-snip-
could you try this for calc time about your 24 2080ti gpu for 100 bit
0314AA23C847D86CE1FCDC4B3E0524F741FDE2AC4B38B522ED2E3B77CF500D5718
and you can use client server or single system with gpuid 0,1,2,3 to 24 command
and just run and you will have estimate time, could update me your estimate time ?
The estimation for 100bit key with 24x2080ti is approximately 24 hours. 24x2080ti has 29500MJump/sec, so 2^(100/2+1.15) / 29500Mjumps/sec --> 24 hours mean if you run 400 gpu, then how you could found 110 bit in 2 days ?  |
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-snip-
how much gpu's you have ?
now left 24x2080ti, around half GPU is out of race. As say Turing, machine working we need only give him what he is undertsand..   could you try this for calc time about your 24 2080ti gpu for 100 bit 0314AA23C847D86CE1FCDC4B3E0524F741FDE2AC4B38B522ED2E3B77CF500D5718 and you can use client server or single system with gpuid 0,1,2,3 to 24 command and just run and you will have estimate time, could update me your estimate time ? |
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There seems to be some kind of mistake in this puzzle#110
A huge number of GPU capacities have already been spent and no one could find the key.
I checked the range borders with bsgs, there is no key there.
This was the only version why we could not find the key for so long.
But she is not true. The key is not near the edge.
Someone has an idea why we can’t find the key .. even with the possibility of 400 GPU?
how much gpu's you have ? |
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Updated fork https://github.com/alek76-2/vs-kangaroo-multiIt uses a lot of working files and little RAM. ./vs-kangaroo-multi -v 1 -gpu -d 14 -p 8 -bits 70 0290e6900a58d33393bc1097b5aed31f2e4e7cbd3e5466af958665bc0121248483 [###########################################################]
[# Pollard-kangaroo PrivKey Recovery Tool #]
[# (based on engine of VanitySearch 1.15) #]
[# bitcoin ecdsa secp256k1 #]
[# ver 0.01 GPU Hybrid v54 Many work files #]
[# GPU implementation changes by alek76 #]
[# Tips: 1NULY7DhzuNvSDtPkFzNo6oRTZQWBqXNE9 #]
[###########################################################]
[DATE(utc)] 25 May 2020 20:54:14
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[pow2bits] 70
[Wsqrt] (2^34) 800000000
[M] 300000000000000000
[rangeW] 2^69..2^70 ; W = U - L = 2^69
[DPsize] 1048576 (hashtable size)
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[pubkey#70] loaded
[Xcoordinate] 90E6900A58D33393BC1097B5AED31F2E4E7CBD3E5466AF958665BC0121248483
[Ycoordinate] D7319F127105F492FD15E009B103B4A83295722F28F07C95F9A5443EF8E77CE0
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[+] Sp-table of pow2 points - ready
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[UV] U*V=0*0=0 (0x00)
[optimal_mean_jumpsize] 0
[meanjumpsize#1] 1(now) <= 0(optimal) <= 1(next)
[i] Sp[0]|J-|Sp[1]
[i] this Sp set has low efficiency (over -25%) for this mean jumpsize
[JmaxofSp] Sp[1]=0 nearer to optimal mean jumpsize of Sp set
[i] Old DPmodule: 2^32
[i] New DPmodule: 2^24
[DPmodule] 2^24 = 16777216 (0x0000000001000000)
[+] 0T+0W kangaroos - ready
[CPU] threads: 0
[GPU] threads: 1 Hang on to your hats... ;-)
[i] Create work files!
[i] Used Comparator in Python
===========================================================================
by Pollard (.. The best choice of m (mean jump size: 2^17) is w^(1/2)/2 ..)
Create Jump Table (size: 32) Max Jump: 2^26
Jump Avg distance: 2^23.96 (+/- use option -p)
===========================================================================
GPUEngine: Fixed DPmodule = 2^14
GPUEngine: Total kangaroos and their close relatives 1835008 ;-)
GPUEngine: Fixed DPmodule: 0x4000 2^14 Hop_modulo: 32 Power: 8
GPU GPU #0 Tesla P100-PCIE-16GB (56x64 cores) Grid(112x128) (177.0 MB used; GRP size: 128)
GPU Bits: 70
GPU Tame Points: [M] + Rand(pow2W-0)
GPU Wild Points: [Target] + Rand(pow2W-0)
GPU Wild Starting Key 0: 12E58930DFDEB47505
GPU Tame Starting Key 1: 45A623A241D377A49C
GPU Wild Starting Key 2: C7B91ADE6A671194
GPU Tame Starting Key 3: 320CE971AD9B185B8F
GPU Wild Starting Key 4: 1F607F8EC52B53B480
GPU Tame Starting Key 5: 3E626B1545E9C088C6
GPU Wild Starting Key 6: 21890EC6628CB0CED
GPU Tame Starting Key 7: 3922A570BB7E6AF773
GPU Wild Starting Key 8: 1BB931960AF29FFD96
GPU Tame Starting Key 9: 4603E150EA74DDEB62
GPU Tame Starting Key 1820672: 4F28F74CB75B693030 Kangaroos: 1835008
[+] Runing Comparator every: 30 sec
Python Comparator time: 646.903 msec
[-][ 0: 0:40 ; 453.1M j/s; [GPU 453.14 Mj/s] 18.0Gj 54.8%; dp/kgr=0.0; 0: 0:34 ]
Python Comparator time: 9735.188 msec
[|][ 0: 1:24 ; 442.2M j/s; [GPU 442.16 Mj/s] 39.0Gj 114.8%; dp/kgr=0.0; 0: 0: 0 ]
SOLVED: 0x349b84b6431a6c4ef1L
Tips: 1NULY7DhzuNvSDtPkFzNo6oRTZQWBqXNE9
[i] No Cleaning wild and tame files
[i] 468.0M j/s; 39.0Gj of 34.0Gj 115.8%; DP 0T+0W=0+0=0; dp/kgr=0.0;
[runtime] 0: 1:25
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[DATE(utc)] 25 May 2020 20:56:00
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[x] EXIT
Another test. bit 80 ./vs-kangaroo-multi -v 1 -gpu -d 16 -bits 80 037e1238f7b1ce757df94faa9a2eb261bf0aeb9f84dbf81212104e78931c2a19dc [###########################################################]
[# Pollard-kangaroo PrivKey Recovery Tool #]
[# (based on engine of VanitySearch 1.15) #]
[# bitcoin ecdsa secp256k1 #]
[# ver 0.01 GPU Hybrid v54 Many work files #]
[# GPU implementation changes by alek76 #]
[# Tips: 1NULY7DhzuNvSDtPkFzNo6oRTZQWBqXNE9 #]
[###########################################################]
[DATE(utc)] 26 May 2020 06:35:43
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[pow2bits] 80
[warning!] bits = 2^79 too big! long runtime expected
[Wsqrt] (2^39) 10000000000
[M] C0000000000000000000
[rangeW] 2^79..2^80 ; W = U - L = 2^79
[DPsize] 1048576 (hashtable size)
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[pubkey#80] loaded
[Xcoordinate] 7E1238F7B1CE757DF94FAA9A2EB261BF0AEB9F84DBF81212104E78931C2A19DC
[Ycoordinate] 625C7118F1C29CB92D28CE0DFD0DC58144FE5572EFFEBC7FEE54C4FCE3333A6B
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[+] Sp-table of pow2 points - ready
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[UV] U*V=0*0=0 (0x00)
[optimal_mean_jumpsize] 0
[meanjumpsize#1] 1(now) <= 0(optimal) <= 1(next)
[i] Sp[0]|J-|Sp[1]
[i] this Sp set has low efficiency (over -25%) for this mean jumpsize
[JmaxofSp] Sp[1]=0 nearer to optimal mean jumpsize of Sp set
[i] Old DPmodule: 2^37
[i] New DPmodule: 2^24
[DPmodule] 2^24 = 16777216 (0x0000000001000000)
[+] 0T+0W kangaroos - ready
[CPU] threads: 0
[GPU] threads: 1 Hang on to your hats... ;-)
[i] Created work files!
[i] Used Comparator in Python
===========================================================================
by Pollard (.. The best choice of m (mean jump size: 2^19) is w^(1/2)/2 ..)
Create Jump Table (size: 32) Max Jump: 2^20
Jump Avg distance: 2^18.00 (+/- use option -p)
===========================================================================
GPUEngine: Fixed DPmodule = 2^16
GPUEngine: Total kangaroos and their close relatives 1835008 ;-)
GPUEngine: Fixed DPmodule: 0x10000 2^16 Hop_modulo: 32 Power: 0
GPU GPU #0 Tesla P100-PCIE-16GB (56x64 cores) Grid(112x128) (177.0 MB used; GRP size: 128)
GPU Bits: 80
GPU Tame Points: [M] + Rand(pow2W-0)
GPU Wild Points: [Target] + Rand(pow2W-0)
GPU Wild Starting Key 0: 67420ED7AAEA820D62BA
GPU Tame Starting Key 1: C2D51BD44986DF40CA00
GPU Wild Starting Key 2: 5655ACEEB25192BDC3F8
GPU Tame Starting Key 3: 117145C5368E584A9C76B
GPU Wild Starting Key 4: F14C72CD00508F65D84
GPU Tame Starting Key 5: 130F65A975DBD8C4DE1EB
GPU Wild Starting Key 6: 40F88A933B208EB5A52D
GPU Tame Starting Key 7: FD9239E4BC99E5598345
GPU Wild Starting Key 8: 2F9BF81524055DC6E03E
GPU Tame Starting Key 9: 106C72ED5CB65D500D212
GPU Tame Starting Key 1820672: DDFC7A0EFBB5710118AE Kangaroos: 1835008
[+] Runing Comparator every: 30 sec
Python Comparator time: 500.395 msec
[-][ 0: 0:32 ; 486.1M j/s; [GPU 486.11 Mj/s] 15.0Gj 1.4%; dp/kgr=0.0; 0:37: 9 ]
Python Comparator time: 2106.200 msec
[\][ 0: 1: 6 ; 486.2M j/s; [GPU 486.15 Mj/s] 32.0Gj 2.9%; dp/kgr=0.0; 0:36:35 ]
Python Comparator time: 3663.671 msec
[/][ 0: 1:42 ; 486.2M j/s; [GPU 486.18 Mj/s] 49.0Gj 4.5%; dp/kgr=0.0; 0:35:59 ]
Python Comparator time: 5324.540 msec
[|][ 0: 2:20 ; 484.4M j/s; [GPU 484.35 Mj/s] 67.0Gj 6.1%; dp/kgr=0.0; 0:35:29 ]
Python Comparator time: 7057.574 msec
[|][ 0: 3: 0 ; 484.3M j/s; [GPU 484.35 Mj/s] 87.0Gj 7.9%; dp/kgr=0.0; 0:34:49 ]
Python Comparator time: 8986.801 msec
[|][ 0: 3:40 ; 486.2M j/s; [GPU 486.18 Mj/s] 106.0Gj 9.6%; dp/kgr=0.0; 0:34: 1 ]
Python Comparator time: 10986.165 msec
[-][ 0: 4:24 ; 486.0M j/s; [GPU 486.03 Mj/s] 128.0Gj 11.6%; dp/kgr=0.0; 0:33:18 ]
Python Comparator time: 12920.514 msec
[/][ 0: 5:10 ; 484.3M j/s; [GPU 484.33 Mj/s] 150.0Gj 13.6%; dp/kgr=0.0; 0:32:39 ]
Python Comparator time: 15202.427 msec
[/][ 0: 5:58 ; 484.3M j/s; [GPU 484.35 Mj/s] 173.0Gj 15.8%; dp/kgr=0.0; 0:31:51 ]
Python Comparator time: 17392.388 msec
[-][ 0: 6:48 ; 486.2M j/s; [GPU 486.17 Mj/s] 198.0Gj 18.0%; dp/kgr=0.0; 0:30:53 ]
Python Comparator time: 20498.843 msec
[/][ 0: 7:42 ; 484.3M j/s; [GPU 484.32 Mj/s] 224.0Gj 20.4%; dp/kgr=0.0; 0:30: 6 ]
Python Comparator time: 22830.591 msec
[/][ 0: 8:38 ; 484.3M j/s; [GPU 484.34 Mj/s] 251.0Gj 22.9%; dp/kgr=0.0; 0:29:10 ]
Python Comparator time: 25163.966 msec
[-][ 0: 9:36 ; 484.3M j/s; [GPU 484.35 Mj/s] 279.0Gj 25.4%; dp/kgr=0.0; 0:28:12 ]
Python Comparator time: 27661.919 msec
[|][ 0:10:36 ; 484.2M j/s; [GPU 484.25 Mj/s] 308.0Gj 28.0%; dp/kgr=0.0; 0:27:12 ]
Python Comparator time: 30292.003 msec
[|][ 0:11:40 ; 486.1M j/s; [GPU 486.11 Mj/s] 339.0Gj 30.9%; dp/kgr=0.0; 0:26: 2 ]
Python Comparator time: 32717.330 msec
[/][ 0:12:46 ; 486.1M j/s; [GPU 486.11 Mj/s] 372.0Gj 33.8%; dp/kgr=0.0; 0:24:56 ]
Python Comparator time: 36437.393 msec
[|][ 0:13:56 ; 486.2M j/s; [GPU 486.17 Mj/s] 406.0Gj 36.9%; dp/kgr=0.0; 0:23:46 ]
Python Comparator time: 39898.262 msec
[/][ 0:15:10 ; 484.3M j/s; [GPU 484.28 Mj/s] 441.0Gj 40.1%; dp/kgr=0.0; 0:22:37 ]
Python Comparator time: 43553.040 msec
[|][ 0:16:28 ; 486.1M j/s; [GPU 486.11 Mj/s] 479.0Gj 43.6%; dp/kgr=0.0; 0:21:14 ]
Python Comparator time: 47073.931 msec
[/][ 0:17:50 ; 484.3M j/s; [GPU 484.35 Mj/s] 519.0Gj 47.2%; dp/kgr=0.0; 0:19:57 ]
Python Comparator time: 51252.606 msec
[|][ 0:19:16 ; 486.0M j/s; [GPU 485.99 Mj/s] 561.0Gj 51.0%; dp/kgr=0.0; 0:18:27 ]
Python Comparator time: 55476.482 msec
[-][ 0:20:48 ; 484.3M j/s; [GPU 484.35 Mj/s] 606.0Gj 55.1%; dp/kgr=0.0; 0:16:58 ]
Python Comparator time: 60563.812 msec
[/][ 0:22:22 ; 486.2M j/s; [GPU 486.15 Mj/s] 651.0Gj 59.2%; dp/kgr=0.0; 0:15:20 ]
Python Comparator time: 64661.246 msec
[\][ 0:24: 2 ; 484.4M j/s; [GPU 484.35 Mj/s] 700.0Gj 63.6%; dp/kgr=0.0; 0:13:43 ]
Python Comparator time: 69173.400 msec
[|][ 0:25:48 ; 486.1M j/s; [GPU 486.09 Mj/s] 751.0Gj 68.4%; dp/kgr=0.0; 0:11:55 ]
Python Comparator time: 75678.491 msec
[|][ 0:27:40 ; 486.2M j/s; [GPU 486.19 Mj/s] 806.0Gj 73.2%; dp/kgr=0.0; 0:10: 3 ]
Python Comparator time: 82198.230 msec
[/][ 0:29:42 ; 484.3M j/s; [GPU 484.35 Mj/s] 865.0Gj 78.6%; dp/kgr=0.0; 0: 8: 3 ]
Python Comparator time: 90042.401 msec
[|][ 0:30:28 ; 486.2M j/s; [GPU 486.19 Mj/s] 887.0Gj 80.8%; dp/kgr=0.0; 0: 7:15 ]
SOLVED: 0xea1a5c66dcc11b5ad180L
Tips: 1NULY7DhzuNvSDtPkFzNo6oRTZQWBqXNE9
[/][ 0:30:30 ; 486.2M j/s; [GPU 486.19 Mj/s] 888.0Gj 80.8%; dp/kgr=0.0; 0: 7:13 ]
[i] No Cleaning wild and tame files
[i] 485.9M j/s; 889.0Gj of 1.0Tj 80.8%; DP 0T+0W=0+0=0; dp/kgr=0.0;
[runtime] 0:30:30
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[DATE(utc)] 26 May 2020 07:06:35
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[x] EXIT
Good luck to all! what a mean for multi ? |
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Multiple search is possible but I won't work on it first.
I will work on a distributed client/server version.
The #110 will be likely solved soon.
With the distributed version, I'm almost sure the #115 will also be solved.
110 solve depend on multiple pubkeys search at once, in others , you all will spend time in jumping here and there, mean you need lot of gpu powers, you need lot of ram, etc, and you can not manage all things togather, and no one have these all option available, only my last word, if you design multiple pubkeys search ver, that will be solution for just within 3 days Enjoy your research!!! I am not sure the multiple pubkey search will really help to solve #110 within 3 days. As I see your idea is to "decrease" the pow of the key and solve the lower bits key, however decreasing the power you will also receive the incorrect public keys which will be the dust for you and will "burn" the resources. This is the example what you want to do (correct me if I am not right): 1) The key #110 (with kno public key P110) has range with width 2^109 (start range is 2^109, end range is 2^110-1). To solve it, the current GPU solver needs approx. 2.22*sqrt(2^109) = 2^55.652) You want to divide this key by some number and receive the "lower bit" public key and solve that new one. Let's imagine you want to receive the key with range 2^90 instead of 2^109, so you need to divide by 2^(109-90) = 2^19 = 524 288. However as you do not know the remainder from that division you should check all the keys. 3) You make 2^19 (524 288) additions (or divisions, it does not matter) of P110 with points 0*G, 1*G, 2*G, 3*G, ... 2^19-1*G (total 2^19 points) and receive 2^19 new points. All these new points are subsequent points, and the scalar of one of that points could be divided by 2^19 with 0 remainder. 4) Now you divide (i.e multiply by inverse scalar) every of these new points by 2^19, and receive another set of 2^19 points, where one of them will be in range 2^90 5) New range for that divided points is now from 2^90 to 2^91-1 (with width exactly 2^90). However, you do not know which point from generated 2^19 is that one with the private key in the new range. So you should check all of them, all 524 288 points (2^19). Yes, the solver could find 90 bit range for some hours, but only for one key to search. If you put 2^19 public keys, (a) the speed will not be the same as for one, (b) you will have "wrong" DPs in the hashtable generated by wild kangaroos started from "wrong" points. Only 1 point from 2^19 is correct, others are wrong and will never solved (because of the incorrect range for them). Now, let's calculate the number of operations required to solve these 2^19 new public keys with new ranges (with one key in range 2^90). For one key, the total number of operations is 2.22*sqrt(2^90) = 2^46.15; However we have not one, but 2^19 key to check. So, the total number of operations for all new generated public keys is 2^19 * 2^46.15 = 2^65.15So, with the whole range you could solve the key for 2^55.65 operations, but now need 2^65.15 operations. This is 725 times more (2^9.5) Moreover, this approximation does not count the new overheads due to incorrect DPs in hashtable. Even you have several independent public keys in the same range, running their solving altogether at the same time will proportionally decrease the speed to find the collision. Dear Friends your mention method of division pubkeys point, are an other way, and maybe not workable as you said, my Proof of Exact 1 key inside low pow you tested, you stated " total number of operations for all new generated public keys is 2^19 * 2^46.15 = 2^65.15 " its also not multi pubkeys search method, its look like each key create its own dp points, and start, and think 2**19 point how much ram you need, ? here for 1 key in big range peoples facing ram problem. its already i mention in above my message multi pubkey search will be multi pubkeys support ver example bitcrack load 1 key my gpu 45mkeys, 100k keys load 40mkeys, gradually last 25 million keys load 33mkeys, and 925mb/1gb ram used for 25m keys, similar when kangaroo ver support multiple pubkeys checking, it show decress speed some how 10% 20% etc, not like " total number of operations for all new generated public keys is 2^19 * 2^46.15 = 2^65.15" Jean Luc understand how multikey search could work, hope you all will have ability to understand what method could be applied for multi support |
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Multiple search is possible but I won't work on it first.
I will work on a distributed client/server version.
The #110 will be likely solved soon.
With the distributed version, I'm almost sure the #115 will also be solved.
110 solve depend on multiple pubkeys search at once, in others , you all will spend time in jumping here and there, mean you need lot of gpu powers, you need lot of ram, etc, and you can not manage all things togather, and no one have these all option available, only my last word, if you design multiple pubkeys search ver, that will be solution for just within 3 days Enjoy your research!!! |
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If i have 10 PC with different cpu cores numbers, how i can setup the program to search for same private key but on different range and to run program on all PC?
PC 1 to search for 10% of private keys PC 2 for next 10% and so on and the last for last 10%?
try now gpu version for Kangaroo https://github.com/JeanLucPons/Kangaroo |
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hi all
I have a question - how do you get Biginteger PVK? Of what? what you need to take to get Biginteger PVK
example:
Address 6:
KwDiBf89QgGbjEhKnhXJuH7LrciVrZi3qYjgd9M7rFU7Tmu6qHxS
1PitScNLyp2HCygzadCh7FveTnfmpPbfp8
Biginteger PVK value: 49 - where did this number come from?
Hex PVK value: 31
Jeanluc GPU Kangaroo version launched, Enjoy high speed https://github.com/JeanLucPons/Kangaroo |
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How to add write to txt resoult option tihs code?
from bitcoin import *
with open("pubkey.txt") as f:
for line in f:
print(pubtoaddr(line.strip()))
Jeanluc GPU version launched, Enjoy high speed https://github.com/JeanLucPons/Kangaroo |
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today jeanluc post Kangaroo for cpu its much fast and better then alek76 gpu version check his link and results BSGS (baby step) https://github.com/JeanLucPons/BSGS/issuesKangaroo https://github.com/JeanLucPons/Kangarootest 65 bit at i3-6100 2 core 4thread processor :~/jean/Kangaroo$ ./kangaroo in.txt Kangaroo v1.0 Start:10000000000000001 Stop :1FFFFFFFFFFFFFFFF Keys :1 Number of CPU thread: 4 Range width: 2^64 Number of random walk: 2^12.00 (Max DP=18) DP size: 18 [0xffffc00000000000] Solvekey Thread 0: 1024 TAME kangaroos Solvekey Thread 1: 1024 TAME kangaroos Solvekey Thread 2: 1024 WILD kangaroos Solvekey Thread 3: 1024 WILD kangaroos [11.56 MKey/s][Count 2^33.15][14:29][Dead 1][6.9MB] Key# 0 Pub: 0x023115A92D2D604381E154EDAC700D4D99AC44F8E2B1274E16524583D1D52DDDC0 Priv: 0x150E316D058E7AFF8 Done: Total time 14:30 |
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you should go back in earlier post to you, where i said you need to correct define, block, thread and process, and you will get 10x faster speed hope you soon you will able to assign this in user level with switches -b -t -p , as per bitcracked assign for manage load of full GPU power |
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Please how can I solve that problem ?  [###########################################################]
[# Pollard-kangaroo PrivKey Recovery Tool #]
[# (based on engine of VanitySearch 1.15) #]
[# bitcoin ecdsa secp256k1 #]
[# ver 0.01 GPU Hybrid v4F #]
[# GPU implementation changes by alek76 #]
[# Tips: 1NULY7DhzuNvSDtPkFzNo6oRTZQWBqXNE9 #]
[###########################################################]
[i] Comparator time: 2.836 msec wild.txt 0 bytes tame.txt 0 bytes seems like here is the error :GPUEngine: Kernel: no kernel image is available for execution on the device pls print your complete command for execuation you run Here is the command. I am using GPU Tesla P4 with CCap=70 as I see in wikipidia. ./vs-kangaroo-hybrid -v 1 -p 8 -bits 56 -gpu 0230210c23b1a047bc9bdbb13448e67deddc108946de6de639bcc75d47c0216b1b remove in folder rm -R obj rm vs-kangaroo-hybrid recompile from start with this command make gpu=1 ccap=61 all then run command as i mention with correction |
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Please how can I solve that problem ? [###########################################################]
[# Pollard-kangaroo PrivKey Recovery Tool #]
[# (based on engine of VanitySearch 1.15) #]
[# bitcoin ecdsa secp256k1 #]
[# ver 0.01 GPU Hybrid v4F #]
[# GPU implementation changes by alek76 #]
[# Tips: 1NULY7DhzuNvSDtPkFzNo6oRTZQWBqXNE9 #]
[###########################################################]
[i] Comparator time: 2.836 msec wild.txt 0 bytes tame.txt 0 bytes seems like here is the error :GPUEngine: Kernel: no kernel image is available for execution on the device pls print your complete command for execuation you run Here is the command. I am using GPU Tesla P4 with CCap=70 as I see in wikipidia. ./vs-kangaroo-hybrid -v 1 -p 8 -bits 56 -gpu 0230210c23b1a047bc9bdbb13448e67deddc108946de6de639bcc75d47c0216b1b try this ./vs-kangaroo-hybrid -v 1 -gpu -p 8 -bits 56 0230210c23b1a047bc9bdbb13448e67deddc108946de6de639bcc75d47c0216b1b |
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Please how can I solve that problem ? [###########################################################]
[# Pollard-kangaroo PrivKey Recovery Tool #]
[# (based on engine of VanitySearch 1.15) #]
[# bitcoin ecdsa secp256k1 #]
[# ver 0.01 GPU Hybrid v4F #]
[# GPU implementation changes by alek76 #]
[# Tips: 1NULY7DhzuNvSDtPkFzNo6oRTZQWBqXNE9 #]
[###########################################################]
[DATE(utc)] 05 Apr 2020 22:22:00
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[pow2bits] 65
[Wsqrt] (2^32) 100000000
[M] 18000000000000000
[rangeW] 2^64..2^65 ; W = U - L = 2^64
[DPsize] 1048576 (hashtable size)
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[pubkey#65] loaded
[Xcoordinate] 30210C23B1A047BC9BDBB13448E67DEDDC108946DE6DE639BCC75D47C0216B1B
[Ycoordinate] E383C4A8ED4FAC77C0D2AD737D8499A362F483F8FE39D1E86AAED578A9455DFC
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[+] Sp-table of pow2 points - ready
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[UV] U*V=0*0=0 (0x00)
[optimal_mean_jumpsize] 0
[meanjumpsize#1] 1(now) <= 0(optimal) <= 1(next)
[i] Sp[0]|J-|Sp[1]
[i] this Sp set has low efficiency (over -25%) for this mean jumpsize
[JmaxofSp] Sp[1]=0 nearer to optimal mean jumpsize of Sp set
[i] Old DPmodule: 2^30
[i] New DPmodule: 2^24
[DPmodule] 2^24 = 16777216 (0x0000000001000000)
[+] 0T+0W kangaroos - ready
[CPU] threads: 0
[GPU] threads: 1 Hang on to your hats... ;-)
[optimal_mean_jumpsize] 80000000
[meanjumpsize#36] 71C71C71(now) <= 80000000(optimal) <= DD67C8A6(next)
[i] Sp[36]|-------J----------------------------------------------------|Sp[37]
[JmaxofSp] Sp[36]=71C71C71 nearer to optimal mean jumpsize of Sp set
GPUEngine: DPmodule: 0x400000 2^22 ((pow2W-(2*Power))/2)-2 Hop_modulo: 44 Power: 8
GPU: GPU #0 Tesla P4 (20x128 cores) Grid(160x128)
GPU Bits: 65
GPU Tame Points: [M] + Rand(pow2W-0)
GPU Tame Starting Key 0: 18000000000000000
GPU Tame Starting Key 1: 206BBC3513D1733A1
GPU Tame Starting Key 2: 25E5235429CA09EF3
GPU Tame Starting Key 3: 2583FB778385DFCD4
GPU Tame Starting Key 4: 1ED1A56D0C06ACCCE
GPU Tame Starting Key 5: 189D65AB36B1D055D
GPU Tame Starting Key 6: 1FA2EABEE40E79BBD
GPU Tame Starting Key 7: 197A3A27B31F5B3D2
GPU Tame Starting Key 8: 206650FB29F02B360
GPU Tame Starting Key 9: 1EE2B45C9529E6C93
GPU Tame Starting Key 20479: 233950B74491CF338 Thread: 20480
GPU Wild Points: [Target] + Rand(pow2W-1)
GPU Wild Starting Key 0: 54D8F8548F7AB6F2
GPU Wild Starting Key 1: 120CEF3BC316421C
GPU Wild Starting Key 2: 7D4E0E90EF29A037
GPU Wild Starting Key 3: 57CFAF613008D1A9
GPU Wild Starting Key 4: 31B859A6B2E3D9D9
GPU Wild Starting Key 5: 6E628C3C53724423
GPU Wild Starting Key 6: 56164090D10C621F
GPU Wild Starting Key 7: 1414DCD8273FD23E
GPU Wild Starting Key 8: 4012C93B385FECD4
GPU Wild Starting Key 9: 3213AB3E8E022B15
GPU Wild Starting Key 20479: 1C6C36C06F3EF445 Thread: 20480
GPUEngine: Kernel: no kernel image is available for execution on the device
[i] Used Comparator in C++
[i]
[+] Runing Comparator every: 32 sec
0.0 j/s; 0.0 j of 8.0Gj 0.0%; DP 0T+0W=0+0=0; dp/kgr=0.0;
[runtime] 0: 0: 1
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[DATE(utc)] 05 Apr 2020 22:22:01
[~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]
[x] EXIT
[i] Comparator time: 2.836 msec wild.txt 0 bytes tame.txt 0 bytes seems like here is the error :GPUEngine: Kernel: no kernel image is available for execution on the device pls print your complete command for execuation you run |
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Unfortunatelly I'm not really expert in this. I'm using 'Visual Studio 2019'.
I have finally succeded to comply vs-kangaroo-hybrid.exe by choosing 'Release' in configuration (before was 'Debug' by default), but without any aadditional settings. Just as it was.
Where do I put this settings "make gpu=1 ccap=20 all"?
Another question here. Runnigng test and found that script goes over 100% i.e. for #50:
Compute capability 2.0 and 3.0 Not supported. This is normal, the program does not make accurate calculations. Set -p 0 or for bits 50 use cpu version. Feedback if run for bit 65 Comparator time: 0.206 msec wild.txt 0 bytes tame.txt 0 bytes
[/][ 0: 0: 6 ; 4.4M j/s; [GPU 4.43 Mj/s] 26.0Mj 0.2%; dp/kgr=0.0; 0:32:11 ]
upword any bit like bit 75 screen is
Comparator time: 0.195 msec wild.txt 0 bytes tame.txt 0 bytes
[\][ 0: 0: 2 ; 0.0 j/s; [GPU 0.00 Mj/s] 0.0 j 0.0%; dp/kgr=0.0; 8.0Ky 4m 17d 6: 9: 4 ]
Which video card do you use? What options does the program run with? gtx 460 and gtx 750 |
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Unfortunatelly I'm not really expert in this. I'm using 'Visual Studio 2019'.
I have finally succeded to comply vs-kangaroo-hybrid.exe by choosing 'Release' in configuration (before was 'Debug' by default), but without any aadditional settings. Just as it was.
Where do I put this settings "make gpu=1 ccap=20 all"?
Another question here. Runnigng test and found that script goes over 100% i.e. for #50:
Compute capability 2.0 and 3.0 Not supported. This is normal, the program does not make accurate calculations. Set -p 0 or for bits 50 use cpu version. Feedback if run for bit 65 Comparator time: 0.206 msec wild.txt 0 bytes tame.txt 0 bytes
[/][ 0: 0: 6 ; 4.4M j/s; [GPU 4.43 Mj/s] 26.0Mj 0.2%; dp/kgr=0.0; 0:32:11 ]
upword any bit like bit 75 screen is
Comparator time: 0.195 msec wild.txt 0 bytes tame.txt 0 bytes
[\][ 0: 0: 2 ; 0.0 j/s; [GPU 0.00 Mj/s] 0.0 j 0.0%; dp/kgr=0.0; 8.0Ky 4m 17d 6: 9: 4 ]
for bit 69 these screen running Comparator time: 0.217 msec wild.txt 0 bytes tame.txt 0 bytes
[|][ 0: 0: 4 ; 4.4M j/s; [GPU 4.36 Mj/s] 17.0Mj 0.0%; dp/kgr=0.0; 1: 5:39 ]
[error] Check Output Data GPU and Compute keys, thId: 00005028
Check key: 94AC90F4A122647D5
Point x: 2B6E5F02AE99AA03569FE46C5A0EAED92D350A5A3D0E091085E9E8BDA6ABE66D
DP Point x: 8BBFEFA75BE67C6795D772D977373999C9A364A8994893793AA417BEE000000
[/][ 0: 0: 6 ; 4.4M j/s; [GPU 4.43 Mj/s] 26.0Mj 0.1%; dp/kgr=0.0; 1: 4:29 ]
[error] Check Output Data GPU and Compute keys, thId: 00000507
Check key: 7EF29F937A9658E03
Point x: B75CF00099B38C6BC3466A69ADFEADDD093EDE62E763DF5555A4F2A221F04F3C
DP Point x: 27F28829B7176A93E6D7AB93A6DA89C5CAD41B5D35425FF6F34C464253000000
[error] Check Output Data GPU and Compute keys, thId: 00005423
Check key: 90C0FA63868810BAB
Point x: E8C5AFF0F27DC6E81D285E058ED35A7F00DB29CCDD51E6B2AA66EB9C9C2665E6
DP Point x: 668F60B040F727C225D697BCA37C2D8A1133422F8EA0F7B3C30D2D77C8000000
[\][ 0: 0:10 ; 4.4M j/s; [GPU 4.40 Mj/s] 44.0Mj 0.2%; dp/kgr=0.0; 1: 4:51 ]
[error] Check Output Data GPU and Compute keys, thId: 00000587
Check key: 8EE434059E01B3660
Point x: 45356089D2471D7F4AEA9D5CE0C410628B9A03845B2C075BF22081298095F846
DP Point x: BBCF411A3D896480FE6006C65C6F48D90F7F1DFDA8ED122B9CFEE5BF9F000000 |
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Unfortunatelly I'm not really expert in this. I'm using 'Visual Studio 2019'.
I have finally succeded to comply vs-kangaroo-hybrid.exe by choosing 'Release' in configuration (before was 'Debug' by default), but without any aadditional settings. Just as it was.
Where do I put this settings "make gpu=1 ccap=20 all"?
Another question here. Runnigng test and found that script goes over 100% i.e. for #50:
Compute capability 2.0 and 3.0 Not supported. This is normal, the program does not make accurate calculations. Set -p 0 or for bits 50 use cpu version. Feedback if run for bit 65 Comparator time: 0.206 msec wild.txt 0 bytes tame.txt 0 bytes
[/][ 0: 0: 6 ; 4.4M j/s; [GPU 4.43 Mj/s] 26.0Mj 0.2%; dp/kgr=0.0; 0:32:11 ]
upword any bit like bit 75 screen is
Comparator time: 0.195 msec wild.txt 0 bytes tame.txt 0 bytes
[\][ 0: 0: 2 ; 0.0 j/s; [GPU 0.00 Mj/s] 0.0 j 0.0%; dp/kgr=0.0; 8.0Ky 4m 17d 6: 9: 4 ]
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i just see issue at your github, same stuck at error with gtx 750, maybe problem of hashtable size, check it
Hashtable for the CPU. What does ptxas info say? whats your makefile setting for cuda 8 same issues as mention here with cuda 8 https://github.com/alek76-2/vs-kangaroo-hybrid/issues |
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i just see issue at your github, same stuck at error with gtx 750, maybe problem of hashtable size, check it
Hashtable for the CPU. What does ptxas info say? whats your makefile setting for cuda 8 |
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2days before i see alek76 message in post, he said soon at github, today i see, his post deleted, maybe he chnage his mind, and his new mind maybe work better then old mind Right. First you need to fix possible inaccuracies, then there is no time to do this on Github. The comparator on python works faster than on c ++, when the file sizes are more than 50MB - have to choose a comparator. In general, the correct way is to do the aggregation of selected points in the sql database on the server. The program should send them as a client. I have no time and knowledge for this I will soon post it as it is.Already available https://github.com/alek76-2/vs-kangaroo-hybridThanks, brother! Can you help, I get this error when triying to run after successfull complilation.  Your GPU code not compiled , mention in your snap have u compiled by this command make gpu=1 ccap=20 all where ccap setting as per your card ... |
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