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Topic: BitCrack - A tool for brute-forcing private keys - page 72. (Read 76850 times)

member
Activity: 275
Merit: 20
the right steps towerds the goal
RTX 3070 test
[2020-12-02.22:02:19] [Info] Starting at:  0000000000000000000000000000000000000000000000007CCE5EFDACCF6808
[2020-12-02.22:02:19] [Info] Ending at:    000000000000000000000000000000000000000000000001A838B13505B26867
[2020-12-02.22:02:19] [Info] Counting by: 0000000000000000000000000000000000000000000000000000000000000001
[2020-12-02.22:02:20] [Info] Compiling OpenCL kernels...
[2020-12-02.22:02:20] [Info] Initializing GeForce RTX 3070
[2020-12-02.22:02:24] [Info] Generating 57,344,000 starting points (2187.5MB)
[2020-12-02.22:02:31] [Info] 10.0%
[2020-12-02.22:02:32] [Info] 20.0%
[2020-12-02.22:02:33] [Info] 30.0%
[2020-12-02.22:02:33] [Info] 40.0%
[2020-12-02.22:02:34] [Info] 50.0%
[2020-12-02.22:02:34] [Info] 60.0%
[2020-12-02.22:02:34] [Info] 70.0%
[2020-12-02.22:02:34] [Info] 80.0%
[2020-12-02.22:02:35] [Info] 90.0%
[2020-12-02.22:02:35] [Info] 100.0%
[2020-12-02.22:02:35] [Info] Done
GeForce RTX 3070 3500 / 8192MB | 1 target 777.86 MKey/s (50,290,688,000 total) [00:01:04]

Not too much speed as I expect from 30 series GPU's will you post the benchmark of VanitySearch ??  and it's a ClBitCrack or CuBitcrack ??
newbie
Activity: 12
Merit: 0
RTX 3070 test
[2020-12-02.22:02:19] [Info] Starting at:  0000000000000000000000000000000000000000000000007CCE5EFDACCF6808
[2020-12-02.22:02:19] [Info] Ending at:    000000000000000000000000000000000000000000000001A838B13505B26867
[2020-12-02.22:02:19] [Info] Counting by: 0000000000000000000000000000000000000000000000000000000000000001
[2020-12-02.22:02:20] [Info] Compiling OpenCL kernels...
[2020-12-02.22:02:20] [Info] Initializing GeForce RTX 3070
[2020-12-02.22:02:24] [Info] Generating 57,344,000 starting points (2187.5MB)
[2020-12-02.22:02:31] [Info] 10.0%
[2020-12-02.22:02:32] [Info] 20.0%
[2020-12-02.22:02:33] [Info] 30.0%
[2020-12-02.22:02:33] [Info] 40.0%
[2020-12-02.22:02:34] [Info] 50.0%
[2020-12-02.22:02:34] [Info] 60.0%
[2020-12-02.22:02:34] [Info] 70.0%
[2020-12-02.22:02:34] [Info] 80.0%
[2020-12-02.22:02:35] [Info] 90.0%
[2020-12-02.22:02:35] [Info] 100.0%
[2020-12-02.22:02:35] [Info] Done
GeForce RTX 3070 3500 / 8192MB | 1 target 777.86 MKey/s (50,290,688,000 total) [00:01:04]
jr. member
Activity: 64
Merit: 1
[2020-11-14.19:48:37] [Info] Compression: compressed
[2020-11-14.19:48:37] [Info] Starting at: 000000000000000000000000000000000000000000000000AA1FB16A0289FDB1
[2020-11-14.19:48:37] [Info] Ending at:   000000000000000000000000000000000000000000000000AA1FB16A0299FDB0
[2020-11-14.19:48:37] [Info] Counting by: 0000000000000000000000000000000000000000000000000000000000000001
[2020-11-14.19:48:37] [Info] Compiling OpenCL kernels...

Not an expert, but which devices do you have available for OpenCL? Try running bitcrack with --list-devices to display the ones you have, and then set a device number manually using --device NUMBER.

If you choose a device and it still hangs then maybe one of the kernels built here are big and are taking too long: https://github.com/brichard19/BitCrack/blob/master/CLKeySearchDevice/CLKeySearchDevice.cpp#L55-L60 There are multiplyStepKernel, keyFinderKernel and keyFinderKernelWithDouble kernels built.

Finally I got it back running. Thank you so much for your suggestion about the list. Before resetting, my Geforce was at Device 0. After reset, it went to Device 2. Device 0 become my Intel Graphic and that's why it hangs there and not computing. Once again, thanks and appreciate that.
jr. member
Activity: 64
Merit: 1
[2020-11-14.19:48:37] [Info] Compression: compressed
[2020-11-14.19:48:37] [Info] Starting at: 000000000000000000000000000000000000000000000000AA1FB16A0289FDB1
[2020-11-14.19:48:37] [Info] Ending at:   000000000000000000000000000000000000000000000000AA1FB16A0299FDB0
[2020-11-14.19:48:37] [Info] Counting by: 0000000000000000000000000000000000000000000000000000000000000001
[2020-11-14.19:48:37] [Info] Compiling OpenCL kernels...

Not an expert, but which devices do you have available for OpenCL? Try running bitcrack with --list-devices to display the ones you have, and then set a device number manually using --device NUMBER.

If you choose a device and it still hangs then maybe one of the kernels built here are big and are taking too long: https://github.com/brichard19/BitCrack/blob/master/CLKeySearchDevice/CLKeySearchDevice.cpp#L55-L60 There are multiplyStepKernel, keyFinderKernel and keyFinderKernelWithDouble kernels built.

Last few days it works well with my Nvidia Geforce. After I did some reset on Windows 10, then it just hangs there. It run pretty fast last time before I reset my Windows 10. Should be something went wrong but I just couldn't figure out yet.
jr. member
Activity: 64
Merit: 1
Hi, any expert here can help? Last time my laptop works well. But after I did some Windows 10 repair, it stuck at the message:

[2020-11-14.19:48:37] [Info] Compression: compressed
[2020-11-14.19:48:37] [Info] Starting at: 000000000000000000000000000000000000000000000000AA1FB16A0289FDB1
[2020-11-14.19:48:37] [Info] Ending at:   000000000000000000000000000000000000000000000000AA1FB16A0299FDB0
[2020-11-14.19:48:37] [Info] Counting by: 0000000000000000000000000000000000000000000000000000000000000001
[2020-11-14.19:48:37] [Info] Compiling OpenCL kernels...

Any idea or suggestion?

Generic suggestion,
1. Reinstall the GPU driver
2. Reinstall the OpenCL SDK/library (different GPU uses different SDK/library)

I update my Nvidia driver and written it's the latest.
Already install the OpenCL SDK/library as well.

Just couldn't get what went wrong.
legendary
Activity: 1568
Merit: 6660
bitcoincleanup.com / bitmixlist.org
[2020-11-14.19:48:37] [Info] Compression: compressed
[2020-11-14.19:48:37] [Info] Starting at: 000000000000000000000000000000000000000000000000AA1FB16A0289FDB1
[2020-11-14.19:48:37] [Info] Ending at:   000000000000000000000000000000000000000000000000AA1FB16A0299FDB0
[2020-11-14.19:48:37] [Info] Counting by: 0000000000000000000000000000000000000000000000000000000000000001
[2020-11-14.19:48:37] [Info] Compiling OpenCL kernels...

Not an expert, but which devices do you have available for OpenCL? Try running bitcrack with --list-devices to display the ones you have, and then set a device number manually using --device NUMBER.

If you choose a device and it still hangs then maybe one of the kernels built here are big and are taking too long: https://github.com/brichard19/BitCrack/blob/master/CLKeySearchDevice/CLKeySearchDevice.cpp#L55-L60 There are multiplyStepKernel, keyFinderKernel and keyFinderKernelWithDouble kernels built.
jr. member
Activity: 64
Merit: 1
Hi, any expert here can help? Last time my laptop works well. But after I did some Windows 10 repair, it stuck at the message:

[2020-11-14.19:48:37] [Info] Compression: compressed
[2020-11-14.19:48:37] [Info] Starting at: 000000000000000000000000000000000000000000000000AA1FB16A0289FDB1
[2020-11-14.19:48:37] [Info] Ending at:   000000000000000000000000000000000000000000000000AA1FB16A0299FDB0
[2020-11-14.19:48:37] [Info] Counting by: 0000000000000000000000000000000000000000000000000000000000000001
[2020-11-14.19:48:37] [Info] Compiling OpenCL kernels...

Any idea or suggestion?
member
Activity: 348
Merit: 34
benchmark

~snip~

  • GeForce RXT 2080 TI = both = 631.57 MKeys/s
  • Tesla V100 = compressed = 603 MKeys/s (with 40k targets)  (config)

I am quite surprised that the Tesla V100 has a lower search rate than the 2080 TI considering that the V100 is meant to be a CUDA-optimized compute GPU, even though this isn’t an apples-to-apples comparison because the 2080 Ti was searching for both types of keys. I’ll keep that in mind when I rent GPUs.

Is there a ready built version available somewhere? Win 64bit

Yep, here are the Windows binaries for v0.31: https://github.com/brichard19/BitCrack/releases/tag/0.31
sorry bro
here is card spec
Tesla V100S PCIe 32 GB   GV100   Nov 26th, 2019   PCIe 3.0 x16   32 GB, HBM2, 4096 bit   1245 MHz   1106 MHz   5120 / 320 / 128
GeForce RTX 2080 Ti   TU102   Sep 20th, 2018   PCIe 3.0 x16   11 GB, GDDR6, 352 bit   1350 MHz   1750 MHz   4352 / 272 / 88

you can understand whats difrence,
here in bitcrack you need to adjust proper setting for -b -t -p
this will tell you what you get highest speed,
others are calc speed wrong
legendary
Activity: 1568
Merit: 6660
bitcoincleanup.com / bitmixlist.org
benchmark

~snip~

  • GeForce RXT 2080 TI = both = 631.57 MKeys/s
  • Tesla V100 = compressed = 603 MKeys/s (with 40k targets)  (config)

I am quite surprised that the Tesla V100 has a lower search rate than the 2080 TI considering that the V100 is meant to be a CUDA-optimized compute GPU, even though this isn’t an apples-to-apples comparison because the 2080 Ti was searching for both types of keys. I’ll keep that in mind when I rent GPUs.

Is there a ready built version available somewhere? Win 64bit

Yep, here are the Windows binaries for v0.31: https://github.com/brichard19/BitCrack/releases/tag/0.31
member
Activity: 348
Merit: 34
benchmark


  • GeForce GT 640 = 9.11 MKeys/s
  • GeForce GTX 1060 3GB = compressed = 60.61 MKeys/s
  • GeForce GTX 1060 3GB = both = 46.93 MKeys/s
  • GeForce GTX 1070  = compressed = 109 MKeys/s
  • GeForce GTX 1070  = compressed = 85 MKeys/s (with 40k targets)
  • GeForce GTX 1070 TI = compressed = 80 MKeys/s (with 87k targets)
  • GeForce GTX 1080 TI = compressed = 1030 MKeys/s (with 40k targets)
  • GeForce GTX 1080 TI = compressed = 350.28 MKeys/s (-b 224 -t 128 -p 1024)
  • GeForce GTX 1080 TI = compressed = 350.28 MKeys/s
  • GeForce GTX 2070 TI = compressed = 805 MKeys/s (with 200 targets)
  • GeForce RXT 2080 TI = both = 631.57 MKeys/s
  • GeForce RXT 2080 XC ULTRA EVGA = both = 174.92 MKeys/s (with 40k targets) -b 42 -t 512 -p 2500
  • GeForce GTX 1050 TI = 64 MKeys/s (with 81 targets)
  • Tesla K80 = compressed = 39.76 MKeys/s
  • Tesla K80 = compressed = 68.21 MKeys/s (config)
  • Tesla P100 = compressed = 76 MKeys/s
  • Tesla P100 = compressed = 251 MKeys/s (config)
  • Tesla V100 = compressed = 174 MKeys/s
  • Tesla V100 = compressed = 603 MKeys/s (with 40k targets)  (config)
  • Tesla V100 = compressed = 715 MKeys/s (with 40k targets)  (config = -b 72 -t 512 -p 1024) =
















./cuBitCrack -b 7 -t 512 -p 1156 16jY7qLJnxb7CHZyqBP8qca9d51gAjyXQN -o new2020.txt-c --keyspace 8000000000000000:fffffffffffffffe  --stride xxxxxxx
[2020-11-06.13:53:49] [Info] Compression: compressed
[2020-11-06.13:53:49] [Info] Starting at: 0000000000000000000000000000000000000000000000008000000000000000
[2020-11-06.13:53:49] [Info] Ending at:   000000000000000000000000000000000000000000000000FFFFFFFFFFFFFFFE
[2020-11-06.13:53:49] [Info] Counting by: 00000000000000000000000000000000000000000000000000000000024C538B
[2020-11-06.13:53:49] [Info] Initializing GeForce GTX 460
[2020-11-06.13:53:49] [Info] Generating 4,143,104 starting points (158.0MB)
[2020-11-06.13:53:51] [Info] 10.0%
[2020-11-06.13:53:52] [Info] 20.0%
[2020-11-06.13:53:52] [Info] 30.0%
[2020-11-06.13:53:53] [Info] 40.0%
[2020-11-06.13:53:53] [Info] 50.0%
[2020-11-06.13:53:53] [Info] 60.0%
[2020-11-06.13:53:53] [Info] 70.0%
[2020-11-06.13:53:53] [Info] 80.0%
[2020-11-06.13:53:54] [Info] 90.0%
[2020-11-06.13:53:54] [Info] 100.0%
[2020-11-06.13:53:54] [Info] Done
GeForce GTX 460  408/964MB | 1 target 44.79 MKey/s (239,139,962,880 total) [01:28:55][2020-11-06.15:22:54] [Info] Reached end of keyspace

load of 20m addresses for compressed check its take 33.92Mkey/s
-b -p -t are too much important for design full speed gpu
sr. member
Activity: 661
Merit: 250
Really low numbers for 1070.
jr. member
Activity: 32
Merit: 11
benchmark


  • GeForce GT 640 = 9.11 MKeys/s
  • GeForce GTX 1060 3GB = compressed = 60.61 MKeys/s
  • GeForce GTX 1060 3GB = both = 46.93 MKeys/s
  • GeForce GTX 1070  = compressed = 109 MKeys/s
  • GeForce GTX 1070  = compressed = 85 MKeys/s (with 40k targets)
  • GeForce GTX 1070 TI = compressed = 80 MKeys/s (with 87k targets)
  • GeForce GTX 1080 TI = compressed = 1030 MKeys/s (with 40k targets)
  • GeForce GTX 1080 TI = compressed = 350.28 MKeys/s (-b 224 -t 128 -p 1024)
  • GeForce GTX 1080 TI = compressed = 350.28 MKeys/s
  • GeForce GTX 2070 TI = compressed = 805 MKeys/s (with 200 targets)
  • GeForce RXT 2080 TI = both = 631.57 MKeys/s
  • GeForce RXT 2080 XC ULTRA EVGA = both = 174.92 MKeys/s (with 40k targets) -b 42 -t 512 -p 2500
  • GeForce GTX 1050 TI = 64 MKeys/s (with 81 targets)
  • Tesla K80 = compressed = 39.76 MKeys/s
  • Tesla K80 = compressed = 68.21 MKeys/s (config)
  • Tesla P100 = compressed = 76 MKeys/s
  • Tesla P100 = compressed = 251 MKeys/s (config)
  • Tesla V100 = compressed = 174 MKeys/s
  • Tesla V100 = compressed = 603 MKeys/s (with 40k targets)  (config)
  • Tesla V100 = compressed = 715 MKeys/s (with 40k targets)  (config = -b 72 -t 512 -p 1024) =














legendary
Activity: 3472
Merit: 10611
AFAIK it was already discussed several times - miners are not a good devices for hash cracking.
there is a big difference between cracking password (hash) and finding a private key of a given address (which is what BitCrack tries to do).
finding a hash of a password is very similar to finding the hash of a block (aka mining) and ASICs should be excellent in it (not bitcoin ASICs used in bitcoin mining but an ASIC devices designed to do this). but it still is going to be a lot more  complicated and possible impossible to do the later (finding the private key) using ASICs since it involves elliptic curve cryptography.
legendary
Activity: 952
Merit: 1385
BitCrack should be ported for ASIC miners. That will change the game.

AFAIK it was already discussed several times - miners are not a good devices for hash cracking.

https://rya.nc/asic-cracking.html
legendary
Activity: 959
Merit: 1037
BitCrack should be ported for ASIC miners. That will change the game.
sr. member
Activity: 443
Merit: 350
So what is the benchmark speed with 3090 card?
newbie
Activity: 9
Merit: 0
3090 on vanitygen, clBitCrack and VanitySearch works. cuBitCrack was never able to start. gives an error message

Code:
ID:          0
Name:        GeForce RTX 3090
Capability:  8.6
MP:          82
Cores:       656 (8 per MP)
Memory:      24576MB
https://i.ibb.co/MR8WV0J/55.png
legendary
Activity: 2618
Merit: 1504
If you can, I'm interested in stats for prefix lengths between 4 and 10, legacy address format. Can you show me screenshots of those too, using all your cores (just for the heck of it) and the 3090? I'd do this myself but I don't have a recent NVIDIA GPU to test with.

Sorry friend, I pointed out that these are not my screenshots RTX3090 they came across me in the tlegram channel, someone shared, I unfortunately only RTX2080Ti, I think in the very near future there will be other details about the working settings and performance of RTX3090. Smiley
legendary
Activity: 1568
Merit: 6660
bitcoincleanup.com / bitmixlist.org
Has anyone managed to run cuBitCrack on 30XX?

I can't say about the work of RTX30XX in cuBitCrack came across screenshots as far as you can tell from them this is 6 RTX3090 cards working in vanitygen, can someone correct me. Where can I see that the RTX3090 is about 70% more productive than the RTX2080Ti. but whether you can trust these screenshots I can't say.



Interesting key rate of 19.63721 Gigakeys/second you have there with that 3090, your 40 cores only contribute ~150 Mkeys/second so they're no good for large prefix lengths. But even with your GPU it's still going to reach 50% of the space in 11 years so what's the length of the prefix you're searching for? It'll help me gauge how much computing power I'd need to put in to compute private keys of different prefix lengths in a single day.

If you can, I'm interested in stats for prefix lengths between 4 and 10, legacy address format. Can you show me screenshots of those too, using all your cores (just for the heck of it) and the 3090? I'd do this myself but I don't have a recent NVIDIA GPU to test with.
legendary
Activity: 2618
Merit: 1504
Has anyone managed to run cuBitCrack on 30XX?

I can't say about the work of RTX30XX in cuBitCrack came across screenshots as far as you can tell from them this is 6 RTX3090 cards working in vanitygen, can someone correct me. Where can I see that the RTX3090 is about 70% more productive than the RTX2080Ti. but whether you can trust these screenshots I can't say.

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