint32_t input_zero[20] = { 0 };
	const int dataLen = 128;

//return;
	sph_blake512_context     ctx_blake;
	sph_bmw512_context       ctx_bmw;
	sph_groestl512_context   ctx_groestl;
	sph_skein512_context     ctx_skein;
	sph_jh512_context        ctx_jh;
	sph_keccak512_context    ctx_keccak;
	sph_luffa512_context     ctx_luffa;
	sph_cubehash512_context  ctx_cubehash;
	sph_shavite512_context   ctx_shavite;
	sph_simd512_context      ctx_simd;
	sph_echo512_context      ctx_echo;
	sph_hamsi512_context     ctx_hamsi;
	sph_fugue512_context     ctx_fugue;
	sph_shabal512_context    ctx_shabal;
	sph_whirlpool_context    ctx_whirlpool;
	sph_sha512_context       ctx_sha512;
	sph_haval256_5_context   ctx_haval;

	print_hash(input_zero,20);
	gpulog(LOG_WARNING, 0, "--INPUT ZEROES--");

	sph_blake512_init(&ctx_blake);
	sph_blake512(&ctx_blake, input_zero, 80);
	sph_blake512_close(&ctx_blake, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BLAKE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	memset(&hash[16], 0, 64);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--AFTER MEMSET--");

	sph_bmw512_init(&ctx_bmw);
	sph_bmw512(&ctx_bmw, hash, dataLen);
	sph_bmw512_close(&ctx_bmw, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BMW512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_groestl512_init(&ctx_groestl);
	sph_groestl512(&ctx_groestl, hash, dataLen);
	sph_groestl512_close(&ctx_groestl, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--GROESTL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_skein512_init(&ctx_skein);
	sph_skein512(&ctx_skein, hash, dataLen);
	sph_skein512_close(&ctx_skein, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SKEIN512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_jh512_init(&ctx_jh);
	sph_jh512(&ctx_jh, hash, dataLen);
	sph_jh512_close(&ctx_jh, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--JH512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_keccak512_init(&ctx_keccak);
	sph_keccak512(&ctx_keccak, hash, dataLen);
	sph_keccak512_close(&ctx_keccak, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--KECCAK512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_luffa512_init(&ctx_luffa);
	sph_luffa512(&ctx_luffa, hash, dataLen);
	sph_luffa512_close(&ctx_luffa, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--LUFFA512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_cubehash512_init(&ctx_cubehash);
	sph_cubehash512(&ctx_cubehash, hash, dataLen);
	sph_cubehash512_close(&ctx_cubehash, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--CUBEHASH512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_shavite512_init(&ctx_shavite);
	sph_shavite512(&ctx_shavite, hash, dataLen);
	sph_shavite512_close(&ctx_shavite, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHAVITE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_simd512_init(&ctx_simd);
	sph_simd512(&ctx_simd, hash, dataLen);
	sph_simd512_close(&ctx_simd, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BLAKE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_echo512_init(&ctx_echo);
	sph_echo512(&ctx_echo, hash, dataLen);
	sph_echo512_close(&ctx_echo, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--ECHO512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_hamsi512_init(&ctx_hamsi);
	sph_hamsi512(&ctx_hamsi, hash, dataLen);
	sph_hamsi512_close(&ctx_hamsi, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--HAMSI512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_fugue512_init(&ctx_fugue);
	sph_fugue512(&ctx_fugue, hash, dataLen);
	sph_fugue512_close(&ctx_fugue, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--FUGUE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_shabal512_init(&ctx_shabal);
	sph_shabal512(&ctx_shabal, hash, dataLen);
	sph_shabal512_close(&ctx_shabal, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHABAL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_whirlpool_init(&ctx_whirlpool);
	sph_whirlpool(&ctx_whirlpool, hash, dataLen);
	sph_whirlpool_close(&ctx_whirlpool, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--WHIRLPOOL--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_sha512_init(&ctx_sha512);
	sph_sha512(&ctx_sha512,(const void*) hash, dataLen);
	sph_sha512_close(&ctx_sha512,(void*) hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHA512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_haval256_5_init(&ctx_haval);
	sph_haval256_5(&ctx_haval,(const void*) hash, dataLen);
	sph_haval256_5_close(&ctx_haval, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--HAVAL256--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	memset(&hash[8], 0, dataLen - 32);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--AFTER MEMSET--");

	sph_blake512_init(&ctx_blake);
	sph_blake512(&ctx_blake, hash, dataLen);
	sph_blake512_close(&ctx_blake, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BLAKE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_bmw512_init(&ctx_bmw);
	sph_bmw512(&ctx_bmw, hash, dataLen);
	sph_bmw512_close(&ctx_bmw, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--BMW512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_groestl512_init(&ctx_groestl);
	sph_groestl512(&ctx_groestl, hash, dataLen);
	sph_groestl512_close(&ctx_groestl, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--GROESTL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_skein512_init(&ctx_skein);
	sph_skein512(&ctx_skein, hash, dataLen);
	sph_skein512_close(&ctx_skein, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SKEIN512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_jh512_init(&ctx_jh);
	sph_jh512(&ctx_jh, hash, dataLen);
	sph_jh512_close(&ctx_jh, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--JH512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_keccak512_init(&ctx_keccak);
	sph_keccak512(&ctx_keccak, hash, dataLen);
	sph_keccak512_close(&ctx_keccak, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--KECCAK512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_luffa512_init(&ctx_luffa);
	sph_luffa512(&ctx_luffa, hash, dataLen);
	sph_luffa512_close(&ctx_luffa, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--LUFFA512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_cubehash512_init(&ctx_cubehash);
	sph_cubehash512(&ctx_cubehash, hash, dataLen);
	sph_cubehash512_close(&ctx_cubehash, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--CUBEHASH512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_shavite512_init(&ctx_shavite);
	sph_shavite512(&ctx_shavite, hash, dataLen);
	sph_shavite512_close(&ctx_shavite, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHAVITE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_simd512_init(&ctx_simd);
	sph_simd512(&ctx_simd, hash, dataLen);
	sph_simd512_close(&ctx_simd, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SIMD512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_echo512_init(&ctx_echo);
	sph_echo512(&ctx_echo, hash, dataLen);
	sph_echo512_close(&ctx_echo, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--ECHO512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_hamsi512_init(&ctx_hamsi);
	sph_hamsi512(&ctx_hamsi, hash, dataLen);
	sph_hamsi512_close(&ctx_hamsi, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--HAMSI512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_fugue512_init(&ctx_fugue);
	sph_fugue512(&ctx_fugue, hash, dataLen);
	sph_fugue512_close(&ctx_fugue, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--FUGUE512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_shabal512_init(&ctx_shabal);
	sph_shabal512(&ctx_shabal, hash, dataLen);
	sph_shabal512_close(&ctx_shabal, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHABAL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_whirlpool_init(&ctx_whirlpool);
	sph_whirlpool(&ctx_whirlpool, hash, dataLen);
	sph_whirlpool_close(&ctx_whirlpool, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--WHIRLPOOL512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_sha512_init(&ctx_sha512);
	sph_sha512(&ctx_sha512,(const void*) hash, dataLen);
	sph_sha512_close(&ctx_sha512,(void*) hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--SHA512--");
	//for (int i = 0; i<32; i++) hash[i] = 0;

	sph_haval256_5_init(&ctx_haval);
	sph_haval256_5(&ctx_haval,(const void*) hash, dataLen);
	sph_haval256_5_close(&ctx_haval, hash);

	print_hash(hash, 32);
	gpulog(LOG_WARNING, 0, "--HAVAL256--");

	for (int i = 0; i<32; i++) hash[i] = 0;

	memcpy(output, hash, 32);
}

static bool init[MAX_GPUS] = { 0 };





extern "C" int scanhash_x17(int thr_id, struct work* work, uint32_t max_nonce, unsigned long *hashes_done){

	int dev_id = device_map[thr_id];

	uint32_t *pdata = work->data;
	uint32_t *ptarget = work->target;
	const uint32_t first_nonce = pdata[19];
	uint32_t default_throughput;
	if(device_sm[dev_id]<=500) default_throughput = 1<<20;
	else if(device_sm[dev_id]<=520) default_throughput = 1<<21;
	else if(device_sm[dev_id]>520) default_throughput = (1<<22) + (1<<21);
	
	if((strstr(device_name[dev_id], "1060")))default_throughput = 1<<20;
	if((strstr(device_name[dev_id], "1070")))default_throughput = 1<<20;
	if((strstr(device_name[dev_id], "1080")))default_throughput = 1<<20;
	
	uint32_t throughput = cuda_default_throughput(thr_id, default_throughput); // 19=256*256*8;
	if (init[thr_id]) throughput = min(throughput, max_nonce - first_nonce);

	throughput&=0xFFFFFF70; //multiples of 128 due to simd_echo kernel

	if (opt_benchmark)
		((uint32_t*)ptarget)[7] = 0xff;

	gpulog(LOG_INFO,thr_id,"target %x %x %x",ptarget[5], ptarget[6], ptarget[7]);
        gpulog(LOG_INFO,thr_id,"target %llx",*(uint64_t*)&ptarget[6]);

	if (!init[thr_id])
	{
		cudaSetDevice(device_map[thr_id]);
		if (opt_cudaschedule == -1 && gpu_threads == 1) {
			cudaDeviceReset();
			// reduce cpu usage
			cudaSetDeviceFlags(cudaDeviceScheduleBlockingSync);
		}
		gpulog(LOG_INFO,thr_id, "Intensity set to %g, %u cuda threads", throughput2intensity(throughput), throughput);

		x15_whirlpool_cpu_init(thr_id, throughput, 0);
		groestl512_cpu_init(thr_id, throughput);
		x11_simd512_cpu_init(thr_id, throughput);
		CUDA_SAFE_CALL(cudaMalloc(&d_hash[thr_id], 8 * sizeof(uint64_t) * throughput));
		CUDA_SAFE_CALL(cudaMalloc(&d_resNonce[thr_id], NBN * sizeof(uint32_t)));
		h_resNonce[thr_id] = (uint32_t*) malloc(NBN  * 8 * sizeof(uint32_t));
		if(h_resNonce[thr_id] == NULL){
			gpulog(LOG_ERR,thr_id,"Host memory allocation failed");
			exit(EXIT_FAILURE);
		}		
		init[thr_id] = true;
	}

	uint32_t _ALIGN(64) endiandata[20];
	for (int k=0; k < 20; k++)
		be32enc(&endiandata[k], pdata[k]);

	quark_blake512_cpu_setBlock_80(thr_id, endiandata);
	cudaMemset(d_resNonce[thr_id], 0xff, NBN*sizeof(uint32_t));


	do {
		// Hash with CUDA

		quark_blake512_cpu_hash_80(thr_id, throughput, pdata[19], d_hash[thr_id]);//A

		quark_groestl512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);

		quark_skein512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);

		quark_jh512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);//A //fast

		x11_luffa512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);//A

		x11_cubehash512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //A 256

		xevan_shavite512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//P slow r2
		 
        x11_simd512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);  //A slow r3
		 
		x11_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//A
		 
        x13_hamsi512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		 
		x13_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast ++
		 
		//x13_hamsi_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		x14_shabal512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		 
		xevan_whirlpool_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //opt2
		 
		xevan_sha512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		 
		xevan_haval512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		 
        quark_blake512_cpu_hash_128(thr_id, throughput,  d_hash[thr_id]);//BAD
		 
        quark_bmw512_cpu_hash_64x(thr_id, throughput, NULL, d_hash[thr_id]);
		 
		quark_groestl512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);
		 
        quark_skein512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);
		 
        quark_jh512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);
		 
        x11_luffa512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);//A
		 
        x11_cubehash512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        xevan_shavite512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//move to shared
		 
        x11_simd512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); 
		 
        x11_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        x13_hamsi512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        x13_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
		//x13_hamsi_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
        x14_shabal512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        xevan_whirlpool_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
        xevan_sha512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
		 
		xevan_haval512_cpu_hash_64_final(thr_id, throughput, d_hash[thr_id],d_resNonce[thr_id],*(uint64_t*)&ptarget[6]);
		 

		cudaMemcpy(h_resNonce[thr_id], d_resNonce[thr_id], NBN*sizeof(uint32_t), cudaMemcpyDeviceToHost);

		if (h_resNonce[thr_id][0] != UINT32_MAX){
			const uint32_t Htarg = ptarget[7];
			const uint32_t startNounce = pdata[19];
			uint32_t vhash64[8];
			be32enc(&endiandata[19], startNounce + h_resNonce[thr_id][0]);
			x17hash(vhash64, endiandata);
//			*hashes_done = pdata[19] - first_nonce + throughput + 1;
//			pdata[19] = startNounce + h_resNonce[thr_id][0];
			gpulog(LOG_WARNING, 0,"NONCE FOUND ");
//			return 1;
			if (vhash64[7] <= Htarg && fulltest(vhash64, ptarget)) {
				int res = 1;
				*hashes_done = pdata[19] - first_nonce + throughput + 1;
				work_set_target_ratio(work, vhash64);
				pdata[19] = startNounce + h_resNonce[thr_id][0];
				if (h_resNonce[thr_id][1] != UINT32_MAX) {
					pdata[21] = startNounce+h_resNonce[thr_id][1];
					if(!opt_quiet)
						gpulog(LOG_BLUE,dev_id,"Found 2nd nonce: %08x", pdata[21]);
					be32enc(&endiandata[19], pdata[21]);
					x17hash(vhash64, endiandata);
					if (bn_hash_target_ratio(vhash64, ptarget) > work->shareratio[0]){
						work_set_target_ratio(work, vhash64);
						xchg(pdata[19],pdata[21]);
					}
					res++;
				}
				return res;
			}
			else {
				gpulog(LOG_WARNING, thr_id, "result for %08x does not validate on CPU!", h_resNonce[thr_id][0]);
				cudaMemset(d_resNonce[thr_id], 0xff, NBN*sizeof(uint32_t));				
			}
		}

		pdata[19] += throughput;
	} while (!work_restart[thr_id].restart && ((uint64_t)max_nonce > (uint64_t)throughput + pdata[19]));

	*hashes_done = pdata[19] - first_nonce + 1;

	return 0;
}

// cleanup
extern "C" void free_x17(int thr_id)
{
	if (!init[thr_id])
		return;

	cudaDeviceSynchronize();

	free(h_resNonce[thr_id]);
	cudaFree(d_resNonce[thr_id]);
	cudaFree(d_hash[thr_id]);

	x11_simd_echo_512_cpu_free(thr_id);
	x15_whirlpool_cpu_free(thr_id);
	cudaDeviceSynchronize();
	init[thr_id] = false;
}

Then recompile and run for a few seconds, before first rejected share. Send me your output in PM or publish it here.

Thanks for everybody in advance!

Bump!
Any help much appreciated.

Seems no *nix user wants to help MS guys 

Will have to wait for krnlx to run it on his machine.

[integrale]

im running on "nix"   if i can help ?  im not a pro   but can try it

[stas260385]

It's from Z-pool bench:


xevan   26h   1070   GeForce GTX 1070   10de:119d   SM 6.1   2.27 MH   21   1822   109   20.791 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 382.53
xevan   17h   1070   EVGA GTX 1070 FTW   3842:6276   SM 6.1   2.26 MH   21   1797   101   22.363 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 385.28
xevan   16h   1070   EVGA GTX 1070 FTW   3842:6276   SM 6.1   2.26 MH   21   1797   108   20.905 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 385.28
xevan   17h   1070   EVGA GTX 1070 FTW   3842:6276   SM 6.1   2.26 MH   21   1797   107   21.088 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 385.28
xevan   17h   1070   EVGA GTX 1070 FTW   3842:6276   SM 6.1   2.25 MH   21   1797   107   21.074 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 385.28
xevan   26h   1070   GeForce GTX 1070   10de:119d   SM 6.1   2.25 MH   21   1822   110   20.479 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 382.53
xevan   17h   1070   EVGA GTX 1070 FTW   3842:6276   SM 6.1   2.25 MH   21   1797   104   21.658 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 385.28
xevan   16h   1070   EVGA GTX 1070 FTW   3842:6276   SM 6.1   2.25 MH   21   1797   140   16.056 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 385.28
xevan   17h   1070   EVGA GTX 1070 FTW   3842:6276   SM 6.1   2.25 MH   21   1797   91   24.674 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 385.28
xevan   17h   1070   EVGA GTX 1070 FTW   3842:6276   SM 6.1   2.24 MH   21   1797   108   20.739 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 385.28
xevan   17h   1070   EVGA GTX 1070 FTW   3842:6276   SM 6.1   2.24 MH   21   1797   105   21.308 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 385.28
xevan   17h   1070   EVGA GTX 1070 FTW   3842:6276   SM 6.1   2.24 MH   21   1797   96   23.289 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 385.28
xevan   2d   1070   GeForce GTX 1070   10de:119d   SM 6.1   2 MH   21   1683   79   25.305 k   ccminer/8.13-KlausT   linux   CUDA 8.0 375.66
xevan   2d   1080 Ti   GeForce GTX 1080 Ti   10de:120f   SM 6.1   1.97 MH   21   1721   81   24.36 k   cpuminer-opt/6.6.6   win64   CUDA 8.0 384.94
xevan   2d   1080 Ti   GeForce GTX 1080 Ti   10de:120f   SM 6.1   1.9 MH   21   1721   186   10.209 k   ccminer/8.13-dj   win64   CUDA 8.0 384.94
xevan   2d   1080 Ti   GeForce GTX 1080 Ti   10de:120f   SM 6.1   1.71 MH   21   1721   96   17.835 k   ccminer/8.13-dj   win64   CUDA 8.0 384.94
xevan   2d   1080 Ti   GeForce GTX 1080 Ti   10de:120f   SM 6.1   1.61 MH   21   1721   153   10.535 k   ccminer/8.13-dj   win64   CUDA 8.0 384.94
xevan   2d   1080 Ti   GeForce GTX 1080 Ti   10de:120f   SM 6.1   1.54 MH   21   1721   117   13.157 k   ccminer/8.13-dj   win64   CUDA 8.0 384.94
xevan   2d   1080 Ti   GeForce GTX 1080 Ti   10de:120f   SM 6.1   1.52 MH   21   1721   106   14.386 k   ccminer/8.13-dj   win64   CUDA 8.0 384.94
xevan   2d   1080 Ti   GeForce GTX 1080 Ti   10de:120f   SM 6.1   1.48 MH   21   1721   124   11.964 k   ccminer/8.13-dj   win64   CUDA 8.0 384.94

[sickofscamcoins]

http://paste.ubuntu.com/25680610/

this is results of output, replacing x17.cu and recompile with one posted palgin.

[palgin]

http://paste.ubuntu.com/25680610/

this is results of output, replacing x17.cu and recompile with one posted palgin.

Thank you, will check it!

[integrale]

copied from my Linux build   x17.cu  hopefully it helps

Code:

/**
 * X17 algorithm (X15 + sha512 + haval256)
 */

extern "C" {
#include "sph/sph_blake.h"
#include "sph/sph_bmw.h"
#include "sph/sph_groestl.h"
#include "sph/sph_skein.h"
#include "sph/sph_jh.h"
#include "sph/sph_keccak.h"

#include "sph/sph_luffa.h"
#include "sph/sph_cubehash.h"
#include "sph/sph_shavite.h"
#include "sph/sph_simd.h"
#include "sph/sph_echo.h"

#include "sph/sph_hamsi.h"
#include "sph/sph_fugue.h"

#include "sph/sph_shabal.h"
#include "sph/sph_whirlpool.h"

#include "sph/sph_sha2.h"
#include "sph/sph_haval.h"
}

#include "miner.h"
#include "cuda_helper.h"
#include "x11/cuda_x11.h"

#define NBN 2

// Memory for the hash functions
static uint32_t *d_hash[MAX_GPUS];
static uint32_t *d_resNonce[MAX_GPUS];
static uint32_t *h_resNonce[MAX_GPUS];

extern void x13_hamsi_fugue512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x14_shabal512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x15_whirlpool_cpu_init(int thr_id, uint32_t threads, int mode);
extern void x15_whirlpool_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x15_whirlpool_cpu_free(int thr_id);

extern void x17_sha512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x17_haval256_cpu_hash_64_final(int thr_id, uint32_t threads, uint32_t *d_hash, uint32_t* resNonce, uint64_t target);
extern void bmw256_cpu_hash_32_full(int thr_id, uint32_t threads, uint32_t *g_hash);
extern void quark_bmw512_cpu_hash_64x(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_hash);
extern void quark_groestl512(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void groestl512_cpu_init(int thr_id, uint32_t threads);
extern void groestl512_cpu_hash(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_skein512(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void keccak_xevan_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void qubit_luffa512_cpu_hash_80(int thr_id, uint32_t threads, uint32_t startNounce, uint32_t *d_outputHash);
extern void x11_cubehash512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_shavite512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_shavite512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_echo512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_echo512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_simd512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_simd512_cpu_init(int thr_id, uint32_t threads);
extern void xevan_simd512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x13_hamsi512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x13_fugue512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_whirlpool_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_sha512_cpu_hash_64(int thr_id, int threads, uint32_t *d_hash);
extern void xevan_haval512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void quark_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_outputHash);
extern void xevan_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_haval512_cpu_hash_64_final(int thr_id, uint32_t threads, uint32_t *d_hash, uint32_t *resNonce, uint64_t target);
extern void xevan_groestl512_cpu_hash(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void keccak_xevan_cpu_hash_64_A(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void quark_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_outputHash);
extern void quark_blake512_cpu_hash_128(int thr_id, uint32_t threads, uint32_t *d_outputHash);
extern void quark_groestl512_cpu_hash_128(int thr_id, uint32_t threads,  uint32_t *d_hash);
extern void x11_luffa512_cpu_hash_128(int thr_id, uint32_t threads,uint32_t *d_hash);



// X17 CPU Hash (Validation)
extern "C" void x17hash(void *output, const void *input)
{
	uint32_t _ALIGN(64) hash[32]; // 128 bytes required
	const int dataLen = 128;
//return;
	sph_blake512_context     ctx_blake;
	sph_bmw512_context       ctx_bmw;
	sph_groestl512_context   ctx_groestl;
	sph_skein512_context     ctx_skein;
	sph_jh512_context        ctx_jh;
	sph_keccak512_context    ctx_keccak;
	sph_luffa512_context     ctx_luffa;
	sph_cubehash512_context  ctx_cubehash;
	sph_shavite512_context   ctx_shavite;
	sph_simd512_context      ctx_simd;
	sph_echo512_context      ctx_echo;
	sph_hamsi512_context     ctx_hamsi;
	sph_fugue512_context     ctx_fugue;
	sph_shabal512_context    ctx_shabal;
	sph_whirlpool_context    ctx_whirlpool;
	sph_sha512_context       ctx_sha512;
	sph_haval256_5_context   ctx_haval;

//print_hash(input,20);
	sph_blake512_init(&ctx_blake);
	sph_blake512(&ctx_blake, input, 80);
	sph_blake512_close(&ctx_blake, hash);
//print_hash(hash,32);
	memset(&hash[16], 0, 64);

	sph_bmw512_init(&ctx_bmw);
	sph_bmw512(&ctx_bmw, hash, dataLen);
	sph_bmw512_close(&ctx_bmw, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_groestl512_init(&ctx_groestl);
	sph_groestl512(&ctx_groestl, hash, dataLen);
	sph_groestl512_close(&ctx_groestl, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;

	sph_skein512_init(&ctx_skein);
	sph_skein512(&ctx_skein, hash, dataLen);
	sph_skein512_close(&ctx_skein, hash);

//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_jh512_init(&ctx_jh);
	sph_jh512(&ctx_jh, hash, dataLen);
	sph_jh512_close(&ctx_jh, hash);
//print_hash(hash,32);

	sph_keccak512_init(&ctx_keccak);
	sph_keccak512(&ctx_keccak, hash, dataLen);
	sph_keccak512_close(&ctx_keccak, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_luffa512_init(&ctx_luffa);
	sph_luffa512(&ctx_luffa, hash, dataLen);
	sph_luffa512_close(&ctx_luffa, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_cubehash512_init(&ctx_cubehash);
	sph_cubehash512(&ctx_cubehash, hash, dataLen);
	sph_cubehash512_close(&ctx_cubehash, hash);
//print_hash(hash,32);
	sph_shavite512_init(&ctx_shavite);
	sph_shavite512(&ctx_shavite, hash, dataLen);
	sph_shavite512_close(&ctx_shavite, hash);
//print_hash(hash,32);
	sph_simd512_init(&ctx_simd);
	sph_simd512(&ctx_simd, hash, dataLen);
	sph_simd512_close(&ctx_simd, hash);
//print_hash(hash,32);
	sph_echo512_init(&ctx_echo);
	sph_echo512(&ctx_echo, hash, dataLen);
	sph_echo512_close(&ctx_echo, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_hamsi512_init(&ctx_hamsi);
	sph_hamsi512(&ctx_hamsi, hash, dataLen);
	sph_hamsi512_close(&ctx_hamsi, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_fugue512_init(&ctx_fugue);
	sph_fugue512(&ctx_fugue, hash, dataLen);
	sph_fugue512_close(&ctx_fugue, hash);
//print_hash(hash,32);
	sph_shabal512_init(&ctx_shabal);
	sph_shabal512(&ctx_shabal, hash, dataLen);
	sph_shabal512_close(&ctx_shabal, hash);
//print_hash(hash,32);
	sph_whirlpool_init(&ctx_whirlpool);
	sph_whirlpool(&ctx_whirlpool, hash, dataLen);
	sph_whirlpool_close(&ctx_whirlpool, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_sha512_init(&ctx_sha512);
	sph_sha512(&ctx_sha512,(const void*) hash, dataLen);
	sph_sha512_close(&ctx_sha512,(void*) hash);
//print_hash(hash,32);
	sph_haval256_5_init(&ctx_haval);
	sph_haval256_5(&ctx_haval,(const void*) hash, dataLen);
	sph_haval256_5_close(&ctx_haval, hash);
//print_hash(hash,32);

	memset(&hash[8], 0, dataLen - 32);

	sph_blake512_init(&ctx_blake);
	sph_blake512(&ctx_blake, hash, dataLen);
	sph_blake512_close(&ctx_blake, hash);

//print_hash(hash,32);

	sph_bmw512_init(&ctx_bmw);
	sph_bmw512(&ctx_bmw, hash, dataLen);
	sph_bmw512_close(&ctx_bmw, hash);

	sph_groestl512_init(&ctx_groestl);
	sph_groestl512(&ctx_groestl, hash, dataLen);
	sph_groestl512_close(&ctx_groestl, hash);

	sph_skein512_init(&ctx_skein);
	sph_skein512(&ctx_skein, hash, dataLen);
	sph_skein512_close(&ctx_skein, hash);

	sph_jh512_init(&ctx_jh);
	sph_jh512(&ctx_jh, hash, dataLen);
	sph_jh512_close(&ctx_jh, hash);

	sph_keccak512_init(&ctx_keccak);
	sph_keccak512(&ctx_keccak, hash, dataLen);
	sph_keccak512_close(&ctx_keccak, hash);

	sph_luffa512_init(&ctx_luffa);
	sph_luffa512(&ctx_luffa, hash, dataLen);
	sph_luffa512_close(&ctx_luffa, hash);

	sph_cubehash512_init(&ctx_cubehash);
	sph_cubehash512(&ctx_cubehash, hash, dataLen);
	sph_cubehash512_close(&ctx_cubehash, hash);

	sph_shavite512_init(&ctx_shavite);
	sph_shavite512(&ctx_shavite, hash, dataLen);
	sph_shavite512_close(&ctx_shavite, hash);

	sph_simd512_init(&ctx_simd);
	sph_simd512(&ctx_simd, hash, dataLen);
	sph_simd512_close(&ctx_simd, hash);

	sph_echo512_init(&ctx_echo);
	sph_echo512(&ctx_echo, hash, dataLen);
	sph_echo512_close(&ctx_echo, hash);

	sph_hamsi512_init(&ctx_hamsi);
	sph_hamsi512(&ctx_hamsi, hash, dataLen);
	sph_hamsi512_close(&ctx_hamsi, hash);

	sph_fugue512_init(&ctx_fugue);
	sph_fugue512(&ctx_fugue, hash, dataLen);
	sph_fugue512_close(&ctx_fugue, hash);

	sph_shabal512_init(&ctx_shabal);
	sph_shabal512(&ctx_shabal, hash, dataLen);
	sph_shabal512_close(&ctx_shabal, hash);

	sph_whirlpool_init(&ctx_whirlpool);
	sph_whirlpool(&ctx_whirlpool, hash, dataLen);
	sph_whirlpool_close(&ctx_whirlpool, hash);

	sph_sha512_init(&ctx_sha512);
	sph_sha512(&ctx_sha512,(const void*) hash, dataLen);
	sph_sha512_close(&ctx_sha512,(void*) hash);

//print_hash(hash,32);
	sph_haval256_5_init(&ctx_haval);
	sph_haval256_5(&ctx_haval,(const void*) hash, dataLen);
	sph_haval256_5_close(&ctx_haval, hash);
//print_hash(hash,8);
	memcpy(output, hash, 32);
}

static bool init[MAX_GPUS] = { 0 };


void print_hash(unsigned int *data,int size){
for(int i=0;i<size;i++)
        gpulog(LOG_WARNING, 0,"%x ",data[i]);
gpulog(LOG_WARNING, 0,"-------------");
}


extern "C" int scanhash_x17(int thr_id, struct work* work, uint32_t max_nonce, unsigned long *hashes_done){

	int dev_id = device_map[thr_id];

	uint32_t *pdata = work->data;
	uint32_t *ptarget = work->target;
	const uint32_t first_nonce = pdata[19];
/*
	uint32_t default_throughput = 1<<20;
	
	if (strstr(device_name[dev_id], "GTX 970")) default_throughput+=256*256*6;
	if (strstr(device_name[dev_id], "GTX 980")) default_throughput =1<<22;
	
	uint32_t throughput = cuda_default_throughput(thr_id, default_throughput); // 19=256*256*8;
*/
	uint32_t default_throughput;
	if(device_sm[dev_id]<=500) default_throughput = 1<<20;
	else if(device_sm[dev_id]<=520) default_throughput = 1<<21;
	else if(device_sm[dev_id]>520) default_throughput = (1<<22) + (1<<21);
	
	if((strstr(device_name[dev_id], "1070")))default_throughput = 1<<20;
	if((strstr(device_name[dev_id], "1080")))default_throughput = 1<<20;
	
	uint32_t throughput = cuda_default_throughput(thr_id, default_throughput); // 19=256*256*8;
	if (init[thr_id]) throughput = min(throughput, max_nonce - first_nonce);

	throughput&=0xFFFFFF70; //multiples of 128 due to simd_echo kernel

	if (opt_benchmark)
		((uint32_t*)ptarget)[7] = 0xff;

	gpulog(LOG_INFO,thr_id,"target %x %x %x",ptarget[5], ptarget[6], ptarget[7]);
        gpulog(LOG_INFO,thr_id,"target %llx",*(uint64_t*)&ptarget[6]);

	if (!init[thr_id])
	{
		cudaSetDevice(device_map[thr_id]);
		if (opt_cudaschedule == -1 && gpu_threads == 1) {
			cudaDeviceReset();
			// reduce cpu usage
			cudaSetDeviceFlags(cudaDeviceScheduleBlockingSync);
//			cudaDeviceSetCacheConfig(cudaFuncCachePreferShared);
		}
		gpulog(LOG_INFO,thr_id, "Intensity set to %g, %u cuda threads", throughput2intensity(throughput), throughput);

//		x11_simd_echo_512_cpu_init(thr_id, throughput);
		x15_whirlpool_cpu_init(thr_id, throughput, 0);
		groestl512_cpu_init(thr_id, throughput);
		x11_simd512_cpu_init(thr_id, throughput);
//for(;;);
		CUDA_SAFE_CALL(cudaMalloc(&d_hash[thr_id], 8 * sizeof(uint64_t) * throughput));
		CUDA_SAFE_CALL(cudaMalloc(&d_resNonce[thr_id], NBN * sizeof(uint32_t)));
		h_resNonce[thr_id] = (uint32_t*) malloc(NBN  * 8 * sizeof(uint32_t));
		if(h_resNonce[thr_id] == NULL){
			gpulog(LOG_ERR,thr_id,"Host memory allocation failed");
			exit(EXIT_FAILURE);
		}		
		init[thr_id] = true;
	}

	uint32_t _ALIGN(64) endiandata[20];
	for (int k=0; k < 20; k++)
		be32enc(&endiandata[k], pdata[k]);
//		endiandata[k]=0;
//	print_hash(endiandata,20);
	quark_blake512_cpu_setBlock_80(thr_id, endiandata);
	cudaMemset(d_resNonce[thr_id], 0xff, NBN*sizeof(uint32_t));
//	x11_simd512_cpu_init(thr_id, throughput);
//	for(;;);
	do {
		// Hash with CUDA


		quark_blake512_cpu_hash_80(thr_id, throughput, pdata[19], d_hash[thr_id]);//A
		quark_groestl512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);

		quark_skein512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);
		quark_jh512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);//A //fast
//		keccak_xevan_cpu_hash_64_A(thr_id, throughput,  d_hash[thr_id]);//A

//cudaMemset(d_hash[thr_id], 0x00, 16*sizeof(uint32_t));
//		x11_luffa512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //P
//cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16*sizeof(uint32_t), cudaMemcpyDeviceToHost);
//print_hash(h_resNonce[thr_id],16);
//cudaMemset(d_hash[thr_id], 0x00, 16*sizeof(uint32_t));

		x11_luffa512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);//A
//cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16*sizeof(uint32_t), cudaMemcpyDeviceToHost);
//print_hash(h_resNonce[thr_id],16);
//for(;;);

		x11_cubehash512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //A 256
		xevan_shavite512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//P slow r2
                x11_simd512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);  //A slow r3

//                cudaMemset(d_hash[thr_id], 0x00, 16*sizeof(uint32_t));


//		xevan_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //slow r1

//                cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16*sizeof(uint32_t), cudaMemcpyDeviceToHost);
//		print_hash(h_resNonce[thr_id],16);


  //              cudaMemset(d_hash[thr_id], 0x00, 16*sizeof(uint32_t));

		x11_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//A


//                cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16*sizeof(uint32_t), cudaMemcpyDeviceToHost);
 //               print_hash(h_resNonce[thr_id],16);

//for(;;);

                x13_hamsi512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		x13_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast ++
		x14_shabal512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		xevan_whirlpool_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //opt2
		xevan_sha512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast
		xevan_haval512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast


//		xevan_blake512_cpu_hash_64(thr_id, throughput,  d_hash[thr_id]);//BAD
quark_blake512_cpu_hash_128(thr_id, throughput,  d_hash[thr_id]);//BAD

//
                quark_bmw512_cpu_hash_64x(thr_id, throughput, NULL, d_hash[thr_id]);
//                xevan_groestl512_cpu_hash(thr_id, throughput, d_hash[thr_id]);
quark_groestl512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);

//                xevan_skein512(thr_id, throughput, d_hash[thr_id]);
                quark_skein512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);

                quark_jh512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);
//                keccak_xevan_cpu_hash_64_A(thr_id, throughput,  d_hash[thr_id]);
//                x11_luffa512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
                x11_luffa512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);//A

                x11_cubehash512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
                xevan_shavite512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//move to shared
                x11_simd512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); 

//                xevan_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
                x11_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);

                x13_hamsi512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
                x13_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
                x14_shabal512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
                xevan_whirlpool_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
                xevan_sha512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);







/*
for(int i = 10000;i< 10016;i++){
                cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][16*i], 16*sizeof(uint32_t), cudaMemcpyDeviceToHost);
print_hash(h_resNonce[thr_id],8);
}
		for(;;);

*/
		xevan_haval512_cpu_hash_64_final(thr_id, throughput, d_hash[thr_id],d_resNonce[thr_id],*(uint64_t*)&ptarget[6]);

		cudaMemcpy(h_resNonce[thr_id], d_resNonce[thr_id], NBN*sizeof(uint32_t), cudaMemcpyDeviceToHost);

		if (h_resNonce[thr_id][0] != UINT32_MAX){
			const uint32_t Htarg = ptarget[7];
			const uint32_t startNounce = pdata[19];
			uint32_t vhash64[8];
			be32enc(&endiandata[19], startNounce + h_resNonce[thr_id][0]);
			x17hash(vhash64, endiandata);
//			*hashes_done = pdata[19] - first_nonce + throughput + 1;
//			pdata[19] = startNounce + h_resNonce[thr_id][0];
			gpulog(LOG_WARNING, 0,"NONCE FOUND ");
//			return 1;
			if (vhash64[7] <= Htarg && fulltest(vhash64, ptarget)) {
				int res = 1;
				*hashes_done = pdata[19] - first_nonce + throughput + 1;
				work_set_target_ratio(work, vhash64);
				pdata[19] = startNounce + h_resNonce[thr_id][0];
				if (h_resNonce[thr_id][1] != UINT32_MAX) {
					pdata[21] = startNounce+h_resNonce[thr_id][1];
					if(!opt_quiet)
						gpulog(LOG_BLUE,dev_id,"Found 2nd nonce: %08x", pdata[21]);
					be32enc(&endiandata[19], pdata[21]);
					x17hash(vhash64, endiandata);
					if (bn_hash_target_ratio(vhash64, ptarget) > work->shareratio[0]){
						work_set_target_ratio(work, vhash64);
						xchg(pdata[19],pdata[21]);
					}
					res++;
				}
				return res;
			}
			else {
				gpulog(LOG_WARNING, thr_id, "result for %08x does not validate on CPU!", h_resNonce[thr_id][0]);
				cudaMemset(d_resNonce[thr_id], 0xff, NBN*sizeof(uint32_t));				
			}
		}

		pdata[19] += throughput;
	} while (!work_restart[thr_id].restart && ((uint64_t)max_nonce > (uint64_t)throughput + pdata[19]));

	*hashes_done = pdata[19] - first_nonce + 1;

	return 0;
}

// cleanup
extern "C" void free_x17(int thr_id)
{
	if (!init[thr_id])
		return;

	cudaDeviceSynchronize();

	free(h_resNonce[thr_id]);
	cudaFree(d_resNonce[thr_id]);
	cudaFree(d_hash[thr_id]);

	x11_simd_echo_512_cpu_free(thr_id);
	x15_whirlpool_cpu_free(thr_id);
	cudaDeviceSynchronize();
	init[thr_id] = false;
}

[sickofscamcoins]

http://paste.ubuntu.com/25680610/

this is results of output, replacing x17.cu and recompile with one posted palgin.

Thank you, will check it!

http://paste.ubuntu.com/25680643/

no escape characters this time

[palgin]

UPDATE: Hashing is exactly the same as on Win, so it comes out to be very weird problem. The one thing I suspect is ulong and uint compiler handling difference on Win and on *nix, for example, ulong will be equal to uint64_t on 64-bit build, but different on 32-bit build. Will look into this way, maybe will come up with something.

[sickofscamcoins]

welp i tried for my cookie anyways.  Anything else I can do to help lmk

[Nesp]

Any binaries?

[anorganix]

Any binaries?

Yes, we have 0 and 1.

[palgin]

Next part of check, now GPU part. All the same, x17.cu is following:

Code:

/**
 * X17 algorithm (X15 + sha512 + haval256)
 */

extern "C" {
#include "sph/sph_blake.h"
#include "sph/sph_bmw.h"
#include "sph/sph_groestl.h"
#include "sph/sph_skein.h"
#include "sph/sph_jh.h"
#include "sph/sph_keccak.h"

#include "sph/sph_luffa.h"
#include "sph/sph_cubehash.h"
#include "sph/sph_shavite.h"
#include "sph/sph_simd.h"
#include "sph/sph_echo.h"

#include "sph/sph_hamsi.h"
#include "sph/sph_fugue.h"

#include "sph/sph_shabal.h"
#include "sph/sph_whirlpool.h"

#include "sph/sph_sha2.h"
#include "sph/sph_haval.h"
}

#include "miner.h"
#include "cuda_helper.h"
#include "x11/cuda_x11.h"

#define NBN 2

// Memory for the hash functions
static uint32_t *d_hash[MAX_GPUS];
static uint32_t *d_resNonce[MAX_GPUS];
static uint32_t *h_resNonce[MAX_GPUS];

extern void x13_hamsi_fugue512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x14_shabal512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x15_whirlpool_cpu_init(int thr_id, uint32_t threads, int mode);
extern void x15_whirlpool_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x15_whirlpool_cpu_free(int thr_id);

extern void x17_sha512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);

extern void x17_haval256_cpu_hash_64_final(int thr_id, uint32_t threads, uint32_t *d_hash, uint32_t* resNonce, uint64_t target);
extern void bmw256_cpu_hash_32_full(int thr_id, uint32_t threads, uint32_t *g_hash);
extern void quark_bmw512_cpu_hash_64x(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_hash);
extern void quark_groestl512(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void groestl512_cpu_init(int thr_id, uint32_t threads);
extern void groestl512_cpu_hash(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_skein512(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void keccak_xevan_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void qubit_luffa512_cpu_hash_80(int thr_id, uint32_t threads, uint32_t startNounce, uint32_t *d_outputHash);
extern void x11_cubehash512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_shavite512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_shavite512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_echo512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_echo512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_simd512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x11_simd512_cpu_init(int thr_id, uint32_t threads);
extern void xevan_simd512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x13_hamsi512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x13_fugue512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_whirlpool_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_sha512_cpu_hash_64(int thr_id, int threads, uint32_t *d_hash);
extern void xevan_haval512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void quark_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_outputHash);
extern void xevan_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void xevan_haval512_cpu_hash_64_final(int thr_id, uint32_t threads, uint32_t *d_hash, uint32_t *resNonce, uint64_t target);
extern void xevan_groestl512_cpu_hash(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void keccak_xevan_cpu_hash_64_A(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void quark_blake512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_nonceVector, uint32_t *d_outputHash);
extern void quark_blake512_cpu_hash_128(int thr_id, uint32_t threads, uint32_t *d_outputHash);
extern void quark_groestl512_cpu_hash_128(int thr_id, uint32_t threads,  uint32_t *d_hash);
extern void x11_luffa512_cpu_hash_128(int thr_id, uint32_t threads,uint32_t *d_hash);



// X17 CPU Hash (Validation)
extern "C" void x17hash(void *output, const void *input)
{
	uint32_t _ALIGN(64) hash[32]; // 128 bytes required
	const int dataLen = 128;
//return;
	sph_blake512_context     ctx_blake;
	sph_bmw512_context       ctx_bmw;
	sph_groestl512_context   ctx_groestl;
	sph_skein512_context     ctx_skein;
	sph_jh512_context        ctx_jh;
	sph_keccak512_context    ctx_keccak;
	sph_luffa512_context     ctx_luffa;
	sph_cubehash512_context  ctx_cubehash;
	sph_shavite512_context   ctx_shavite;
	sph_simd512_context      ctx_simd;
	sph_echo512_context      ctx_echo;
	sph_hamsi512_context     ctx_hamsi;
	sph_fugue512_context     ctx_fugue;
	sph_shabal512_context    ctx_shabal;
	sph_whirlpool_context    ctx_whirlpool;
	sph_sha512_context       ctx_sha512;
	sph_haval256_5_context   ctx_haval;

//print_hash(input,20);
	sph_blake512_init(&ctx_blake);
	sph_blake512(&ctx_blake, input, 80);
	sph_blake512_close(&ctx_blake, hash);
//print_hash(hash,32);
	memset(&hash[16], 0, 64);

	sph_bmw512_init(&ctx_bmw);
	sph_bmw512(&ctx_bmw, hash, dataLen);
	sph_bmw512_close(&ctx_bmw, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_groestl512_init(&ctx_groestl);
	sph_groestl512(&ctx_groestl, hash, dataLen);
	sph_groestl512_close(&ctx_groestl, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;

	sph_skein512_init(&ctx_skein);
	sph_skein512(&ctx_skein, hash, dataLen);
	sph_skein512_close(&ctx_skein, hash);

//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_jh512_init(&ctx_jh);
	sph_jh512(&ctx_jh, hash, dataLen);
	sph_jh512_close(&ctx_jh, hash);
//print_hash(hash,32);

	sph_keccak512_init(&ctx_keccak);
	sph_keccak512(&ctx_keccak, hash, dataLen);
	sph_keccak512_close(&ctx_keccak, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_luffa512_init(&ctx_luffa);
	sph_luffa512(&ctx_luffa, hash, dataLen);
	sph_luffa512_close(&ctx_luffa, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_cubehash512_init(&ctx_cubehash);
	sph_cubehash512(&ctx_cubehash, hash, dataLen);
	sph_cubehash512_close(&ctx_cubehash, hash);
//print_hash(hash,32);
	sph_shavite512_init(&ctx_shavite);
	sph_shavite512(&ctx_shavite, hash, dataLen);
	sph_shavite512_close(&ctx_shavite, hash);
//print_hash(hash,32);
	sph_simd512_init(&ctx_simd);
	sph_simd512(&ctx_simd, hash, dataLen);
	sph_simd512_close(&ctx_simd, hash);
//print_hash(hash,32);
	sph_echo512_init(&ctx_echo);
	sph_echo512(&ctx_echo, hash, dataLen);
	sph_echo512_close(&ctx_echo, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_hamsi512_init(&ctx_hamsi);
	sph_hamsi512(&ctx_hamsi, hash, dataLen);
	sph_hamsi512_close(&ctx_hamsi, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_fugue512_init(&ctx_fugue);
	sph_fugue512(&ctx_fugue, hash, dataLen);
	sph_fugue512_close(&ctx_fugue, hash);
//print_hash(hash,32);
	sph_shabal512_init(&ctx_shabal);
	sph_shabal512(&ctx_shabal, hash, dataLen);
	sph_shabal512_close(&ctx_shabal, hash);
//print_hash(hash,32);
	sph_whirlpool_init(&ctx_whirlpool);
	sph_whirlpool(&ctx_whirlpool, hash, dataLen);
	sph_whirlpool_close(&ctx_whirlpool, hash);
//print_hash(hash,32);
//for(int i=0;i<32;i++)hash[i]=0;
	sph_sha512_init(&ctx_sha512);
	sph_sha512(&ctx_sha512,(const void*) hash, dataLen);
	sph_sha512_close(&ctx_sha512,(void*) hash);
//print_hash(hash,32);
	sph_haval256_5_init(&ctx_haval);
	sph_haval256_5(&ctx_haval,(const void*) hash, dataLen);
	sph_haval256_5_close(&ctx_haval, hash);
//print_hash(hash,32);

	memset(&hash[8], 0, dataLen - 32);

	sph_blake512_init(&ctx_blake);
	sph_blake512(&ctx_blake, hash, dataLen);
	sph_blake512_close(&ctx_blake, hash);

//print_hash(hash,32);

	sph_bmw512_init(&ctx_bmw);
	sph_bmw512(&ctx_bmw, hash, dataLen);
	sph_bmw512_close(&ctx_bmw, hash);

	sph_groestl512_init(&ctx_groestl);
	sph_groestl512(&ctx_groestl, hash, dataLen);
	sph_groestl512_close(&ctx_groestl, hash);

	sph_skein512_init(&ctx_skein);
	sph_skein512(&ctx_skein, hash, dataLen);
	sph_skein512_close(&ctx_skein, hash);

	sph_jh512_init(&ctx_jh);
	sph_jh512(&ctx_jh, hash, dataLen);
	sph_jh512_close(&ctx_jh, hash);

	sph_keccak512_init(&ctx_keccak);
	sph_keccak512(&ctx_keccak, hash, dataLen);
	sph_keccak512_close(&ctx_keccak, hash);

	sph_luffa512_init(&ctx_luffa);
	sph_luffa512(&ctx_luffa, hash, dataLen);
	sph_luffa512_close(&ctx_luffa, hash);

	sph_cubehash512_init(&ctx_cubehash);
	sph_cubehash512(&ctx_cubehash, hash, dataLen);
	sph_cubehash512_close(&ctx_cubehash, hash);

	sph_shavite512_init(&ctx_shavite);
	sph_shavite512(&ctx_shavite, hash, dataLen);
	sph_shavite512_close(&ctx_shavite, hash);

	sph_simd512_init(&ctx_simd);
	sph_simd512(&ctx_simd, hash, dataLen);
	sph_simd512_close(&ctx_simd, hash);

	sph_echo512_init(&ctx_echo);
	sph_echo512(&ctx_echo, hash, dataLen);
	sph_echo512_close(&ctx_echo, hash);

	sph_hamsi512_init(&ctx_hamsi);
	sph_hamsi512(&ctx_hamsi, hash, dataLen);
	sph_hamsi512_close(&ctx_hamsi, hash);

	sph_fugue512_init(&ctx_fugue);
	sph_fugue512(&ctx_fugue, hash, dataLen);
	sph_fugue512_close(&ctx_fugue, hash);

	sph_shabal512_init(&ctx_shabal);
	sph_shabal512(&ctx_shabal, hash, dataLen);
	sph_shabal512_close(&ctx_shabal, hash);

	sph_whirlpool_init(&ctx_whirlpool);
	sph_whirlpool(&ctx_whirlpool, hash, dataLen);
	sph_whirlpool_close(&ctx_whirlpool, hash);

	sph_sha512_init(&ctx_sha512);
	sph_sha512(&ctx_sha512,(const void*) hash, dataLen);
	sph_sha512_close(&ctx_sha512,(void*) hash);

//print_hash(hash,32);
	sph_haval256_5_init(&ctx_haval);
	sph_haval256_5(&ctx_haval,(const void*) hash, dataLen);
	sph_haval256_5_close(&ctx_haval, hash);
//print_hash(hash,8);
	memcpy(output, hash, 32);
}

static bool init[MAX_GPUS] = { 0 };


void print_hash(unsigned int *data,int size){
for(int i=0;i<size;i++)
        gpulog(LOG_WARNING, 0,"%x ",data[i]);
gpulog(LOG_WARNING, 0,"-------------");
}


extern "C" int scanhash_x17(int thr_id, struct work* work, uint32_t max_nonce, unsigned long *hashes_done){

	int dev_id = device_map[thr_id];

	uint32_t *pdata = work->data;
	uint32_t *ptarget = work->target;
	const uint32_t first_nonce = pdata[19];
/*
	uint32_t default_throughput = 1<<20;
	
	if (strstr(device_name[dev_id], "GTX 970")) default_throughput+=256*256*6;
	if (strstr(device_name[dev_id], "GTX 980")) default_throughput =1<<22;
	
	uint32_t throughput = cuda_default_throughput(thr_id, default_throughput); // 19=256*256*8;
*/
	uint32_t default_throughput;
	if(device_sm[dev_id]<=500) default_throughput = 1<<20;
	else if(device_sm[dev_id]<=520) default_throughput = 1<<21;
	else if(device_sm[dev_id]>520) default_throughput = (1<<22) + (1<<21);
	
	if((strstr(device_name[dev_id], "1070")))default_throughput = 1<<20;
	if((strstr(device_name[dev_id], "1080")))default_throughput = 1<<20;
	
	uint32_t throughput = cuda_default_throughput(thr_id, default_throughput); // 19=256*256*8;
	if (init[thr_id]) throughput = min(throughput, max_nonce - first_nonce);

	throughput&=0xFFFFFF70; //multiples of 128 due to simd_echo kernel

	if (opt_benchmark)
		((uint32_t*)ptarget)[7] = 0xff;

	gpulog(LOG_INFO,thr_id,"target %x %x %x",ptarget[5], ptarget[6], ptarget[7]);
        gpulog(LOG_INFO,thr_id,"target %llx",*(uint64_t*)&ptarget[6]);

	if (!init[thr_id])
	{
		cudaSetDevice(device_map[thr_id]);
		if (opt_cudaschedule == -1 && gpu_threads == 1) {
			cudaDeviceReset();
			// reduce cpu usage
			cudaSetDeviceFlags(cudaDeviceScheduleBlockingSync);
//			cudaDeviceSetCacheConfig(cudaFuncCachePreferShared);
		}
		gpulog(LOG_INFO,thr_id, "Intensity set to %g, %u cuda threads", throughput2intensity(throughput), throughput);

//		x11_simd_echo_512_cpu_init(thr_id, throughput);
		x15_whirlpool_cpu_init(thr_id, throughput, 0);
		groestl512_cpu_init(thr_id, throughput);
		x11_simd512_cpu_init(thr_id, throughput);
//for(;;);
		CUDA_SAFE_CALL(cudaMalloc(&d_hash[thr_id], 8 * sizeof(uint64_t) * throughput));
		CUDA_SAFE_CALL(cudaMalloc(&d_resNonce[thr_id], NBN * sizeof(uint32_t)));
		h_resNonce[thr_id] = (uint32_t*) malloc(NBN  * 8 * sizeof(uint32_t));
		if(h_resNonce[thr_id] == NULL){
			gpulog(LOG_ERR,thr_id,"Host memory allocation failed");
			exit(EXIT_FAILURE);
		}		
		init[thr_id] = true;
	}

	uint32_t _ALIGN(64) endiandata[20];
	for (int k=0; k < 20; k++)
		be32enc(&endiandata[k], pdata[k]);
//		endiandata[k]=0;
//	print_hash(endiandata,20);
	quark_blake512_cpu_setBlock_80(thr_id, endiandata);
	cudaMemset(d_resNonce[thr_id], 0xff, NBN*sizeof(uint32_t));
//	x11_simd512_cpu_init(thr_id, throughput);
//	for(;;);
	do {
		// Hash with CUDA


		quark_blake512_cpu_hash_80(thr_id, throughput, pdata[19], d_hash[thr_id]);//A

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id], 16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

		quark_groestl512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16*sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id],16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

		quark_skein512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id], 16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

		quark_jh512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);//A //fast

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id], 16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));
//		keccak_xevan_cpu_hash_64_A(thr_id, throughput,  d_hash[thr_id]);//A

//cudaMemset(d_hash[thr_id], 0x00, 16*sizeof(uint32_t));
//		x11_luffa512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //P
//cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16*sizeof(uint32_t), cudaMemcpyDeviceToHost);
//print_hash(h_resNonce[thr_id],16);
//cudaMemset(d_hash[thr_id], 0x00, 16*sizeof(uint32_t));

		x11_luffa512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);//A

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id], 16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

//cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16*sizeof(uint32_t), cudaMemcpyDeviceToHost);
//print_hash(h_resNonce[thr_id],16);
//for(;;);

		x11_cubehash512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //A 256

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id], 16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

		xevan_shavite512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//P slow r2

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id], 16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

                x11_simd512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);  //A slow r3

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));


//                cudaMemset(d_hash[thr_id], 0x00, 16*sizeof(uint32_t));


//		xevan_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //slow r1

//                cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16*sizeof(uint32_t), cudaMemcpyDeviceToHost);
//		print_hash(h_resNonce[thr_id],16);


  //              cudaMemset(d_hash[thr_id], 0x00, 16*sizeof(uint32_t));

		x11_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//A

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id], 16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));



//                cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16*sizeof(uint32_t), cudaMemcpyDeviceToHost);
 //               print_hash(h_resNonce[thr_id],16);

//for(;;);

                x13_hamsi512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

		x13_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast ++

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id], 16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

		x14_shabal512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id], 16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

		xevan_whirlpool_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //opt2

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id], 16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

		xevan_sha512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id], 16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

		xevan_haval512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); //fast

		cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
		print_hash(h_resNonce[thr_id], 16);
		cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));



//		xevan_blake512_cpu_hash_64(thr_id, throughput,  d_hash[thr_id]);//BAD
quark_blake512_cpu_hash_128(thr_id, throughput,  d_hash[thr_id]);//BAD

cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
print_hash(h_resNonce[thr_id], 16);
cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));


//
                quark_bmw512_cpu_hash_64x(thr_id, throughput, NULL, d_hash[thr_id]);

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

//                xevan_groestl512_cpu_hash(thr_id, throughput, d_hash[thr_id]);
quark_groestl512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);

cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
print_hash(h_resNonce[thr_id], 16);


//                xevan_skein512(thr_id, throughput, d_hash[thr_id]);
                quark_skein512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));


                quark_jh512_cpu_hash_64(thr_id, throughput, NULL, d_hash[thr_id]);

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

//                keccak_xevan_cpu_hash_64_A(thr_id, throughput,  d_hash[thr_id]);
//                x11_luffa512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
                x11_luffa512_cpu_hash_128(thr_id, throughput, d_hash[thr_id]);//A

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));


                x11_cubehash512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

                xevan_shavite512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);//move to shared

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

                x11_simd512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); 

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));


//                xevan_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);
                x11_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));


                x13_hamsi512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

                x13_fugue512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

                x14_shabal512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

                xevan_whirlpool_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));

                xevan_sha512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]);

				cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][0], 16 * sizeof(uint32_t), cudaMemcpyDeviceToHost);
				print_hash(h_resNonce[thr_id], 16);
				cudaMemset(d_hash[thr_id], 0x00, 16 * sizeof(uint32_t));








/*
for(int i = 10000;i< 10016;i++){
                cudaMemcpy(h_resNonce[thr_id], &d_hash[thr_id][16*i], 16*sizeof(uint32_t), cudaMemcpyDeviceToHost);
print_hash(h_resNonce[thr_id],8);
}
		for(;;);

*/
		xevan_haval512_cpu_hash_64_final(thr_id, throughput, d_hash[thr_id],d_resNonce[thr_id],*(uint64_t*)&ptarget[6]);

		cudaMemcpy(h_resNonce[thr_id], d_resNonce[thr_id], NBN*sizeof(uint32_t), cudaMemcpyDeviceToHost);

		print_hash(h_resNonce[thr_id], 16);

		if (h_resNonce[thr_id][0] != UINT32_MAX){
			const uint32_t Htarg = ptarget[7];
			const uint32_t startNounce = pdata[19];
			uint32_t vhash64[8];
			be32enc(&endiandata[19], startNounce + h_resNonce[thr_id][0]);
			x17hash(vhash64, endiandata);
//			*hashes_done = pdata[19] - first_nonce + throughput + 1;
//			pdata[19] = startNounce + h_resNonce[thr_id][0];
			gpulog(LOG_WARNING, 0,"NONCE FOUND ");
//			return 1;
			if (vhash64[7] <= Htarg && fulltest(vhash64, ptarget)) {
				int res = 1;
				*hashes_done = pdata[19] - first_nonce + throughput + 1;
				work_set_target_ratio(work, vhash64);
				pdata[19] = startNounce + h_resNonce[thr_id][0];
				if (h_resNonce[thr_id][1] != UINT32_MAX) {
					pdata[21] = startNounce+h_resNonce[thr_id][1];
					if(!opt_quiet)
						gpulog(LOG_BLUE,dev_id,"Found 2nd nonce: %08x", pdata[21]);
					be32enc(&endiandata[19], pdata[21]);
					x17hash(vhash64, endiandata);
					if (bn_hash_target_ratio(vhash64, ptarget) > work->shareratio[0]){
						work_set_target_ratio(work, vhash64);
						xchg(pdata[19],pdata[21]);
					}
					res++;
				}
				return res;
			}
			else {
				gpulog(LOG_WARNING, thr_id, "result for %08x does not validate on CPU!", h_resNonce[thr_id][0]);
				cudaMemset(d_resNonce[thr_id], 0xff, NBN*sizeof(uint32_t));				
			}
		}

		pdata[19] += throughput;
	} while (!work_restart[thr_id].restart && ((uint64_t)max_nonce > (uint64_t)throughput + pdata[19]));

	*hashes_done = pdata[19] - first_nonce + 1;

	return 0;
}

// cleanup
extern "C" void free_x17(int thr_id)
{
	if (!init[thr_id])
		return;

	cudaDeviceSynchronize();

	free(h_resNonce[thr_id]);
	cudaFree(d_resNonce[thr_id]);
	cudaFree(d_hash[thr_id]);

	x11_simd_echo_512_cpu_free(thr_id);
	x15_whirlpool_cpu_free(thr_id);
	cudaDeviceSynchronize();
	init[thr_id] = false;
}

Thanks for everybody who helps in investigation.

UPDATE: think I've found the bug, it's in xevan_haval512_cpu_hash_64_final function, so h_resNonce[0] and h_resNonce[1] are always random on Win with exactly the same input data... Need confirmation that behaviour is different on *nix, of course. CUDA memcpy bug?

[Nesp]

Any binaries?

Yes, we have 0 and 1.

Hahah, nice one

[sickofscamcoins]

Next part of check, now GPU part. All the same, x17.cu is following:


http://paste.ubuntu.com/25681179/

[palgin]

Next part of check, now GPU part. All the same, x17.cu is following:


http://paste.ubuntu.com/25681179/

Thank you, you're really helping, will check now.

UPDATE: Hmm, behaviour is the same, but what is more strange, pool accepts shares? That shouldn't be this way, my mind blows off, think everybody should wait for krnlx comments, he's the code author 

[anorganix]

It has something to do with platform target (x86/x64) for sure.
See below how it behaves for x86.

[magnacartic]

Somehow I got stuck at the api.cpp stage during compilation:

ccminer-util.o: In function `stratum_handle_method':
util.cpp:(.text+0x4af3): undefined reference to `gpu_power(cgpu_info*)'
util.cpp:(.text+0x4b51): undefined reference to `nvml_get_current_clocks(int, unsigned int*, unsigned int*)'
util.cpp:(.text+0x4b59): undefined reference to `gpu_info(cgpu_info*)'
ccminer-api.o: In function `gpustatus(int)':
api.cpp:(.text+0x554): undefined reference to `gpu_busid(cgpu_info*)'
api.cpp:(.text+0x560): undefined reference to `gpu_temp(cgpu_info*)'
api.cpp:(.text+0x56b): undefined reference to `gpu_fanpercent(cgpu_info*)'
api.cpp:(.text+0x57b): undefined reference to `gpu_fanrpm(cgpu_info*)'
api.cpp:(.text+0x587): undefined reference to `gpu_power(cgpu_info*)'
ccminer-api.o: In function `gpuhwinfos(int)':
api.cpp:(.text+0xbf0): undefined reference to `gpu_busid(cgpu_info*)'
api.cpp:(.text+0xbfc): undefined reference to `gpu_temp(cgpu_info*)'
api.cpp:(.text+0xc07): undefined reference to `gpu_fanpercent(cgpu_info*)'
api.cpp:(.text+0xc17): undefined reference to `gpu_fanrpm(cgpu_info*)'
api.cpp:(.text+0xc23): undefined reference to `gpu_pstate(cgpu_info*)'
api.cpp:(.text+0xc2f): undefined reference to `gpu_power(cgpu_info*)'
api.cpp:(.text+0xc42): undefined reference to `gpu_info(cgpu_info*)'
collect2: error: ld returned 1 exit status
make[2]: *** [ccminer] Error 1

Any ideas on how to fix this? Compiling on Ubuntu 14.04 & CUDA 8.0

[milliza]

i try to build it on visual studio 2013 but i get next error

error LNK1181: cannot open input file 'libcurl.x64.lib' ccminer

can someone help me ?

[ZenFr]

it works fine with cuda8, ubuntu16,suprnova, gtx1080ti get  5.6m @core clock+100, 200watts.

Compilation with no problem under Ubuntu 16.04 and Cuda 8.
But, when I start the ccminer, he ask me for the Cuda 7.5 library...
How do you make to use the Cuda 8 library (Cuda 7.5 is not installed on this new RIG installation) ?

[palgin]

it works fine with cuda8, ubuntu16,suprnova, gtx1080ti get  5.6m @core clock+100, 200watts.

Compilation with no problem under Ubuntu 16.04 and Cuda 8.
But, when I start the ccminer, he ask me for the Cuda 7.5 library...
How do you make to use the Cuda 8 library (Cuda 7.5 is not installed on this new RIG installation) ?

Check /usr/local  for cuda folders. Default coming in configure.sh is cuda 7.5

[sp_]

I don't undestand why you spend so much time on a non profitable shitcoin. So many coders, and no progress. I buildt the shit on windows in 30 minutes and it works perfectly fine... 5 pages already with puppet postings.

[ans34]

I don't undestand why you spend so much time on a non profitable shitcoin. So many coders, and no progress. I buildt the shit on windows in 30 minutes and it works perfectly fine... 5 pages already with puppet postings.

If it is shitcoin and non profit why don't you share binaries?

[anorganix]

Dear sp_,

Stop being an ass for once.
Seriously now, is it worth it?!

[palgin]

I don't undestand why you spend so much time on a non profitable shitcoin. So many coders, and no progress. I buildt the shit on windows in 30 minutes and it works perfectly fine... 5 pages already with puppet postings.

So, sell it for 200 bucks/copy and claim bounties, make yourself richer, you know it  

It's just fun, debugging always train your skills  

[sp_]

sorry, the bin is under GPL licence. You have to wait for the cuda-students to do the job for free..

Works great on linux. Let the shitcoins be mined on linux..

[integrale]

let him talking  bla bla ,
we are his pain in the a..  because Xevan-gpu goes public for free

[palgin]

OK, I give up on this for today.

For krnlx, if he needs it, of course:

Win output after single roll

It's clear from the output that resulting hashes from CPU and GPU are completely different.

[sp_]

It's clear from the output that resulting hashes from CPU and GPU are completely different.

The krlx kernel is just another alxis rippoff. Change a few lines of gpl code, and claim the 0.5 btc bounty. The bounty should go to the developers of the alexei miner. 0.5 btc just for changing a few padding bytes??? Really? and not even capable of creating a working windows binary.

[sickofscamcoins]

Dear sp_,

you just wish you got ther^H^H^H^Hmade money off it first.  Here is a spoon, for which to eat my ass.  Much love.

- WindowsWalletDev

[sp_]

When a team of wallet developers are competing with kernel developers, you usually end up with non profitable shitcode. To beat a grandmaster, you need to become a grandmaster.

[DextroFree]

It's clear from the output that resulting hashes from CPU and GPU are completely different.

The krlx kernel is just another alxis rippoff. Change a few lines of gpl code, and claim the 0.5 btc bounty. The bounty should go to the developers of the alexei miner. 0.5 btc just for changing a few padding bytes??? Really? and not even capable of creating a working windows binary.

Are you trolling yourself? Isn't that exactly what you did for months?

[UrsaUrsa]

This totally reminds me of the time when I was so into unlocking phones. You had the devs who were stealing from each other and the ones who actually developed stuff. But on a serious level SP_, which coins do you consider to be not-so-shitcoin?

[PandaVLike]

When a team of wallet developers are competing with kernel developers, you usually end up with non profitable shitcode. To beat a grandmaster, you need to become a grandmaster.

Why so salty sp_ ? and what is the point keep pointing out non profitable shitcode, what you gain from this? To beat a grandmaster obviously you need be grandmaster, yet you are not grandmaster..hahahaha

[Thebestis7950]

when will we see windows version
i cant do linux im not very smart

[sickofscamcoins]

Dear Palgin & krnlx (and Alexis & Epsylon),

Thank you so much for your work, I see great things for ccminer dev scene with you guys.  You guys have not forgotten the childlike wonder and excitement in tinkering.  Don't ever become like sp_ -- and don't ever let his toxicity scare you guys off.  You guys are assets to CUDA mining scene.  I am amateur crypto farmer, big enough to benefit from small gains but too small to afford every new sp_ bin.  It's not all about money -- yes, we are all here to make money -- but some also enjoy the hobbyist aspect of this stuff too.  I play around with ccminer code too for fun, and just bought two books on CUDA development.  Maybe one day I can join you guys.  sp_ sits all day in his little safe zone thumping his dick against the kitchen table about how great he is, and comes here to piss on others with his "oh it's 30 minute job" -- if it is 30 minute job, then contribute or fuck off.  How do you think people become as "great" as you?  They put their nose to the grindstone and work hard.  

  WindowsWalletDev  

p.s. sp_ when exactly did you realize you liked men

[ZenFr]

it works fine with cuda8, ubuntu16,suprnova, gtx1080ti get  5.6m @core clock+100, 200watts.

Compilation with no problem under Ubuntu 16.04 and Cuda 8.
But, when I start the ccminer, he ask me for the Cuda 7.5 library...
How do you make to use the Cuda 8 library (Cuda 7.5 is not installed on this new RIG installation) ?

Check /usr/local  for cuda folders. Default coming in configure.sh is cuda 7.5

Thank you.
I made the update of my paths (i forgot that was an old USB key with Cuda 7.5 previously installed :-)).
Works fine, thank you dev.

[CH0DE]

When a team of wallet developers are competing with kernel developers, you usually end up with non profitable shitcode. To beat a grandmaster, you need to become a grandmaster.

SP I am so sorry you feel this way.  I mean your miner mods are very mediocre in hash improvement.  They also overheat my gpus and I need to wear earplugs around the house.  I actually bought some because of your over compensation of gpu power which ends up costing me more anyway.  SleepSoft by Alpine, great reusable earplugs.  I highly recommend them when using an SP mod.  I also accuse you of a very minor but noticeable hash stealing code in one or two of your miners.  I will look into it more and let the community know of your blatant rascality and theft.

[antantti]

Wow, I must have missed something, sp_ why are you megatrolling in krnlx's thread? Why are you so pissed off?

[tazmako]

Thank

[maxmad_x]

LOL this whole thread..

All the hard work was done by original developers such as Palgin, krnlx, Alexis & Epsylon

sp_ is just a cheap hooker profiting off their hard work!

[NameTaken]

I checked pool API and why is one miner getting such high rejection?

Code:

    {
      "version": "ccminer/krnlx-xevan",
      "password": "c=BTC,id=miner2",
      "ID": "",
      "algo": "xevan",
      "difficulty": 26,
      "subscribe": 1,
      "accepted": 17867034.631,
      "rejected": 0
    },
    {
      "version": "ccminer/krnlx-xevan",
      "password": "c=BTC,id=miner3",
      "ID": "",
      "algo": "xevan",
      "difficulty": 46,
      "subscribe": 1,
      "accepted": 28976764.001,
      "rejected": 14660155.037
    },

[ZenFr]

I checked pool API and why is one miner getting such high rejection?

Code:

    {
      "version": "ccminer/krnlx-xevan",
      "password": "c=BTC,id=miner2",
      "ID": "",
      "algo": "xevan",
      "difficulty": 26,
      "subscribe": 1,
      "accepted": 17867034.631,
      "rejected": 0
    },
    {
      "version": "ccminer/krnlx-xevan",
      "password": "c=BTC,id=miner3",
      "ID": "",
      "algo": "xevan",
      "difficulty": 46,
      "subscribe": 1,
      "accepted": 28976764.001,
      "rejected": 14660155.037
    },

Perhaps because the difficulty of your second miner : "difficulty" : 46.
46 is a wrong value for CCMiner.
26 is a accepted value, but huge : what is this RIG ?

[ZenFr]

Anybody can remember me where and the syntax, in the command line, I can manage the difficulty (not the intensity, it is done) ?
Is there a "=" in the syntax or not ?
I think I have not the correct share rate...

[NameTaken]

I checked pool API and why is one miner getting such high rejection?

Code:

    {
      "version": "ccminer/krnlx-xevan",
      "password": "c=BTC,id=miner2",
      "ID": "",
      "algo": "xevan",
      "difficulty": 26,
      "subscribe": 1,
      "accepted": 17867034.631,
      "rejected": 0
    },
    {
      "version": "ccminer/krnlx-xevan",
      "password": "c=BTC,id=miner3",
      "ID": "",
      "algo": "xevan",
      "difficulty": 46,
      "subscribe": 1,
      "accepted": 28976764.001,
      "rejected": 14660155.037
    },

Perhaps because the difficulty of your second miner : "difficulty" : 46.
46 is a wrong value for CCMiner.
26 is a accepted value, but huge : what is this RIG ?

So I should add d=26 in the passwords field?

[Amph]

no windows build yet?

[ZenFr]

I checked pool API and why is one miner getting such high rejection?

Code:

    {
      "version": "ccminer/krnlx-xevan",
      "password": "c=BTC,id=miner2",
      "ID": "",
      "algo": "xevan",
      "difficulty": 26,
      "subscribe": 1,
      "accepted": 17867034.631,
      "rejected": 0
    },
    {
      "version": "ccminer/krnlx-xevan",
      "password": "c=BTC,id=miner3",
      "ID": "",
      "algo": "xevan",
      "difficulty": 46,
      "subscribe": 1,
      "accepted": 28976764.001,
      "rejected": 14660155.037
    },

Perhaps because the difficulty of your second miner : "difficulty" : 46.
46 is a wrong value for CCMiner.
26 is a accepted value, but huge : what is this RIG ?

So I should add d=26 in the passwords field?

I don't know.
Making the difficulty in the password field is working for some specifics configurations like MiningRigRentals, but I don't know if it is OK with this Xevan version of CCMiner.
You/We have to try...
On which pool are you ?

[palgin]

no windows build yet?

No, krnlx is quite busy, I'm off home on holiday trip with only remote access to dev machine, _sp is only trolling  
Debugging is ongoing, but it's quite slow in present conditions.

UPDATE: OK, hope I've fixed it, it's **** Win weirdo syntax problem, now it seems that the rest is on yiimp side (difficulty problem mentioned above).

Proof:


https://imgur.com/tojeKaN.png

It's very pre-alfa build and I won't release it, I'll send source and binaries to krnlx for him to claim bounties.

[konqueror]

It's clear from the output that resulting hashes from CPU and GPU are completely different.

The krlx kernel is just another alxis rippoff. Change a few lines of gpl code, and claim the 0.5 btc bounty. The bounty should go to the developers of the alexei miner. 0.5 btc just for changing a few padding bytes??? Really? and not even capable of creating a working windows binary.

The same way you are not even capable of creating a linux binary but suggesting wine

[anorganix]

no windows build yet?

No, krnlx is quite busy, I'm off home on holiday trip with only remote access to dev machine, _sp is only trolling  
Debugging is ongoing, but it's quite slow in present conditions.

UPDATE: OK, hope I've fixed it, it's **** Win weirdo syntax problem, now it seems that the rest is on yiimp side (difficulty problem mentioned above).

Proof:


https://imgur.com/tojeKaN.png

It's very pre-alfa build and I won't release it, I'll send source and binaries to krnlx for him to claim bounties.

Great news, thanks for the effort!

[palgin]

Great news, thanks for the effort!

Another error showed up, so keep digging code

[ZenFr]

Who know how many time/blocks for the confirmation block with BitSend ?
More than 10 hours and still no block confirmed for me...

[foldingextra]

Nice to know finally xevan algo for nvidia. I will compile it in linux and waiting to try out mining the new solaris soon.

[cryptojai]

no windows build yet?

No, krnlx is quite busy, I'm off home on holiday trip with only remote access to dev machine, _sp is only trolling  
Debugging is ongoing, but it's quite slow in present conditions.

UPDATE: OK, hope I've fixed it, it's **** Win weirdo syntax problem, now it seems that the rest is on yiimp side (difficulty problem mentioned above).

Proof:


https://imgur.com/tojeKaN.png

It's very pre-alfa build and I won't release it, I'll send source and binaries to krnlx for him to claim bounties.

Appreciate your honesty and help for the community . Hope we will at least have a beta build before solaris' new network goes live.

[ZenFr]

For Solaris (XLR) mining : which pool are you using.
I'm trying ZPool and YiImp, but not very efficients.
What pool for XLR mining ?
Thanks.

[palgin]

Finally, bug found and fixed. Windows binary is on the go  

Hope krnlx will publish my win binaries on his GitHub, as a prove of being first dev.

Just wait a bit.

UPDATE: everything compiled and sent to krnlx, the rest is on him. Just check his git from time to time.

[btcman1]

Finally, bug found and fixed. Windows binary is on the go  

Hope krnlx will publish my win binaries on his GitHub, as a prove of being first dev.

Just wait a bit.

Nice news
Good work!. When it is published I will test it with gtx 1070 and 1080 on win 10 x64

[krnlx]

Github updated with Windows binaries. Thanks Palgin!

[Gaglam]

Great news.
Are you peeps mining bitsend or solaris?

[anorganix]

Works like a charm!
Thanks!

[WelcomeHomeCrypto]

Thanks Palgin, you did a great job with the Windows version.

[Gaglam]

Works great, got about 12MH/s with 5x 1070's (Powerlimit 61, Core +150, Mem +400 my ZEC settings)

Still more profitable to mine equihash coins, any suggestions for the Afterburner settings? It's more a powersafe setting.

[rednoW]

Big thanx krnlx and palgin.
Just built cuda7.5x64 version and it seems to be 5% faster then palgin's cuda8x64 build.

[palgin]

It's alexis78 base, optimised for cuda 7.5, so it should be faster. Try x86 build, it's generally faster in CUDA8 not specifically optimised case, or build your own binaries, experiment 

[rednoW]

It's alexis78 base, optimised for cuda 7.5, so it should be faster. Try x86 build, it's generally faster in CUDA8 not specifically optimised case, or build your own binaries, experiment 

No, I love those wattage and temp monitoring in x64 builds so x86 build is not for me ))
And my binary is only 20mb ... yours is 37 ... why?

[Vivik]

25Mh - 8 1070 x64 version

[Gaglam]

25Mh - 8 1070 x64 version

Which core/mem settings do you use?

[Vivik]

25Mh - 8 1070 x64 version

Which core/mem settings do you use?

1860/4400  temp 69~72

[palgin]

No, I love those wattage and temp monitoring in x64 builds so x86 build is not for me ))
And my binary is only 20mb ... yours is 37 ... why?

Static lib linkage and piece of debug information. I can make it lighter, but I don't think binary size matters, especially when source is open.

[stolarzz]

32mh 6x 1080ti Aorus +100 core, +300 mem, power limit 75%

[Gaglam]

CPU#2:GeForce GTX 1070, 2727.58kH/s
CPU#2:GeForce GTX 1070, 0.034MH/W, 0.0017MH/Mhz
CPU#2:GeForce GTX 1070, 61C(F:33%) 1574/4201MHz(81W)


looks good?

[btcman1]

With Stock settings win10 x64:

EVGA GTX 1070
[2017-10-06 14:53:01] GPU#1:EVGA GTX 1070, 3106.90kH/s
[2017-10-06 14:53:01] GPU#1:EVGA GTX 1070, 0.025MH/W, 0.0017MH/Mhz
[2017-10-06 14:53:01] GPU#1:EVGA GTX 1070, 69C(F:49%) 1826/3802MHz(122W)

KFA2 gtx 1080
[2017-10-06 14:54:04] GPU#2:GeForce GTX 1080, 3820.32kH/s
[2017-10-06 14:54:04] GPU#2:GeForce GTX 1080, 0.02MH/W, 0.0021MH/Mhz
[2017-10-06 14:54:04] GPU#2:GeForce GTX 1080, 81C(F:78%) 1859/4513MHz(188W)

[percy_tc]

Is there any way to get a bulited, runable version on Win 10 x64?

[Vivik]

CPU#2:GeForce GTX 1070, 2727.58kH/s
CPU#2:GeForce GTX 1070, 0.034MH/W, 0.0017MH/Mhz
CPU#2:GeForce GTX 1070, 61C(F:33%) 1574/4201MHz(81W)


looks good?

You use your video cards very carefully  

[palgin]

Is there any way to get a bulited, runable version on Win 10 x64?

Chech krnlx github, Releases section

[rednoW]

With Stock settings win10 x64:

EVGA GTX 1070
[2017-10-06 14:53:01] GPU#1:EVGA GTX 1070, 3106.90kH/s
[2017-10-06 14:53:01] GPU#1:EVGA GTX 1070, 0.025MH/W, 0.0017MH/Mhz
[2017-10-06 14:53:01] GPU#1:EVGA GTX 1070, 69C(F:49%) 1826/3802MHz(122W)

KFA2 gtx 1080
[2017-10-06 14:54:04] GPU#2:GeForce GTX 1080, 3820.32kH/s
[2017-10-06 14:54:04] GPU#2:GeForce GTX 1080, 0.02MH/W, 0.0021MH/Mhz
[2017-10-06 14:54:04] GPU#2:GeForce GTX 1080, 81C(F:78%) 1859/4513MHz(188W)

palit gamerock gtx1080 60%tdp 109W
4mH/s

[Vivik]

Krnlx,
Under CUDA8.0 difficult to adapt?

[palgin]

Krnlx,
Under CUDA8.0 difficult to adapt?

You can build it with 7.5, 8.0 or 9.0 without any problem. Code is friendly to CUDA version bump. 9.0 is significantly faster than 8.0, didn't measure against 7.5.

[e6ug]

Thanks for the miner!

[mikebzh44]

Anyone to give GTX 1060 6 Gb hashrate ?

Thanks.

[ZenFr]

Mining since yesterday night and Xevan pay not so much : just a little more than Dagger-Hashimoto in dual mode ith nVidia GPUs.
I'm a little disappointed
Otherwise, good devs work : the miner was runing all the night and no problem with differents GPUs.

[anorganix]

Anyone to give GTX 1060 6 Gb hashrate ?

Thanks.

Check stats on YiiMP.
You should get between 2 - 2.4 MH/s depending on your settings.

[mikebzh44]

Thanks.

[brownfly]

krnlx, great work!   thank you.
I will try your miner soon. regardless of profitability it will be good addition to miners family. Keep going!

[Gaglam]

Krnlx,
Under CUDA8.0 difficult to adapt?

You can build it with 7.5, 8.0 or 9.0 without any problem. Code is friendly to CUDA version bump. 9.0 is significantly faster than 8.0, didn't measure against 7.5.

where to find the 9.0 binary?

[Gaglam]

Mining since yesterday night and Xevan pay not so much : just a little more than Dagger-Hashimoto in dual mode ith nVidia GPUs.
I'm a little disappointed
Otherwise, good devs work : the miner was runing all the night and no problem with differents GPUs.

thats the problem, i'm also back to ZEC
but great miner anyway

[MarcusDe]

Good work, I was waiting for this long time :-)

12MH on 6x 1060 3GB rig.

Problem is it's far less profitable mining bitsend than using that rig on nicehash :-/

[palgin]

where to find the 9.0 binary?

https://mega.nz/#F!RtYS0KwY!FGxr0uBWo1nZBSqBWkFx0w


CUDA 9 built project, feel free to test. Start with intensity 18.

[abudfv2008]

ccminer_x86 looks faster
1060 6Gb ~2500
1070 ~3500
1080 ~4350

[car1999]

Krnlx,
Under CUDA8.0 difficult to adapt?

You can build it with 7.5, 8.0 or 9.0 without any problem. Code is friendly to CUDA version bump. 9.0 is significantly faster than 8.0, didn't measure against 7.5.

can i build it against cuda9 and copy the binary to rigs with only cuda8 installed? does it run slower than  cuda9 rig?
upgrading all my rigs from cuda8 to cuda9 isn't a trivial work, a rig is dead during the upgrade, it cannot boot.

[palgin]

can i build it against cuda9 and copy the binary to rigs with only cuda8 installed? does it run slower than  cuda9 rig?

All you need is recent Nvidia driver with CUDA9 support, you won't need any toolkits installed.

Ooops, you use *nix or Win?

[Ryuh]

Finally miner for xevan, great job guys. Thank you for the hard work!

[car1999]

can i build it against cuda9 and copy the binary to rigs with only cuda8 installed? does it run slower than  cuda9 rig?

All you need is recent Nvidia driver with CUDA9 support, you won't need any toolkits installed.

Great, thanks. Does the CPU of build machine matter? I have G1840, g3900 ,g4560, e3 1231, which one is better to build the binary and copy to other rig with different CPU?

I use ubuntu 16, nvOC.

[palgin]

can i build it against cuda9 and copy the binary to rigs with only cuda8 installed? does it run slower than  cuda9 rig?

All you need is recent Nvidia driver with CUDA9 support, you won't need any toolkits installed.

Great, thanks. Does the CPU of build machine matter? I have G1840, g3900 ,g4560, e3 1231, which one is better to build the binary and copy to other rig with different CPU?

I use ubuntu 16, nvOC.

For *nix it will be a problem (running without reboot), if you already have recent drivers installed, you can ask someone to build binary for you and just update, but if you need to update driver or want to install toolkit and build from scratch - as I know you'll need to reboot at least 1 time. If access is only remote it's quite risky, especially regarding driver module update.

CPU matters, so if you want to build it for all variety of hardware you need to remove "-march=native" flag from configure.sh file.

P.S: I'm not so experienced in *nix, it's just what I remember

[car1999]

can i build it against cuda9 and copy the binary to rigs with only cuda8 installed? does it run slower than  cuda9 rig?

All you need is recent Nvidia driver with CUDA9 support, you won't need any toolkits installed.

Great, thanks. Does the CPU of build machine matter? I have G1840, g3900 ,g4560, e3 1231, which one is better to build the binary and copy to other rig with different CPU?

I use ubuntu 16, nvOC.

For *nix it will be a problem (running without reboot), if you already have recent drivers installed, you can ask someone to build binary for you and just update, but if you need to update driver or want to install toolkit and build from scratch - as I know you'll need to reboot at least 1 time. If access is only remote it's quite risky, especially regarding driver module update.

CPU matters, so if you want to build it for all variety of hardware you need to remove "-march=native" flag from configure.sh file.

P.S: I'm not so experienced in *nix, it's just what I remember

I checked the document of gcc, removing arch=native can lead performance losses, so I think build  against the weakest g1840 is fine.

[UrsaUrsa]

where to find the 9.0 binary?

https://mega.nz/#F!RtYS0KwY!FGxr0uBWo1nZBSqBWkFx0w


CUDA 9 built project, feel free to test. Start with intensity 18.

So weird that the one on github does not get flagged up as a virus but this one does? (false positive, I know)

[stzcze]

Good job!!! Thx

1060 tdp 70 core +150 mem -500

13,66 6x1060 6gb -i 21

latest driver, x86 cuda 9 build, w10

[palgin]

where to find the 9.0 binary?

https://mega.nz/#F!RtYS0KwY!FGxr0uBWo1nZBSqBWkFx0w


CUDA 9 built project, feel free to test. Start with intensity 18.

So weird that the one on github does not get flagged up as a virus but this one does? (false positive, I know)

It's packed, so it gets flagged.

[UrsaUrsa]

where to find the 9.0 binary?

https://mega.nz/#F!RtYS0KwY!FGxr0uBWo1nZBSqBWkFx0w


CUDA 9 built project, feel free to test. Start with intensity 18.

So weird that the one on github does not get flagged up as a virus but this one does? (false positive, I know)

It's packed, so it gets flagged.

I'm obviously not questioning your integrity but found it a bit strange. Is the one github not packed? Have you introduced a fee by any chance? Thanks for your time.

[startsts]

Maximum result that I could get,  seems very profitable 

GPU#0:MSI GTX 1060 3GB, 2178.23kH/s

[Vivik]

CUDA 9.0 x86 - 8x1070 28Mh

[brownfly]

anybody can tell me what I am doing wrong?
When I start the miner with altminer config like this:

Code:

ccminer_x86 -a xevan -o stratum+tcp://eu1.altminer.net:3739 -u Vo...Z -p c=VSX
Windows 10

it always gives me an error message:

Code:

[2017-10-06 13:59:06] Starting on stratum+tcp://eu1.altminer.net:3739
[2017-10-06 13:59:06] NVAPI GPU monitoring enabled.
[2017-10-06 13:59:06] 6 miner threads started, using 'xevan' algorithm.
[2017-10-06 13:59:07] Stratum authentication failed
[2017-10-06 13:59:07] ...retry after 30 seconds

WTF??? coin code is correct, wallet address is correct, startum address is correct, so why it complains???

[stzcze]

Gigabyte GTX 1080 Ti, 5243.33kH/s
Gigabyte GTX 1080, 3855.18kH/s

cuda 9 build x86

tdp 65 -i 21

[UrsaUrsa]

Gigabyte GTX 1080 Ti, 5243.33kH/s
Gigabyte GTX 1080, 3855.18kH/s

cuda 9 build x86

tdp 65 -i 21

cude 9 build x86 (thank god for windows defender...)

tdp 73 -i 21

5x 1070 @ 15.28Mh/s

[Vorona34]

Maximum result that I could get,  seems very profitable 

GPU#0:MSI GTX 1060 3GB, 2178.23kH/s

Long works? I have a miner inevitably die after 1 minute or after 5 , depending on the intensity. Dropped to 14 could not wait for fall, but normal speed not seen )))

[arity]

On linux with CUDA 9 & compile with sm61, 6x1080ti (each power limit 170w) reported hash rate is 30Mh/s. Default intensity.

According to whattomine that hash rate should yield about 1.47 BSD per hour, but the actual shown on pool earning is only 0.8 BSD. Tested on suprnova pool.

[th3.r00t]

anybody can tell me what I am doing wrong?
When I start the miner with altminer config like this:

Code:

ccminer_x86 -a xevan -o stratum+tcp://eu1.altminer.net:3739 -u Vo...Z -p c=VSX
Windows 10

it always gives me an error message:

Code:

[2017-10-06 13:59:06] Starting on stratum+tcp://eu1.altminer.net:3739
[2017-10-06 13:59:06] NVAPI GPU monitoring enabled.
[2017-10-06 13:59:06] 6 miner threads started, using 'xevan' algorithm.
[2017-10-06 13:59:07] Stratum authentication failed
[2017-10-06 13:59:07] ...retry after 30 seconds

WTF??? coin code is correct, wallet address is correct, startum address is correct, so why it complains???

Did you set the intensity manually?

UPD. For 1060 cards intensity sets up incorrectly - you must adjust it with -i param. -i 20 is best for 1070, 1080ti

As far as I see the answer is no. There may be your problem.

[buzzkillb]

1080 hashrate. not ti.

Code:

[S/A/T]: 0/151/151, diff: 0.065, 3794.39kH/s yes!
[S/A/T]: 0/152/152, diff: 0.020, 3794.27kH/s yes!
GPU#0:EVGA GTX 1080, 3799.83kH/s

[integrale]

Your great Work resulted :

Xubuntu 16.04 LTS
Cuda 9
Nv 384.90
i=20.25

Code:

[2017-10-06 22:35:34] GPU#0:NONCE FOUND 
[2017-10-06 22:35:34] GPU#0:MSI GTX 1050, 1113.18kH/s
[2017-10-06 22:35:34] GPU#0:MSI GTX 1050, 0.018MH/W, 0.00063MH/Mhz
[2017-10-06 22:35:34] GPU#0:MSI GTX 1050, 62C(F:56%) 1766/3504MHz(63W)
[2017-10-06 22:35:34] GPU#0:target 0 22c92492 1c9
[2017-10-06 22:35:34] GPU#0:target 1c922c92492
[2017-10-06 22:35:34] [S/A/T]: 0/78/80, diff: 0.004, 1110.65kH/s yes!

thx Guys for The Miner

[blackhorse7]

Windows x64 version, EVGA GTX 1060 + 80 / + 500 / 84% tdp (I didnt change intensity, worked on default = 20): 2240kh/s in benchmark mode.
It works, thank you

[buzzkillb]

It's alexis78 base, optimised for cuda 7.5, so it should be faster. Try x86 build, it's generally faster in CUDA8 not specifically optimised case, or build your own binaries, experiment 

No, I love those wattage and temp monitoring in x64 builds so x86 build is not for me ))
And my binary is only 20mb ... yours is 37 ... why?

How do you check wattage and temp on ccminer?

[brownfly]

Did you set the intensity manually?

UPD. For 1060 cards intensity sets up incorrectly - you must adjust it with -i param. -i 20 is best for 1070, 1080ti

As far as I see the answer is no. There may be your problem.

yes, I did:

ccminer -a xevan -i 20 -o stratum+tcp://eu1.altminer.net:3739 -u Vo...Z -p c=VSX

the same result. I use 1070.

Update: something wrong with my wallet. If I use the wallet id from any recorded transaction, it works! but any addresses from my wallet - they look like invalid for the pool. Any ideas???
I use VSYNC wallet v1.2.3.0-g32a928e

Update: crap, apparently there are two VSYNCs! Downloaded another VSync v 1.0.0.1 and synchronizing...

[spider703]

where to find the 9.0 binary?

https://mega.nz/#F!RtYS0KwY!FGxr0uBWo1nZBSqBWkFx0w


CUDA 9 built project, feel free to test. Start with intensity 18.

hi, i runing your miner on algo myriadgroestl, he gives me 3 Gh and no seach blocks

[brownfly]

finally... the wallet has been synchronized and the miner does work. 6 x 1070 ~ 20 MH/s
Profitability is about like for BTX/VIVO. Not too bad, but still less than my favorite coin

[fr4nkthetank]

the coins are pretty small so expect profitability to stabilize around average profitability...its kinda sad to be honest.  Heres hoping to see a new ZCash some day with a new algo

[car1999]

the coins are pretty small so expect profitability to stabilize around average profitability...its kinda sad to be honest.  Heres hoping to see a new ZCash some day with a new algo

I mined and hold 20k SIGT, but it is going to die. So I think holding small coin is risky, now I exchange BSD to BTC daily.

[UrsaUrsa]

the coins are pretty small so expect profitability to stabilize around average profitability...its kinda sad to be honest.  Heres hoping to see a new ZCash some day with a new algo

I mined and hold 20k SIGT, but it is going to die. So I think holding small coin is risky, now I exchange BSD to BTC daily.

Oh, good old sigt. Worthless

I've been mining Bitsend all night long on suprnova but my balance is still not confirmed. Does it really take so long?

[palgin]

where to find the 9.0 binary?

https://mega.nz/#F!RtYS0KwY!FGxr0uBWo1nZBSqBWkFx0w


CUDA 9 built project, feel free to test. Start with intensity 18.

So weird that the one on github does not get flagged up as a virus but this one does? (false positive, I know)

It's packed, so it gets flagged.

I'm obviously not questioning your integrity but found it a bit strange. Is the one github not packed? Have you introduced a fee by any chance? Thanks for your time.

No fees, it's krnlx code, it's opensource and should stay free. I've just packed executables to take less space on my mega.nz, I keep quite big data there, so space matters in this case, even 50 mb    One on github is not packed.

P.S: don't run miner on yiimp with "-p stats" option, it will fail just after pool asks for stats.

[ZenFr]

Can you put a version number in the source code and the name of this topic ?
It's will be easier to understand for the future of this good program.

I have made a lot of try, but I still not fund a very profitable setting with xevan mining (GTX 1070).

[UrsaUrsa]

Can you put a version number in the source code and the name of this topic ?
It's will be easier to understand for the future of this good program.

I have made a lot of try, but I still not fund a very profitable setting with xevan mining (GTX 1070).

What do you consider very profitable? I didn't expect it to make 50 bucks a day.

[NameTaken]

It was more profitable than ZEC for a while then the Windows version released and pool hashrate went up 5x+ = GG profit

[UrsaUrsa]

It was more profitable than ZEC for a while then the Windows version released and pool hashrate went up 5x+ = GG profit

You're absolutely right, even last night it was more profitable than this morning. Amazing...

[Vcxz]

It was more profitable than ZEC for a while then the Windows version released and pool hashrate went up 5x+ = GG profit

You're absolutely right, even last night it was more profitable than this morning. Amazing...

Diff have come up 2x compare with last week.

[kollom]

Inno3D GTX1080 PL 80


CUDA 8  x64
3476H/s
66C (F;65%) ) 1640/ 4513 MHz (127W)


CUDA 9  x64
3700H/s
66C (F;65%) ) 1640/ 4513 MHz (127W)

[Vivik]

CUDA 9 x86 the fastest.

[brownfly]

hm, significant difference. Is there compiled CUDA 9 x86 binary available? The published one was compiled with CUDA 8.0.

[..XyZ..]

hm, significant difference. Is there compiled CUDA 9 x86 binary available? The published one was compiled with CUDA 8.0.

8 posts above:
https://mega.nz/#F!RtYS0KwY!FGxr0uBWo1nZBSqBWkFx0w

[blackhorse7]

x86 version is faster (2350 vs 2240kh/s = ~5%), but with stats option on zpool it's crashing after 'pool asked for stats' line. x64 version didnt crash

[UrsaUrsa]

x86 version is faster (2350 vs 2240kh/s = ~5%), but with stats option on zpool it's crashing after 'pool asked for stats' line. x64 version didnt crash

What's even funnier is that CUDA9 makes all the other algo's work faster as well. My 5x 1070 rig went from 131mh to 142mh when mining lyra2v2.

@palgin, again, thanks for your contribution. Is this what SP_ does with his releases? XD

[blackhorse7]

omg, 20 tests again...
Thak you guys for coding!

[startsts]

What multiplier has xevan algo?   24 ?

[brownfly]

hm, significant difference. Is there compiled CUDA 9 x86 binary available? The published one was compiled with CUDA 8.0.

8 posts above:
https://mega.nz/#F!RtYS0KwY!FGxr0uBWo1nZBSqBWkFx0w

thx!

[abudfv2008]

What's even funnier is that CUDA9 makes all the other algo's work faster as well. My 5x 1070 rig went from 131mh to 142mh when mining lyra2v2.

5*1070 makes 185-190mh on Lyra2v2

[UrsaUrsa]

What's even funnier is that CUDA9 makes all the other algo's work faster as well. My 5x 1070 rig went from 131mh to 142mh when mining lyra2v2.

5*1070 makes 185-190mh on Lyra2v2

And that's how I realised that one of my cards was not working... I think I'm overstretching that one 750W PSU. Gotta buy another one. However even now I'm only getting 179mh. What settings are you using?

EDIT: i-21 gets it up to 185mh.

[fhakenzz]

hi, I keep on gettin this error

Cuda error in func 'quark_blake512_cpu_setBlock_80' at line 871 : unspecified launch failure.

[Littledragons]

Thanks so much for your work!

I really do appreciate that!

[palgin]

hi, I keep on gettin this error

Cuda error in func 'quark_blake512_cpu_setBlock_80' at line 871 : unspecified launch failure.

Precompiled binary? Intensity is too high, I suppose.

[Vorona34]

Hello. Marking with "target 0 ff ff000000" correct or is it a mistake?

[2017-10-08 08:32:17] GPU#1:target 0 ff000000 ff
[2017-10-08 08:32:17] GPU#1:target ffff000000
[2017-10-08 08:32:20] GPU#1:target 0 ff000000 ff
[2017-10-08 08:32:20] GPU#1:target ffff000000
[2017-10-08 08:32:20] GPU#2:target 0 ff000000 ff
[2017-10-08 08:32:20] GPU#2:target ffff000000
[2017-10-08 08:32:20] GPU#0:target 0 ff000000 ff
[2017-10-08 08:32:20] GPU#0:target ffff000000
[2017-10-08 08:32:22] GPU#2:target 0 ff000000 ff
[2017-10-08 08:32:22] GPU#2:target ffff000000

http://joxi.ru/xAe80qzhp8dP12

[palgin]

Hello. Marking with "target 0 ff ff000000" correct or is it a mistake?

[2017-10-08 08:32:17] GPU#1:target 0 ff000000 ff
[2017-10-08 08:32:17] GPU#1:target ffff000000
[2017-10-08 08:32:20] GPU#1:target 0 ff000000 ff
[2017-10-08 08:32:20] GPU#1:target ffff000000
[2017-10-08 08:32:20] GPU#2:target 0 ff000000 ff
[2017-10-08 08:32:20] GPU#2:target ffff000000
[2017-10-08 08:32:20] GPU#0:target 0 ff000000 ff
[2017-10-08 08:32:20] GPU#0:target ffff000000
[2017-10-08 08:32:22] GPU#2:target 0 ff000000 ff
[2017-10-08 08:32:22] GPU#2:target ffff000000

http://joxi.ru/xAe80qzhp8dP12

Shares accepted, so seems OK

[Vorona34]

Miner on 1060 constantly closed, even with the intensity of 14 so all is not OK.

[palgin]

Miner on 1060 constantly closed, even with the intensity of 14 so all is not OK.

Dear sir, you got miner for free, we were hard working chasing rare bug for win build while you were sitting on your sofa, and now you're complaining something? Go ask _sp to sell you same code for 200$, told already that miner will fail in 2 cases:

1) High overclock
2) -p stats option

I won't comment anymore, as stuff like this drives me angry. AS-IS, roll-roll your boat gently down the stream.

P.S: coвceм oxpeнeли yжe, пoтoмy krnlx ничeгo и нe кoммeнтиpyeт, тaк кaк люди пopoй пpeвpaщaютcя в cвинeй, пoлyчили ПO нaxaлявy, eщe и пpeтeнзии имeют.

[Vorona34]

Cпacибo зa пoмoщь и paзpaбoткy мaйнepa. Я нe имeю пpeтeнзий, a ищy peшeниe пpoблeмы. Ha cчeт "-p" я пpoпycтил.
Bидимo, Bы нe пoняли цeли мoeгo cooбщeния, и нe xoтeли нaзвaть мeня cвиньeй, пoэтoмy я нe cтaнy пocылaть Bac нa *yй.

[rednoW]

Russian battle )))

Ok, I decided to post my cuda 7.5 x64 build
If someone wants he can compare speed with fastest cuda 9 x86 build and post the results.
https://drive.google.com/open?id=0B4flkNGCHIGFa1BQTzEzaUFmaDA

Disclaimer: This was build on my main notebook with a lot of shitcoin wallets so I cannot guarantee it is virus-safe.
Use on your own risk.

Update: Just compared my build with palgin's cuda 9 x86 build. Palgin's faster by 100khs on gtx1070 100% tdp. So no need to download my version ))

[fhakenzz]

hi, I keep on gettin this error

Cuda error in func 'quark_blake512_cpu_setBlock_80' at line 871 : unspecified launch failure.

Precompiled binary? Intensity is too high, I suppose.

lowered my intensity to 18 and OC seems find now., will post again if it crashes., but RN been running for 6 hours straight

[spider703]

Miner on 1060 constantly closed, even with the intensity of 14 so all is not OK.

Dear sir, you got miner for free, we were hard working chasing rare bug for win build while you were sitting on your sofa, and now you're complaining something? Go ask _sp to sell you same code for 200$, told already that miner will fail in 2 cases:

1) High overclock
2) -p stats option

I won't comment anymore, as stuff like this drives me angry. AS-IS, roll-roll your boat gently down the stream.

P.S: coвceм oxpeнeли yжe, пoтoмy krnlx ничeгo и нe кoммeнтиpyeт, тaк кaк люди пopoй пpeвpaщaютcя в cвинeй, пoлyчили ПO нaxaлявy, eщe и пpeтeнзии имeют.

He oбpaщaй нa ниx внимaниe, ты peaльнo пpoдeлaл бoльшyю paбoтy, ecли бы я yмeл paзpaбaтывaть ПO c yдoвoльcтвиeм Baм c krnlx пoмoг. A тex ктo нe дoвoлeн, пycть идyт к sp_ и зa бaблo пoкyпaют eгo вepcию.

[spider703]

Cпacибo зa пoмoщь и paзpaбoткy мaйнepa. Я нe имeю пpeтeнзий, a ищy peшeниe пpoблeмы. Ha cчeт "-p" я пpoпycтил.
Bидимo, Bы нe пoняли цeли мoeгo cooбщeния, и нe xoтeли нaзвaть мeня cвиньeй, пoэтoмy я нe cтaнy пocылaть Bac нa *yй.

Гyгл пepeвeдoчик oднaкo!!! я тoжe тaк пapy paз пpoлeтeл, кoгдa пишeшь oднo, a oн мнe o coвceм дpyгoм пepeвoдит

[spider703]

Russian battle )))

Ok, I decided to post my cuda 7.5 x64 build
If someone wants he can compare speed with fastest cuda 9 x86 build and post the results.
https://drive.google.com/open?id=0B4flkNGCHIGFa1BQTzEzaUFmaDA

Disclaimer: This was build on my main notebook with a lot of shitcoin wallets so I cannot guarantee it is virus-safe.
Use on your own risk.

This is for AMD card?

[rednoW]

Russian battle )))

Ok, I decided to post my cuda 7.5 x64 build
If someone wants he can compare speed with fastest cuda 9 x86 build and post the results.
https://drive.google.com/open?id=0B4flkNGCHIGFa1BQTzEzaUFmaDA

Disclaimer: This was build on my main notebook with a lot of shitcoin wallets so I cannot guarantee it is virus-safe.
Use on your own risk.

This is for AMD card?

It is ccminer )) It is CUDA. It is for nVidia ))

[sp_]

What are you guys getting with the free opensorce miner on the gtx 1060 and 1070?

but what about the 1070. 1060 6g and 1060 6gb?

Here are some preresults. xevan sp-mod 1 (100% tdp)

1. gtx 1070 g1 gaming  (3850 KHASH)
2. gtx 1060 windforce 6gb (2550 KHASH)
2. gtx 1060 gainward 3gb (2420 KHASH)

[Leass]

Miner on 1060 constantly closed, even with the intensity of 14 so all is not OK.

Dear sir, you got miner for free, we were hard working chasing rare bug for win build while you were sitting on your sofa, and now you're complaining something? Go ask _sp to sell you same code for 200$, told already that miner will fail in 2 cases:

1) High overclock
2) -p stats option

I won't comment anymore, as stuff like this drives me angry. AS-IS, roll-roll your boat gently down the stream.

P.S: coвceм oxpeнeли yжe, пoтoмy krnlx ничeгo и нe кoммeнтиpyeт, тaк кaк люди пopoй пpeвpaщaютcя в cвинeй, пoлyчили ПO нaxaлявy, eщe и пpeтeнзии имeют.

So parameters passed in -p crashes miner? My rig crashed yesterday, was hashing superb high for moment (33mh - 5x1080Ti) on stock clocks, now miner is dead and I'll ressurect him tommorow
Thanks for Your work Palgin (&Krnlx)!

[brownfly]

Krnlx, Palgin, thank you for your hard work!
Your miner works very stable at my 1070 rigs. 

[brownfly]

What are you guys getting with the free opensorce miner on the gtx 1060 and 1070?

1. gtx 1070 g1 gaming  (3850 KHASH)

gtx 1070 ASUS Strix O8G - 3475 KHASH/s

[FQ_Neronk]

What are you guys getting with the free opensorce miner on the gtx 1060 and 1070?

1. gtx 1070 g1 gaming  (3850 KHASH)

gtx 1070 ASUS Strix O8G - 3475 KHASH/s

GTX 1070 Gainward - 3625.05 KHASH/s

[kollom]

Krnlx, Palgin really good work, thanks.
sp_ is fat troll

[santan]

Great Work!!!!  krnlx  and Thanks a lot to palgin for serious bug hunting and giving us free Windows build.
This time i tried to compile on CUDA8 and got 1322 errors on VS13, got so terrified that closed Visual Studio immediately.
Maybe because i am compiling on a very old Laptop.

Anyway, Keep up the good work... You guys are the real Hope for the future....

[k0stas]

What are you guys getting with the free opensorce miner on the gtx 1060 and 1070?

but what about the 1070. 1060 6g and 1060 6gb?

Here are some preresults. xevan sp-mod 1 (100% tdp)

1. gtx 1070 g1 gaming  (3850 KHASH)
2. gtx 1060 windforce 6gb (2550 KHASH)
2. gtx 1060 gainward 3gb (2420 KHASH)

I have not play much with my card 1060 3GB i am getting this results if you intresting

[majorlee]

where can we D/L the win version?

[BitBustah]

Rates for 1080 and 1080 TI.


Any ideas on how to increase to reach 6mh? Or are my rates ok?

[sp_]

Bitsend(XEVAN) can be sold, and profit is declining from day to day.

In this thread klrx wrote that the miner does 3.3MHASH on the 1070. I am making a miner that does more than 4MHASH on the gtx 1070. This is the number you need to mine with a profit right now..



current profit 24hours of mining:

3.3Mhash =(0.08774*0.0033)=0,00026322btc= $1.2
4Mhash =(0.08774*0.004)=0,00035096btc= $1.6175



Here is the nicehashminer profit calculator 24 hours: $1.62

[ShowMeCoins]

Bitsend(XEVAN) can be sold, and profit is declining from day to day.

In this thread klrx wrote that the miner does 3.3MHASH on the 1070. I am making a miner that does more than 4MHASH on the gtx 1070. This is the number you need to mine with a profit right now..

Dear '_sp',

I'm a small miner, pushing/punishing my cards to maximize output. Given your long history on this board, you've probably forgotten how long it takes to gather a .5 Bitcoin profit. Every time you post a comment regarding all the worderfull things you can do as a developer, I get sad . Personally I fully understand the reasons for asking compensation for your efforts, but why not using the already common practice of a devfee. Make 2 versions: a commerce version (devfree) and a non-commerce version (devfee). Looking at the numbers you are presenting, I'm seeing an increase in output of about 20%. I wouldn't mind sharing this increase 50/50. The devfee could be as much as 5-8%.

Doing a 5% devfee calculation on 3 popular xevan pools using krnlx-xevan as a reference:

Yiimp: 858.5 MH/s x 5% = 42,925 MH/s
Zpool: 763,1 MH/s x 5% = 38.155 MH/s
Altminer: 980.2MH/s x 5% = 49,01 MH/s
----------------------------------------------
+ 130,09 MH/s  (= 0.08774*0.13009=0,0114140966btc = $ 52,24)

Just wondering what could be achieved if the 3 main contributors would work together, using the devfee as a common account for all developers need (like hardware, office space, hosting costs, etc.). We are talking about just one algo here, add equihash to the equation and income could be 5 times (just speculating) the amount.

[aloneforever]

Code:

[2017-10-09 13:52:05] reject reason: low difficulty share of 0.0000030442944267742225
[2017-10-09 13:52:05] [S/A/T]: 0/3/493, diff: 0.006, 9610.14kH/s booooo
[2017-10-09 13:52:05] reject reason: low difficulty share of 0.000006456882654663993
[2017-10-09 13:52:05] [S/A/T]: 0/3/494, diff: 0.006, 9610.14kH/s booooo
[2017-10-09 13:52:05] reject reason: low difficulty share of 0.000002336367330125864
[2017-10-09 13:52:05] [S/A/T]: 0/3/495, diff: 0.006, 9610.14kH/s booooo
[2017-10-09 13:52:05] reject reason: low difficulty share of 0.000003734128306642016
[2017-10-09 13:52:05] [S/A/T]: 0/3/496, diff: 0.006, 9610.14kH/s booooo
[2017-10-09 13:52:05] reject reason: low difficulty share of 0.0000028502608097857447
[2017-10-09 13:52:05] GPU#1:Found 2nd nonce: 56b0d1eb
[2017-10-09 13:52:05] GPU#1:target 0 30000000 7cff8
[2017-10-09 13:52:05] GPU#1:target 7cff830000000
[2017-10-09 13:52:05] GPU#0:Found 2nd nonce: 013f72e8
[2017-10-09 13:52:05] GPU#0:target 0 30000000 7cff8
[2017-10-09 13:52:05] GPU#0:target 7cff830000000
[2017-10-09 13:52:05] GPU#2:Found 2nd nonce: abe0382b
[2017-10-09 13:52:05] GPU#2:target 0 30000000 7cff8
[2017-10-09 13:52:05] GPU#2:target 7cff830000000
[2017-10-09 13:52:05] Stratum connection interrupted
[2017-10-09 13:52:05] GPU#0:Found 2nd nonce: 01433e6f
[2017-10-09 13:52:05] GPU#1:Found 2nd nonce: 56b4692c
[2017-10-09 13:52:05] GPU#2:Found 2nd nonce: abe3f8ce
[2017-10-09 13:52:05] ...retry after 30 seconds

3x1080 TI ,Win x64 , Cuda 9 .
What i wrong>?
Tnx

[tpd09]

tried compiling with cuda 9 on visual studio 2017 - but I get this error

any help would be great

[gcvanasel]

Has anyone mined Solaris yet? Whould like to know how the Nvidia cards are performing and what your profitability is?

https://bitcointalk.org/index.php?topic=1831629.0

[brownfly]

Dear '_sp',

I'm a small miner, pushing/punishing my cards to maximize output. Given your long history on this board, you've probably forgotten how long it takes to gather a .5 Bitcoin profit.

Absolutely agree. Also _sp is not right about profitability. Since I made a script that calculates earning, it clearly shows that free miner for VSYNC is more profitable than his miner for Bitcore (that he advertises a lot!).
Even for the same coin it requires pretty long time to recover miner price for a small miner. Otherwise it looks we work for _sp   I appreciate his work but let's see the truth.

[hous26]

where to find the 9.0 binary?

https://mega.nz/#F!RtYS0KwY!FGxr0uBWo1nZBSqBWkFx0w


CUDA 9 built project, feel free to test. Start with intensity 18.

Is this a windows version?  I'm interested in mining this algo!

[Cortez7575]

Solo mining is not possible this algo? I tried several xevan coins, but dont work either.

[bodrumair]

What is the suggested intensity for P106 ( GTX 1060 6GB) with Krnlx Nvidia xevan miner?
Currently I used İ 21 and my hasrate is 2230 approximately.
it seems low I think

[stzcze]

where to find the 9.0 binary?

https://mega.nz/#F!RtYS0KwY!FGxr0uBWo1nZBSqBWkFx0w


CUDA 9 built project, feel free to test. Start with intensity 18.

Is this a windows version?  I'm interested in mining this algo!

Yes, it's a windows version, why do not you read what people are writing here?

[BitBustah]

All I can say is that I mine Xevan right now.. Most profitable for me.

[olek82]

Solo mining is not possible this algo? I tried several xevan coins, but dont work either.

ive also tried solo mining but without luck. i think we need the --no-getwork command to mine solo... here are my stats with my gtx1080

https://imgur.com/Ndw2dwe

[Mozzus]

is supernova pool up ?> i used the new mier for windows and i am not able to mine on supernova  this ios how my bat file looks --> ccminer -a xevan -o stratum+tcp://bsd.suprnova.cc:8686 -u Injaabs.slave1 -p x -i 19
pause

do i do something wrong ?

[junforever]

Hi which pool do you recommend to mine bitsend? Thanks

[junforever]

All I can say is that I mine Xevan right now.. Most profitable for me.

Which coin are you mine ?

[Elder III]

Hi which pool do you recommend to mine bitsend? Thanks

Yiimp is good for BitSend. You can also check out Zpool and Suprnova for a couple other bigger pools. There are some small ones too but they may take awhile to find blocks unless you have a number of rigs to point at it.

[Aureliusy]

Running the windows version  Xevan algo (on 4GB 64 bit Win10 with G3900) , but it seems to crash within 24 hrs
Always with:
quark_blake512_cpu_setBlock80 at line 871 an illegal memory access was encountered

EDIT 15/10 Did switch to the x86 windows miner. More hash and more stability (no crash) Same GPU settings.

[santan]

Hi which pool do you recommend to mine bitsend? Thanks

http://yiimp.ccminer.org/

[konqueror]

Running the windows version  Xevan algo (on 4GB 64 bit Win10 with G3900) , but it seems to crash within 24 hrs
Always with:
quark_blake512_cpu_setBlock80 at line 871 an illegal memory access was encountered

Too much overclock?

[junforever]

Hi which pool do you recommend to mine bitsend? Thanks

Yiimp is good for BitSend. You can also check out Zpool and Suprnova for a couple other bigger pools. There are some small ones too but they may take awhile to find blocks unless you have a number of rigs to point at it.

Thanks for the advice

[junforever]

Anyone can help me with the info of which approximately is the daily profit to mine bitsend with nvidia gtx 1080ti? Thanks

[Alex68]

Any ready binary available for Ubuntu 14.04 and cuda 8.0? Thanks!

[gcvanasel]

Hi All,

What is your OC settings for 1070 cards?

[joshuaj]

It is good that xevan no longer cpu mining and support nvidia now. Thanks krnlx

[fhakenzz]

Hi All,

What is your OC settings for 1070 cards?

go for a little 100+ core and -500 memory coz its more of core intensive algo

[sergey777]

where to find the 9.0 binary?

https://mega.nz/#F!RtYS0KwY!FGxr0uBWo1nZBSqBWkFx0w


CUDA 9 built project, feel free to test. Start with intensity 18.

Is this a windows version?  I'm interested in mining this algo!

Yes, it's a windows version, why do not you read what people are writing here?

cтpaннo, нo нa Win7 64bit CUDA 9 ccminer_x86 быcтpee, чeм ccminer_x64  пpимepнo нa 0,17 MH/s
3x1060 3Gb нa ccminer_x64 выдaют пpимepнo 6600 MH/s
3x1060 3Gb нa ccminer_x86 выдaют пpимepнo 6770 MH/s

[buzzkillb]

Anyone figured out how to get this to solomine?

[loatchoat]

Please tell me why and how to fix it
VGA P106

[stas260385]

https://i.imgur.com/McJehK3.jpg

Please tell me why and how to fix it
VGA P106

You must to reduce your intensity. Set it like -i 20
It must help you.

[BitBustah]

1x 1080 Ti + 1x 1080: 9920 MH/s

[loatchoat]

Please tell me why and how to fix it
VGA P106

You must to reduce your intensity. Set it like -i 20
It must help you.

Thank you for your support !
I tried with -i 14, 15, 16, 20, 24 but all have the same result (dump )

[konqueror]

1x 1080 Ti + 1x 1080: 9920 MH/s

MH/s or KH/s? 

[BitBustah]

1x 1080 Ti + 1x 1080: 9920 MH/s

MH/s or KH/s? 

Oops.. There's the wodka again. 9,92 MH/S, 9920 KH/s of course.

[rmd73]

I noticed that the miner will compile only for compute arch 52 and 50...
If one removes the comments for compute arch 35 and 30 (and, of course 20) in Makefile.am, the compilation will fail. Tested on Ubuntu 14.04 with CUDA 7.5 and CUDA 8.
I wanted to experiment mining xevan with older and weaker card(s): an old 570 gtx and a geforce 730... rentability NOT considered
Any clues?

[madmack1]

got this miner compiled in ubuntu 16.04 hitting 5600Khs on VXS is this good for a 1080ti?
i dont overclock everything is standard apart from fan speed

[Elder III]

got this miner compiled in ubuntu 16.04 hitting 5600Khs on VXS is this good for a 1080ti?
i dont overclock everything is standard apart from fan speed

I'm on Windows 10, so I can't say for sure in regards to linux, but I think you're speed is about right. I get 5200-5400 for Xevan per GTX 1080 Ti, depending on the overclock, at 80% power limit. I've seen reports of people being close to 6000, but I think that is both Overclocked and at full power limit.

[loatchoat]

Does anyone know why ccminer xevan 32b mine at hashrate higher than 64b?

[brownfly]

probably because the x64 version has overhead in terms of memory management and it is slower because of that?

[loatchoat]

probably because the x64 version has overhead in terms of memory management and it is slower because of that?

So what does ccminer for 64b do?

[adam1230]

I just start to test xevan miner. Everything works on my end. Need some mods to get more hashrate but its good that there is no dev fee in this miner.

[Makak4R]

I just start to test xevan miner. Everything works on my end. Need some mods to get more hashrate but its good that there is no dev fee in this miner.

just wait! soon there will be a version from SP. not for free of course, for a small bonus you'll get some 10-20% improvements 
no, I do not say that SP is not right, i'm just curious why versions from SP with new algos appears after free version miner has been released?

 

[madmack1]

how do you show GPU temps in this miner?

[Mike011]

80% power limit

Sounds a bit high powerwise.

[Elder III]

80% power limit

Sounds a bit high powerwise.

Could you elaborate? Are you saying that the hashrate is more then you expected for that power limit, or that you would run it at a lower power limit and still get that hashrate?

[fhakenzz]

hi, been follwing this thread., are there any significant upgrades or updates about this miner?

[rmd73]

hi, been follwing this thread., are there any significant upgrades or updates about this miner?

https://github.com/krnlx/ccminer-xevan
Look at the dates and wait for sp_ to "release" a "vastly improved and thoroughly corrected miner"

[BitBustah]

got this miner compiled in ubuntu 16.04 hitting 5600Khs on VXS is this good for a 1080ti?
i dont overclock everything is standard apart from fan speed

I'm on Windows 10, so I can't say for sure in regards to linux, but I think you're speed is about right. I get 5200-5400 for Xevan per GTX 1080 Ti, depending on the overclock, at 80% power limit. I've seen reports of people being close to 6000, but I think that is both Overclocked and at full power limit.

Been mining Xevan for a few weeks now. Using Windows 10.
- Asus STRIX 1080 Ti: 5818.11
- MSI 1080 Gaming Plus (11 Gbps): 4078.85

Little bit clocked.

[stevascha]

doing good, my aorus extreme get 6mhs, thanks alot!!

[BitBustah]

doing good, my aorus extreme get 6mhs, thanks alot!!

Wow. 1080 ti or just 1080?

[oktoshiimin]

need some help here, i got this error

Code:

In file included from bignum.cpp:8:0:
bignum.hpp:63:24: error: invalid use of incomplete type ‘BIGNUM {aka struct bignum_st}’
 class CBigNum : public BIGNUM
                        ^
In file included from /usr/local/include/openssl/bn.h:32:0,
                 from bignum.hpp:20,
                 from bignum.cpp:8:
/usr/local/include/openssl/ossl_typ.h:80:16: note: forward declaration of ‘BIGNUM {aka struct bignum_st}’
 typedef struct bignum_st BIGNUM;
                ^
In file included from bignum.cpp:8:0:
bignum.hpp: In constructor ‘CBigNum::CBigNum()’:
bignum.hpp:68:21: error: ‘BN_init’ was not declared in this scope
         BN_init(this);
                     ^
bignum.hpp: In copy constructor ‘CBigNum::CBigNum(const CBigNum&)’:
bignum.hpp:73:21: error: ‘BN_init’ was not declared in this scope
         BN_init(this);
                     ^
bignum.hpp:74:30: error: cannot convert ‘CBigNum*’ to ‘BIGNUM* {aka bignum_st*}’ for argument ‘1’ to ‘BIGNUM* BN_copy(BIGNUM*, const BIGNUM*)’

when try to compiling build.sh in ubuntu, can some one guide me to fix it?

[sp_]

Look at the dates and wait for sp_ to "release" a "vastly improved and thoroughly corrected miner"

I have already made a faster private xevan miner. A rewrite of groestl and simd gave a 10% speedup. I don't want to give it away cheap. (0.05btc). Some of you have disassembled my code and see that I use a new shuffle instruction.

[Vispilio]

is it now better to mine with this new improved miner on a 1080 ti compared to mining ZCASH with it, what is the cash value of 6mh mining power / month / card ?..

What is Xevan mining, only Solaris ?..

[Elder III]

is it now better to mine with this new improved miner on a 1080 ti compared to mining ZCASH with it, what is the cash value of 6mh mining power / month / card ?..

What is Xevan mining, only Solaris ?..

Solaris, Amsterdam, Vsync, and Bitsend (the original Xevan coin).... there are at least a couple of others that I can't think of at the moment. It's been a popular coin this autumn, with those 3 coins all either starting new with Xevan, or forking from a different algorithm to Xevan.

[henrynguyen]

My asus rog stix 1080TI is about 5mh/s.
Who can hepl me overlooking MSI?

Xevan use core lock or memory ?
Now, I set : core +200 mem +100

Sr I'm bad in English

[stevascha]

doing good, my aorus extreme get 6mhs, thanks alot!!

Wow. 1080 ti or just 1080?

1080ti man

any benchmark & setup intensity for gtx 1060 3gb?

[ShowMeCoins]

doing good, my aorus extreme get 6mhs, thanks alot!!

Wow. 1080 ti or just 1080?

1080ti man

any benchmark & setup intensity for gtx 1060 3gb?

take your pick https://altminer.net/bench?algo=xevan&chip=6
Any other yiimp pool will do

[Vispilio]

doing good, my aorus extreme get 6mhs, thanks alot!!

whoa isn't 6mhs extreme bro ? what a powerful miner this is, how much cash is being generated with this miner on a 1080 ti ?.. Be kind enough to tell me the coin you've mined over the course of last month with x amount of 1080ti's and how much it's worth now... Thanks in advance.

[Helios45]

I'm mining a Xevan coin using this miner and I'm getting more than 2% rejected shares in the last 24 hours, any idea what can be causing this?

[Elder III]

I'm mining a Xevan coin using this miner and I'm getting more than 2% rejected shares in the last 24 hours, any idea what can be causing this?

Well my first thought is that perhaps you have your overclock too high, or you need to lower your intensity in the miner.  Also, have you tried a different pool to see if the reject rate is the same?

[Helios45]

I'm mining a Xevan coin using this miner and I'm getting more than 2% rejected shares in the last 24 hours, any idea what can be causing this?

Well my first thought is that perhaps you have your overclock too high, or you need to lower your intensity in the miner.  Also, have you tried a different pool to see if the reject rate is the same?

Thanks for the tips, I will try lowering my OC settings, if it doesn't help I'll give the intensity a try

[Bluecheese]

Hey thanks for the support of Xevan for nvidia.  I'm glad I waited to try this out.

[NetopyrMan]

wierd ...

- mixed rig 4x1070 + 1x1080ti makes 3,3MH/per 1070 -i 20 and +-5,5MH on 1080ti -i 19 (ok)
- rig with 5x1070ti makes 3950kH per card, -i 19 (ok)

- BUT rig with 6x1070ti ... 5 cards makes 3850Kh and 1 makes 3730 .... lower OC clocks vs 5gpu rig due to illegal memory access OR illegal instruction, -i used def or 16-22 ...
and to make it stable i must make 4 threads: 1x3gpu(-i default) and 3x1gpu(2x -i default, 1x -i 18) ... at least it has a positive impact on swap ... takes only 10g instead of 30g

edited: and pool shows 5-10% lower hashrate in total then should be (bsod.pw)

[RogerSally]

I think he mean separate instances and miners 

[stas260385]

Hi all! This is prealpha version of my xevan miner. Tested only on linux, cuda 7.5 and 1070 & 1080ti.

https://github.com/krnlx/ccminer-xevan

Donations are welcome.


UPD. For 1060 cards intensity sets up incorrectly - you must adjust it with -i param. -i 20 is best for 1070, 1080ti

UPD2. Windows version by Palgin

x86_64
https://mega.nz/#!NhhnGahJ!dGC_LNOi_a98BuHSuLZQB7k-YT-dM7I_We_svn1hCc0
x86
https://mega.nz/#!98xj3RyD!tfWT6yKHb7gQhzJMi0YYx7wwIX75wppE3Hw7grcMR-4

When you planing to update your miner?

[BitBustah]

"GPU#0:ASUS GTX 1080 Ti, 6218.11kH/s"

[Jimm3h]

Hi all! This is prealpha version of my xevan miner. Tested only on linux, cuda 7.5 and 1070 & 1080ti.

https://github.com/krnlx/ccminer-xevan

Donations are welcome.


UPD. For 1060 cards intensity sets up incorrectly - you must adjust it with -i param. -i 20 is best for 1070, 1080ti

UPD2. Windows version by Palgin

x86_64
https://mega.nz/#!NhhnGahJ!dGC_LNOi_a98BuHSuLZQB7k-YT-dM7I_We_svn1hCc0
x86
https://mega.nz/#!98xj3RyD!tfWT6yKHb7gQhzJMi0YYx7wwIX75wppE3Hw7grcMR-4

When you planing to update your miner?

Would also love to see an update to this project.

[Mr.Spider703]

updates will most likely not be, the maximum is already squeezed out, according to Palgin

[sp_]

updates will most likely not be, the maximum is already squeezed out, according to Palgin

Palgin is wrong. I have a mod that does +10% Simd/groestl rewrite

[Mr.Spider703]

updates will most likely not be, the maximum is already squeezed out, according to Palgin

Palgin is wrong. I have a mod that does +10% Simd/groestl rewrite

maybe there is only someone trying to sell it for 0.05 btc in difference from the version of Palgin and Krnlx

[sp_]

maybe there is only someone trying to sell it for 0.05 btc in difference from the version of Palgin and Krnlx

0.05? No. more than 1 bitcoin. +++

Palgin is not doing any opensource anymore. Check out his slow Neoscrypt/hsr miner with opensource violation and a fee.

[Mr.Spider703]

maybe there is only someone trying to sell it for 0.05 btc in difference from the version of Palgin and Krnlx

0.05? No. more than 1 bitcoin. +++

Palgin is not doing any opensource anymore. Check out his slow Neoscrypt/hsr miner with opensource violation and a fee.

probably because it is not based on opensource, and by the way I knew about the creation of this miner and began to test it before the release for users, yes there is a dev free, but he does not ask users to pay 0.05 btc, for some it's their income for half a year, but the SP_ branch of which I often read many are accused of breaking opensource

[crocozino]

maybe there is only someone trying to sell it for 0.05 btc in difference from the version of Palgin and Krnlx

0.05? No. more than 1 bitcoin. +++

Palgin is not doing any opensource anymore. Check out his slow Neoscrypt/hsr miner with opensource violation and a fee.

SP come on, there is no other miner avail to everyone which is can push more the 1800kh/s from gtx1080ti
all other version are slower then that, and nobody will even consider your version for 1 btc or something like that
cause it is better just leave btc and use free fast miner and gets more profit, then spend 1btc on your miner and get 5% more speed

[d0n4ald]

what core clock and mem settings for 1080ti and 1070ti using this krnlx ccminer for xevan algo?

[d0n4ald]

I guess this krnlx ccminer no longer being updated.
But still works for xevan
2 1080ti and 1 1070ti getting about 14.2 mh
However I don't see what each individual card is doing
Does my hash rate sound good?

[Helios45]

I guess this krnlx ccminer no longer being updated.
But still works for xevan
2 1080ti and 1 1070ti getting about 14.2 mh
However I don't see what each individual card is doing
Does my hash rate sound good?

I get 11mh with three 1070 TI's running at 60% TDP

[d0n4ald]

I guess this krnlx ccminer no longer being updated.
But still works for xevan
2 1080ti and 1 1070ti getting about 14.2 mh
However I don't see what each individual card is doing
Does my hash rate sound good?

I get 11mh with three 1070 TI's running at 60% TDP

Seems like I'm getting low hashrate then

I'm at 80% tdp. +135+700

[Helios45]

I guess this krnlx ccminer no longer being updated.
But still works for xevan
2 1080ti and 1 1070ti getting about 14.2 mh
However I don't see what each individual card is doing
Does my hash rate sound good?

I get 11mh with three 1070 TI's running at 60% TDP

Seems like I'm getting low hashrate then

I'm at 80% tdp. +135+700

Try higher core, I run mine at +200 and less memory

[sean808080]

My 2 rigs were running this miner just fine until I added a new card to fill out the second rig. 

Now only this rig is consistently crashing with the error:

Cuda error in func 'quark_blake512_cpu_setBlock_80' at line 701 : unspecified launch failure.                         

I've tried removing OC, lower intensity and have had no luck.  Both rigs are now at 6 cards mixing 1070TIs and 1070s.

Any ideas?

Thx!

[tritonchev89]

can anybody share a Afterburner optimal overcloking setings  for card Gigabyte GeForce GTX 1060 Windforce OC 6GB GDDR5 with hynix memory

[Mr.Spider703]

can anybody share a Afterburner optimal overcloking setings  for card Gigabyte GeForce GTX 1060 Windforce OC 6GB GDDR5 with hynix memory

PL 75-80 mem 550-600 core 150
try this

[DeadAbrasiveness]

Surprised not to see a virustotal result shared here for this miner.

Scores 23/66: https://www.virustotal.com/#/file/f8b2120127c88ec8d91f59305e6f1c5c18b2c614b0e68643701849a01874ff1d/detection

[NameTaken]

Surprised not to see a virustotal result shared here for this miner.

Scores 23/66: https://www.virustotal.com/#/file/f8b2120127c88ec8d91f59305e6f1c5c18b2c614b0e68643701849a01874ff1d/detection

You can view source code on Github and compile it yourself.

[d0n4ald]

Surprised not to see a virustotal result shared here for this miner.

Scores 23/66: https://www.virustotal.com/#/file/f8b2120127c88ec8d91f59305e6f1c5c18b2c614b0e68643701849a01874ff1d/detection

This miner has viruses? What does the virus do?

[fanon]

Surprised not to see a virustotal result shared here for this miner.

Scores 23/66: https://www.virustotal.com/#/file/f8b2120127c88ec8d91f59305e6f1c5c18b2c614b0e68643701849a01874ff1d/detection

This miner has viruses? What does the virus do?

Every miner is flagged as a virus. You can thank malware authors for using mining software in their malware.

[Asgeirsk]

New coin, Ellerium coming tonight. Cant wait to try out this miner

[thecoder2012]

New coin, Ellerium coming tonight. Cant wait to try out this miner

Yes. You can use urals coin as pre-test for xevan.

[ManuBBXX]

I only get 5.2 mh/s per 1080ti

Is there a better miner released ?

[buddy123]

I havent been able to compile it for ubuntu 16.04.
I have 1080TI and cuda 9.1 installed, with nvidia-390 drivers.

I get an error:

Code:

ccminer.cpp:45:26: fatal error: cuda_runtime.h: No such file or directory

I know that other miners, like ccminer, requires editing the nvcc version and keeping only sm_61 for my graphics card, but in Makefile.am its not even listed.
I tried to add manually, but stumble to the same error.

Anyone have a clue about that?

[95dram]

I havent been able to compile it for ubuntu 16.04.
I have 1080TI and cuda 9.1 installed, with nvidia-390 drivers.

I get an error:

Code:

ccminer.cpp:45:26: fatal error: cuda_runtime.h: No such file or directory

I know that other miners, like ccminer, requires editing the nvcc version and keeping only sm_61 for my graphics card, but in Makefile.am its not even listed.
I tried to add manually, but stumble to the same error.

Anyone have a clue about that?

I had the same problem. after hours of banging my head off the wall I found the configure.sh file was looking for cuda 7.5. I just changed it to my current version and bingo off to the races

[Rc-BtcZmining]

My 2 rigs were running this miner just fine until I added a new card to fill out the second rig. 

Now only this rig is consistently crashing with the error:

Cuda error in func 'quark_blake512_cpu_setBlock_80' at line 701 : unspecified launch failure.                         

I've tried removing OC, lower intensity and have had no luck.  Both rigs are now at 6 cards mixing 1070TIs and 1070s.

Any ideas?

Thx!

Hi Friend ,

I also have the same problem , my rig has 8 cards 1070ti and the miner is krnlx/ccminer-xevan but in the last three days i have the same error,,
Have you could to solve this trouble?
Thanks if you could share something with me.
 

[lir3000]

Hi all!
Ubuntu 16.04 LTS, Cuda 8.0, Nvidia Xserver (prefer high performance), 5 x 1060 3Gb Gigabyte
ccMiner today biuld from Github. readme.txt: release 1.7.1 (Jan 2015) "Sibcoin & Whirlpool midstate"

sudo ./ccminer -a xevan -o stratum+tcp://stratum.gos.cx:3738 -u xxx -p c=XHM
2018-02-27 13:16:01] GPU#0:NONCE FOUND
[2018-02-27 13:16:01] GPU#1:target 0 ffc00000 3f
[2018-02-27 13:16:01] GPU#1:target 3fffc00000
[2018-02-27 13:16:01] [S/A/T]: 0/304/304, diff: 0.036, 9832.42kH/s yes!
[2018-02-27 13:16:08] GPU#0:NONCE FOUND
[2018-02-27 13:16:08] GPU#2:GeForce GTX 1060 3GB, 1981.43kH/s
[2018-02-27 13:16:08] GPU#2:target 0 ffc00000 3f
[2018-02-27 13:16:08] GPU#2:target 3fffc00000
[2018-02-27 13:16:08] [S/A/T]: 0/305/305, diff: 0.018, 9831.88kH/s yes!
[2018-02-27 13:16:10] GPU#0:NONCE FOUND
[2018-02-27 13:16:10] GPU#0:target 0 ffc00000 3f
[2018-02-27 13:16:10] GPU#0:target 3fffc00000
[2018-02-27 13:16:10] [S/A/T]: 0/306/306, diff: 0.025, 9831.53kH/s yes!
[2018-02-27 13:16:11] GPU#0:NONCE FOUND
[2018-02-27 13:16:11] GPU#4:GeForce GTX 1060 3GB, 1964.88kH/s
[2018-02-27 13:16:11] GPU#4:target 0 ffc00000 3f
[2018-02-27 13:16:11] GPU#4:target 3fffc00000
[2018-02-27 13:16:11] [S/A/T]: 0/307/307, diff: 0.293, 9831.06kH/s yes!

What does it mean GPU#0:NONCE FOUND? (marked in red) Does it even work (gpu 0)?

WBR.

[NetopyrMan]

What does it mean GPU#0:NONCE FOUND? (marked in red) Does it even work (gpu 0)?

dont worry ... its same like block found

[KriptoFull]

Tell me, how can I download the miner haven for Windows!The link from the main page does not work?

[crocozino]

I guess this krnlx ccminer no longer being updated.
But still works for xevan
2 1080ti and 1 1070ti getting about 14.2 mh
However I don't see what each individual card is doing
Does my hash rate sound good?

yes, it is a pity this great miner stopped to be updated, I hope there could be some more improvements to be achieved
maybe tpruvot could look further into in and get it done? dont't no..
but still this is the best miner we have for xevan for nv cards...

[extravizor]

hello guys
i try use
--quiet and some another
--plimit=
--tlimit=85
--max-temp=
not work miner just not accept this command...

command worked well
--no-color        disable colored output

just very need --quiet  and --tlimit or --max-temp
today freezee afterbernet and temp go to 80C.. in another miner Ccminer on another algo no this problem

[Zheko87]

What intensivety better for p106-100 and 1066?

[barista1992]

Hey, guys!

Are you planned to make compiler for Ubuntu?

Thanks!

[Kelsier]

anyone have the problem where the miner closes after a few minutes - every time? I'm not entirely sure what the error or if there even is one displayed because the command prompt disappears too quickly.

I do have some slight overclock on my gpus but most other algos with various other miners seem to mine fine. Was just wondering if anyone else had this problem and figured out what was going on.

[criptooo]

güzel miner ++++

[Shelltux]

I created an pull request because the xevan-ccminer does not compile with OpenSSL >= 1.1.0.
https://github.com/krnlx/ccminer-xevan/pull/11

[Shelltux]

anyone have the problem where the miner closes after a few minutes - every time? I'm not entirely sure what the error or if there even is one displayed because the command prompt disappears too quickly.

I do have some slight overclock on my gpus but most other algos with various other miners seem to mine fine. Was just wondering if anyone else had this problem and figured out what was going on.

How do yo start the miner? Are you using Windows or Linux? I would guess Windows .
Can you put in the script you are using to start the miner?

[Shelltux]

I more or less randomly faced the following error:

Code:

Cuda error in func 'quark_blake512_cpu_setBlock_80' at line 701 : unspecified launch failure.

After some Google'ing there are some people stating that this has something todo with over or underclocking the GPU's.
My 1080Rig is overclocked so I build myself the following systemd file to enable the watchdog function which in case restarts the xevan-ccminer:

Code:

[Unit]
Description=CCMiner
After=syslog.target network.target
StartLimitBurst=10
StartLimitIntervalSec=120

[Service]
Type=simple
ExecStart=/usr/bin/screen -S ccminer -L -Logfile /home/miner/ccminer.log -Dm /home/miner/ccminer-xevan/ccminer -a xevan -o [STRATUM_URL] -u [USERNAME] -p x --api-remote -q --no-color --api-bind=192.168.178.10:4068
ExecStop=/usr/bin/killall ccminer
User=miner
Restart=always
RestartSec=3

[Install]
WantedBy=multi-user.target

This can possibly help someone ...

[livewacn5785]

Can someone share ccmner/krnlx-enemy.mod01? Please private message to me

[stas260385]

Hi all! This is prealpha version of my xevan miner. Tested only on linux, cuda 7.5 and 1070 & 1080ti.

https://github.com/krnlx/ccminer-xevan

Donations are welcome.


UPD. For 1060 cards intensity sets up incorrectly - you must adjust it with -i param. -i 20 is best for 1070, 1080ti

UPD2. Windows version by Palgin

x86_64
https://mega.nz/#!NhhnGahJ!dGC_LNOi_a98BuHSuLZQB7k-YT-dM7I_We_svn1hCc0
x86
https://mega.nz/#!98xj3RyD!tfWT6yKHb7gQhzJMi0YYx7wwIX75wppE3Hw7grcMR-4

Hey, krnlx!
Any chance to rewrite/improve performance Xevan algo?

[ganzocrypt]

My 2 rigs were running this miner just fine until I added a new card to fill out the second rig. 

Now only this rig is consistently crashing with the error:

Cuda error in func 'quark_blake512_cpu_setBlock_80' at line 701 : unspecified launch failure.                         

I've tried removing OC, lower intensity and have had no luck.  Both rigs are now at 6 cards mixing 1070TIs and 1070s.

Any ideas?

Thx!

Hi Friend ,

I also have the same problem , my rig has 8 cards 1070ti and the miner is krnlx/ccminer-xevan but in the last three days i have the same error,,
Have you could to solve this trouble?
Thanks if you could share something with me.
 

same issue with 1070TI freezing PC, fan 100%
Any suggestions?

[ruplikminer]

Can someone share ccmner/krnlx-enemy.mod01? Please private message to me

yes please...anyone have the ccminer/krnlx-enemy.mod01  miner?

[paulus59]

hello there,


if you have problems like :  "Cuda error in func 'quark_blake512_cpu_setBlock_80' at line 701 : unspecified launch failure"

the problem is your intensity is set to high , lower intensity then try again , it will work i am playing with this miner on a MSI GTX 750 2 GB and get with algo xevan : 548.60 KH/s !
not bad for an GTX 750 2GB and its not the i version


[edit]

this error "Cuda error in func 'quark_blake512_cpu_setBlock_80' at line 701 : unspecified launch failure , has to do with your memory allocation clock on your GPU/CPU

Question >: can some one ex plain what this means in the miner > :  [S/A/T]: 0/246/246, diff: