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Author Topic: Krnlx Nvidia xevan miner - 3.3+ mh on 1070, ~6mh on 80ti FREE, OPENSOURCE  (Read 21402 times)
krnlx
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October 05, 2017, 12:04:48 AM
 #1

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

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October 05, 2017, 01:58:49 AM
 #2

awesome, I'm compiling it, is there a recommend pool?
krnlx
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October 05, 2017, 02:03:47 AM
 #3

I tested on yiimp and suprnova

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October 05, 2017, 02:22:56 AM
 #4

it works fine with cuda8, ubuntu16,suprnova, gtx1080ti get  5.6m @core clock+100, 200watts.
I'll install cuda7.5.
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October 05, 2017, 02:28:23 AM
 #5

Can someone share windows cuda 7.5 x32 biraries please?
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October 05, 2017, 02:41:23 AM
 #6

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
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October 05, 2017, 02:43:56 AM
 #7

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

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FortuneNVirtue
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October 05, 2017, 02:46:23 AM
 #8

Thank you so much.
I'll try it.  Cheesy
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October 05, 2017, 03:49:32 AM
 #9

Are you planning to bring one for windows?
krnlx
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October 05, 2017, 03:59:18 AM
 #10

Are you planning to bring one for windows?

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

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October 05, 2017, 05:04:25 AM
 #11

Any Win build please!
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October 05, 2017, 05:25:52 AM
 #12

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
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October 05, 2017, 05:32:51 AM
 #13

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.

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October 05, 2017, 05:49:13 AM
 #14

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?
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October 05, 2017, 06:06:15 AM
 #15

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
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October 05, 2017, 06:15:03 AM
 #16

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.

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krnlx
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October 05, 2017, 06:16:07 AM
 #17

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

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palgin
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October 05, 2017, 06:44:15 AM
 #18

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

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.

BTC tips welcome: 15rc7ZpVXvSiDhKkpWf4agV65Cfw3uCk
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October 05, 2017, 06:45:54 AM
 #19

Im happy to do donation but no Win buld to test here Sad
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October 05, 2017, 07:03:58 AM
 #20

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

I am building now.
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October 05, 2017, 07:18:12 AM
 #21

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.
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October 05, 2017, 07:28:59 AM
 #22

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
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October 05, 2017, 07:35:10 AM
 #23

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  Sad What changes did you made to source code ?

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October 05, 2017, 07:37:27 AM
 #24

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?
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October 05, 2017, 07:48:38 AM
 #25

a win binary would be highly appreciated
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October 05, 2017, 08:16:58 AM
 #26

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.
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October 05, 2017, 08:19:09 AM
 #27

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.

GTX 1080Ti rocks da house... seriously... this card is a beast³
Owning by now 18x GTX1080Ti :-D @serious love of efficiency
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October 05, 2017, 08:25:20 AM
 #28

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  Sad 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.
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October 05, 2017, 08:28:24 AM
 #29

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 Smiley

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October 05, 2017, 08:31:05 AM
 #30

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

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October 05, 2017, 08:36:35 AM
 #31

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  Sad 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
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October 05, 2017, 08:39:12 AM
 #32

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.

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October 05, 2017, 08:41:33 AM
 #33

we need windows build... устал ждать))
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October 05, 2017, 08:42:47 AM
 #34

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  Sad 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 ...

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October 05, 2017, 08:45:32 AM
 #35

I have a windows build. But Xevan is not profitable. any more.
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October 05, 2017, 08:45:42 AM
 #36

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.

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October 05, 2017, 08:48:12 AM
 #37

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
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October 05, 2017, 08:49:18 AM
 #38

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?
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October 05, 2017, 08:50:56 AM
 #39

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  Sad 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)
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October 05, 2017, 08:53:24 AM
 #40

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

please send me this build Wink
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October 05, 2017, 08:54:19 AM
 #41

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 Smiley

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 ;(

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October 05, 2017, 08:54:37 AM
 #42

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
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October 05, 2017, 08:56:14 AM
 #43

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)

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October 05, 2017, 09:01:57 AM
 #44

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
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October 05, 2017, 09:02:27 AM
 #45

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
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October 05, 2017, 09:09:29 AM
 #46

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.
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October 05, 2017, 09:13:43 AM
 #47

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

GTX 1080Ti rocks da house... seriously... this card is a beast³
Owning by now 18x GTX1080Ti :-D @serious love of efficiency
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October 05, 2017, 09:29:31 AM
 #48

A compiled Windows binary would be greatly appreciated.

Cryptum.co - The First Crypto Mining Board Game
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October 05, 2017, 09:32:17 AM
 #49

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 Smiley

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

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October 05, 2017, 10:55:23 AM
 #50

Any news about win build?
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October 05, 2017, 11:02:58 AM
 #51

Awesome!

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

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October 05, 2017, 11:13:49 AM
 #52

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. Wink

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October 05, 2017, 11:53:25 AM
 #53

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. Wink

Quote
sozdatelya

 Cheesy Cheesy Cheesy  good

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

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October 05, 2017, 11:58:40 AM
 #54

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

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October 05, 2017, 12:29:58 PM
 #55

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
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October 05, 2017, 12:38:15 PM
 #56

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  Cry

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 Grin Grin Grin

BTC tips welcome: 15rc7ZpVXvSiDhKkpWf4agV65Cfw3uCk
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October 05, 2017, 02:57:39 PM
 #57

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?
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October 05, 2017, 03:10:33 PM
 #58

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


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October 05, 2017, 03:19:34 PM
 #59

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
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October 05, 2017, 03:21:53 PM
 #60

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!

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zer0k
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October 05, 2017, 03:35:30 PM
 #61

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
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October 05, 2017, 03:42:47 PM
 #62

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
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October 05, 2017, 03:50:07 PM
 #63


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  Wink

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).

BTC tips welcome: 15rc7ZpVXvSiDhKkpWf4agV65Cfw3uCk
stas260385
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October 05, 2017, 03:53:14 PM
 #64


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  Wink

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
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October 05, 2017, 03:56:55 PM
 #65

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.

BTC tips welcome: 15rc7ZpVXvSiDhKkpWf4agV65Cfw3uCk
anorganix
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October 05, 2017, 04:13:53 PM
 #66

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.


There are only 10 types of people in the world: those who understand binary, and those who don't.
stas260385
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October 05, 2017, 04:20:36 PM
 #67

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
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October 05, 2017, 04:22:50 PM
 #68

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

->Altcoin Mining< @ Xubuntu 16.04LTS
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October 05, 2017, 04:22:59 PM
 #69

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.

There are only 10 types of people in the world: those who understand binary, and those who don't.
palgin
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October 05, 2017, 04:27:12 PM
 #70

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  Grin

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

BTC tips welcome: 15rc7ZpVXvSiDhKkpWf4agV65Cfw3uCk
integrale
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October 05, 2017, 04:30:26 PM
 #71

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

->Altcoin Mining< @ Xubuntu 16.04LTS
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October 05, 2017, 04:30:42 PM
 #72

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
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October 05, 2017, 04:36:25 PM
 #73

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

this is results of output, replacing x17.cu and recompile with one posted palgin.
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October 05, 2017, 04:37:47 PM
 #74

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

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


Thank you, will check it!


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October 05, 2017, 04:39:29 PM
 #75

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;
}

->Altcoin Mining< @ Xubuntu 16.04LTS
sickofscamcoins
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October 05, 2017, 04:42:56 PM
 #76

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
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October 05, 2017, 04:51:19 PM
 #77

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.

BTC tips welcome: 15rc7ZpVXvSiDhKkpWf4agV65Cfw3uCk
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October 05, 2017, 04:58:52 PM
 #78

welp i tried for my cookie anyways.  Anything else I can do to help lmk
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October 05, 2017, 05:57:04 PM
 #79

Any binaries?
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October 05, 2017, 05:59:06 PM
 #80

Any binaries?

Yes, we have 0 and 1.

There are only 10 types of people in the world: those who understand binary, and those who don't.
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October 05, 2017, 06:01:08 PM
 #81

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?

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October 05, 2017, 06:18:19 PM
 #82

Any binaries?

Yes, we have 0 and 1.

Hahah, nice one
sickofscamcoins
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October 05, 2017, 06:23:26 PM
 #83

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


http://paste.ubuntu.com/25681179/
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October 05, 2017, 06:26:33 PM
 #84

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  Grin

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October 05, 2017, 06:43:59 PM
 #85

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


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October 05, 2017, 06:58:22 PM
 #86

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
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October 05, 2017, 07:06:29 PM
 #87

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 ?
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October 05, 2017, 07:32:06 PM
 #88

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) ?

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October 05, 2017, 08:07:08 PM
 #89

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

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October 05, 2017, 08:25:41 PM
 #90

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.
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October 05, 2017, 08:28:15 PM
 #91

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?
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October 05, 2017, 08:30:07 PM
 #92

Dear sp_,

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

There are only 10 types of people in the world: those who understand binary, and those who don't.
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October 05, 2017, 08:32:22 PM
 #93

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  Grin Grin Grin Grin

It's just fun, debugging always train your skills  Wink

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October 05, 2017, 08:32:31 PM
 #94

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..
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October 05, 2017, 08:43:28 PM
 #95

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

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October 05, 2017, 09:38:22 PM
 #96

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.

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October 05, 2017, 09:47:18 PM
 #97

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.
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October 05, 2017, 09:49:19 PM
 #98

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.

- Huh WindowsWalletDev Huh
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October 05, 2017, 09:59:05 PM
 #99

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.
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October 05, 2017, 10:08:02 PM
 #100

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?
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October 05, 2017, 10:09:34 PM
 #101

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?
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October 05, 2017, 10:10:39 PM
 #102

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
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October 05, 2017, 10:12:40 PM
 #103

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

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October 05, 2017, 10:14:32 PM
 #104

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.  

 Huh WindowsWalletDev  Huh

p.s. sp_ when exactly did you realize you liked men
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October 05, 2017, 10:35:20 PM
 #105

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.

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October 05, 2017, 11:05:56 PM
 #106

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.
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October 05, 2017, 11:39:34 PM
 #107


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


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October 06, 2017, 01:36:31 AM
 #108

Thank

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October 06, 2017, 01:44:00 AM
 #109

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!

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October 06, 2017, 05:04:09 AM
 #110

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
    },

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October 06, 2017, 05:23:43 AM
 #111

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 ?

The best way to make your firsts free bitcoins/satoshis (la façon la plus simple d'obtenir gratuitement vos premiers bitcoins/satoshis) : Moon Bitcoin (topic in english ou en français)
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October 06, 2017, 05:25:51 AM
 #112

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...

The best way to make your firsts free bitcoins/satoshis (la façon la plus simple d'obtenir gratuitement vos premiers bitcoins/satoshis) : Moon Bitcoin (topic in english ou en français)
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October 06, 2017, 05:28:17 AM
 #113

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?
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October 06, 2017, 05:33:45 AM
 #114

no windows build yet?
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October 06, 2017, 05:39:08 AM
 #115

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 ?

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October 06, 2017, 05:56:44 AM
 #116

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  Cheesy
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.

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October 06, 2017, 07:06:25 AM
 #117

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 Cheesy
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October 06, 2017, 07:08:30 AM
 #118

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  Cheesy
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!

There are only 10 types of people in the world: those who understand binary, and those who don't.
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October 06, 2017, 07:16:51 AM
 #119

Great news, thanks for the effort!

Another error showed up, so keep digging code Huh

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October 06, 2017, 07:38:41 AM
 #120

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

The best way to make your firsts free bitcoins/satoshis (la façon la plus simple d'obtenir gratuitement vos premiers bitcoins/satoshis) : Moon Bitcoin (topic in english ou en français)
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October 06, 2017, 08:27:04 AM
 #121

Nice to know finally xevan algo for nvidia. I will compile it in linux and waiting to try out mining the new solaris soon.
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October 06, 2017, 09:07:28 AM
 #122

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  Cheesy
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.
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October 06, 2017, 09:34:59 AM
 #123

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.

The best way to make your firsts free bitcoins/satoshis (la façon la plus simple d'obtenir gratuitement vos premiers bitcoins/satoshis) : Moon Bitcoin (topic in english ou en français)
The easiest and speedest way to begin to mine (la façon la plus simple et la plus rapide pour commencer à miner) : Minergate
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October 06, 2017, 09:44:00 AM
 #124

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

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.

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October 06, 2017, 10:01:21 AM
 #125

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

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
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October 06, 2017, 10:26:15 AM
 #126

Github updated with Windows binaries. Thanks Palgin!

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October 06, 2017, 10:49:05 AM
 #127

Great news.
Are you peeps mining bitsend or solaris?
anorganix
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October 06, 2017, 10:52:57 AM
 #128

Works like a charm!
Thanks!

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October 06, 2017, 10:58:26 AM
 #129

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

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October 06, 2017, 11:00:50 AM
 #130

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.
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October 06, 2017, 11:04:59 AM
 #131

Big thanx krnlx and palgin.
Just built cuda7.5x64 version and it seems to be 5% faster then palgin's cuda8x64 build.

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October 06, 2017, 11:08:56 AM
 #132

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  Wink

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October 06, 2017, 11:19:04 AM
 #133

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  Wink
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?

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October 06, 2017, 11:22:07 AM
 #134

25Mh - 8 1070 x64 version

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October 06, 2017, 11:23:01 AM
 #135

25Mh - 8 1070 x64 version

Which core/mem settings do you use?
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October 06, 2017, 11:29:04 AM
 #136

25Mh - 8 1070 x64 version

Which core/mem settings do you use?

1860/4400  temp 69~72

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October 06, 2017, 11:33:01 AM
 #137


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.

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October 06, 2017, 11:33:26 AM
 #138

32mh 6x 1080ti Aorus +100 core, +300 mem, power limit 75%
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October 06, 2017, 11:50:00 AM
 #139

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?
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October 06, 2017, 11:56:42 AM
 #140

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)
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October 06, 2017, 11:57:01 AM
 #141

Is there any way to get a bulited, runable version on Win 10 x64?

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October 06, 2017, 11:57:12 AM
 #142

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  Wink

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October 06, 2017, 11:59:29 AM
 #143

Is there any way to get a bulited, runable version on Win 10 x64?

Chech krnlx github, Releases section

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October 06, 2017, 12:19:10 PM
 #144

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

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October 06, 2017, 12:45:19 PM
 #145

Krnlx,
Under CUDA8.0 difficult to adapt?

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October 06, 2017, 01:08:36 PM
 #146

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.

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October 06, 2017, 01:09:11 PM
 #147

Thanks for the miner!

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October 06, 2017, 01:27:23 PM
 #148

Anyone to give GTX 1060 6 Gb hashrate ?

Thanks.
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October 06, 2017, 01:42:06 PM
 #149

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.

The best way to make your firsts free bitcoins/satoshis (la façon la plus simple d'obtenir gratuitement vos premiers bitcoins/satoshis) : Moon Bitcoin (topic in english ou en français)
The easiest and speedest way to begin to mine (la façon la plus simple et la plus rapide pour commencer à miner) : Minergate
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October 06, 2017, 01:51:50 PM
 #150

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.

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October 06, 2017, 01:53:14 PM
 #151

Thanks.
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October 06, 2017, 01:59:41 PM
 #152

krnlx, great work!  Cool thank you.
I will try your miner soon. regardless of profitability it will be good addition to miners family. Keep going!
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October 06, 2017, 02:39:54 PM
 #153

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?
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October 06, 2017, 02:42:04 PM
 #154

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 Cheesy
but great miner anyway
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October 06, 2017, 03:10:52 PM
 #155

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 :-/

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October 06, 2017, 03:15:50 PM
 #156

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.

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October 06, 2017, 03:19:46 PM
 #157

ccminer_x86 looks faster
1060 6Gb ~2500
1070 ~3500
1080 ~4350
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October 06, 2017, 03:20:10 PM
 #158

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.
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October 06, 2017, 03:22:16 PM
 #159

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?

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October 06, 2017, 03:27:02 PM
 #160

Finally miner for xevan, great job guys. Thank you for the hard work!

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October 06, 2017, 03:28:32 PM
 #161

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.
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October 06, 2017, 03:52:24 PM
 #162

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

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October 06, 2017, 04:36:27 PM
 #163

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.
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October 06, 2017, 05:35:20 PM
 #164

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)
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October 06, 2017, 05:46:38 PM
 #165

Good job!!! Thx

1060 tdp 70 core +150 mem -500

13,66 6x1060 6gb -i 21

latest driver, x86 cuda 9 build, w10
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October 06, 2017, 05:49:44 PM
 #166

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.

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October 06, 2017, 05:53:57 PM
 #167

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.
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October 06, 2017, 05:56:07 PM
 #168

Maximum result that I could get,  seems very profitable  Smiley

GPU#0:MSI GTX 1060 3GB, 2178.23kH/s

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October 06, 2017, 05:56:19 PM
 #169

CUDA 9.0 x86 - 8x1070 28Mh

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October 06, 2017, 06:01:08 PM
 #170

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???
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October 06, 2017, 06:02:31 PM
 #171

Gigabyte GTX 1080 Ti, 5243.33kH/s
Gigabyte GTX 1080, 3855.18kH/s

cuda 9 build x86

tdp 65 -i 21
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October 06, 2017, 06:22:16 PM
 #172

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
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October 06, 2017, 08:01:23 PM
 #173

Maximum result that I could get,  seems very profitable  Smiley

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 )))
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October 06, 2017, 08:19:46 PM
 #174

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.
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October 06, 2017, 08:29:03 PM
 #175

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?
Quote
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.

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October 06, 2017, 08:37:17 PM
 #176

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
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Activity: 106

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October 06, 2017, 08:40:12 PM
 #177

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

->Altcoin Mining< @ Xubuntu 16.04LTS
blackhorse7
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October 06, 2017, 08:47:34 PM
 #178

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