BitCrack - A tool for brute-forcing private keys

[WanderingPhilospher]

I have compiled cuBitCrack using CUDA 11.2, confirmed working on 2080, 2080ti, and 3070 without the multiplication issue preventing private keys from being found.

Can anyone help me create a windows binary?

https://github.com/yoyodapro/BitCrack/releases/tag/v11.2-alpha

What speed did you see with 3070?

Source code available on github, to compile for Windows?

3070 with 45 256 2096 - 1845Mkeys/s

Ive tried to make the same modifications to the VS project files and it wont compile for me.

Also i am not familiar enough with VS to begin with.

what code did you modify? I can create windows if you tell me what you modified...

[1713898273]

1713898273

[1713898273]

1713898273

[yoyodapro]

I have compiled cuBitCrack using CUDA 11.2, confirmed working on 2080, 2080ti, and 3070 without the multiplication issue preventing private keys from being found.

Can anyone help me create a windows binary?

https://github.com/yoyodapro/BitCrack/releases/tag/v11.2-alpha

What speed did you see with 3070?

Source code available on github, to compile for Windows?

3070 with 45 256 2096 - 1845Mkeys/s

Ive tried to make the same modifications to the VS project files and it wont compile for me.

Also i am not familiar enough with VS to begin with.

what code did you modify? I can create windows if you tell me what you modified...

I changed in the makefile

# CUDA variables
COMPUTE_CAP=75
NVCC=nvcc
NVCCFLAGS=-std=c++11 -gencode=arch=compute_${COMPUTE_CAP},code=\"sm_${COMPUTE_CAP}\" -Xptxas="-v" -Xcompiler "${CXXFLAGS}"
CUDA_HOME=/usr/local/cuda-11.2
CUDA_LIB=${CUDA_HOME}/lib64
CUDA_INCLUDE=${CUDA_HOME}/include
CUDA_MATH=$(CUR_DIR)/cudaMath

# OpenCL variables
OPENCL_LIB=${CUDA_LIB}
OPENCL_INCLUDE=${CUDA_INCLUDE}
OPENCL_VERSION=112

Ive tried modifying the .props to change

Code:

<CUDA_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include</CUDA_INCLUDE>
	<CUDA_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\lib\x64</CUDA_LIB>
    <OPENCL_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include</OPENCL_INCLUDE>
    <OPENCL_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\lib\x64</OPENCL_LIB>

[/color]

to

Code:

<CUDA_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\include</CUDA_INCLUDE>
	<CUDA_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\lib\x64</CUDA_LIB>
    <OPENCL_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\include</OPENCL_INCLUDE>
    <OPENCL_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\lib\x64</OPENCL_LIB>

[/color]

Then building the CudaKeyFinder and KeyFinder in VS2019 (Release x64) but it will not work for me, I am most likely doing something wrong.


P.S. When running on linux the most up to date cuda drivers had no problems running on my 2080, 2080ti, and 3070. there is most likely just a problem with the last release and the compute capability with cuBitCrack from brichard19.

[NotATether]

-o or --out for output file?

Also, does anyone know what message is displayed or what happens if a private key is found?

It's activated with either -o or --out.

When it finds a private key it prints "Found key for address XYZ. Written to OUTPUTFILE", then in the output file it writes the address, private key in hex and compressed public key separated by space, all in one line. It looks like if you don't pass one of them, you will not get private keys printed at all.

Ive tried modifying the .props to change

Code:

<CUDA_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include</CUDA_INCLUDE>
	<CUDA_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\lib\x64</CUDA_LIB>
    <OPENCL_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include</OPENCL_INCLUDE>
    <OPENCL_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\lib\x64</OPENCL_LIB>

[/color]

to

Code:

<CUDA_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\include</CUDA_INCLUDE>
	<CUDA_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\lib\x64</CUDA_LIB>
    <OPENCL_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\include</OPENCL_INCLUDE>
    <OPENCL_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\lib\x64</OPENCL_LIB>

[/color]

Then building the CudaKeyFinder and KeyFinder in VS2019 (Release x64) but it will not work for me, I am most likely doing something wrong.


P.S. When running on linux the most up to date cuda drivers had no problems running on my 2080, 2080ti, and 3070. there is most likely just a problem with the last release and the compute capability with cuBitCrack from brichard19.

VS doesn't read the Makefiles when it complies the Windows version so the things in the Props file and each .vcxproj are the only things it reads.

Did you check to see if the path to CUDA 11.2 is called C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2? Also paste the errors from the VS build window here, it'll be helpful to know what's going on.

[zahid888]

I have compiled cuBitCrack using CUDA 11.2, confirmed working on 2080, 2080ti, and 3070 without the multiplication issue preventing private keys from being found.

Can anyone help me create a windows binary?

https://github.com/yoyodapro/BitCrack/releases/tag/v11.2-alpha

What speed did you see with 3070?

Source code available on github, to compile for Windows?

3070 with 45 256 2096 - 1845Mkeys/s

Ive tried to make the same modifications to the VS project files and it wont compile for me.

Also i am not familiar enough with VS to begin with.

what code did you modify? I can create windows if you tell me what you modified...

Excellent work guys.. now waiting for windows version for my 3060TI

[zahid888]

I have compiled cuBitCrack using CUDA 11.2, confirmed working on 2080, 2080ti, and 3070 without the multiplication issue preventing private keys from being found.

Can anyone help me create a windows binary?

https://github.com/yoyodapro/BitCrack/releases/tag/v11.2-alpha

cuBitCrack.exe is not compatible with the version of Windows you're running. Check your computer's system information and then contact the software publisher.

[yoyodapro]

I have compiled cuBitCrack using CUDA 11.2, confirmed working on 2080, 2080ti, and 3070 without the multiplication issue preventing private keys from being found.

Can anyone help me create a windows binary?

https[Suspicious link removed] is not compatible with the version of Windows you're running. Check your computer's system information and then contact the software publisher.

the code isnt ready yet, its only confirmed working on WSL - Ubuntu 20.14

[Noname400]

good evening to all enthusiasts.
I found many versions and modifications of this project. In addition to the original branch from the respected brichard19, I found a branch with a random search. Should I use it? the better or worse it is.
in the original branch, everything is simple (start + step + step + N step)
random points are generated in the branch. but I don’t understand after the generation, the search proceeds further by random choice or also (random point + step + step + N step)

[NotATether]

good evening to all enthusiasts.
I found many versions and modifications of this project. In addition to the original branch from the respected brichard19, I found a branch with a random search. Should I use it? the better or worse it is.
in the original branch, everything is simple (start + step + step + N step)
random points are generated in the branch. but I don’t understand after the generation, the search proceeds further by random choice or also (random point + step + step + N step)

Are you talking about the points being chosen by an RNG? I am not totally sure how long does the process of generating random numbers takes because I haven't measured it, but I'd say it could take a noticeable percentage of the time it takes to check a private key.

I still feel like pregenerating a bunch of keyspace ranges beforehand and passing those to bitcrack serially is a better approach at randomization than generating a random number 2^X times per second (X is an arbitrary number proportional to the speed of your GPU).

Anyway it would be nice if you linked that version of Bitcrack you're talking about so we can take a look at it's commit history to see what it changed.

[brainless]

I have compiled cuBitCrack using CUDA 11.2, confirmed working on 2080, 2080ti, and 3070 without the multiplication issue preventing private keys from being found.

Can anyone help me create a windows binary?

https://github.com/yoyodapro/BitCrack/releases/tag/v11.2-alpha

What speed did you see with 3070?

Source code available on github, to compile for Windows?

3070 with 45 256 2096 - 1845Mkeys/s

Ive tried to make the same modifications to the VS project files and it wont compile for me.

Also i am not familiar enough with VS to begin with.

what code did you modify? I can create windows if you tell me what you modified...

I changed in the makefile

# CUDA variables
COMPUTE_CAP=75
NVCC=nvcc
NVCCFLAGS=-std=c++11 -gencode=arch=compute_${COMPUTE_CAP},code=\"sm_${COMPUTE_CAP}\" -Xptxas="-v" -Xcompiler "${CXXFLAGS}"
CUDA_HOME=/usr/local/cuda-11.2
CUDA_LIB=${CUDA_HOME}/lib64
CUDA_INCLUDE=${CUDA_HOME}/include
CUDA_MATH=$(CUR_DIR)/cudaMath

# OpenCL variables
OPENCL_LIB=${CUDA_LIB}
OPENCL_INCLUDE=${CUDA_INCLUDE}
OPENCL_VERSION=112

Ive tried modifying the .props to change

Code:

<CUDA_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include</CUDA_INCLUDE>
	<CUDA_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\lib\x64</CUDA_LIB>
    <OPENCL_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include</OPENCL_INCLUDE>
    <OPENCL_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\lib\x64</OPENCL_LIB>

[/color]

to

Code:

<CUDA_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\include</CUDA_INCLUDE>
	<CUDA_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\lib\x64</CUDA_LIB>
    <OPENCL_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\include</OPENCL_INCLUDE>
    <OPENCL_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\lib\x64</OPENCL_LIB>

[/color]

Then building the CudaKeyFinder and KeyFinder in VS2019 (Release x64) but it will not work for me, I am most likely doing something wrong.


P.S. When running on linux the most up to date cuda drivers had no problems running on my 2080, 2080ti, and 3070. there is most likely just a problem with the last release and the compute capability with cuBitCrack from brichard19.

correct your line
NVCCFLAGS=-std=c++11 -gencode=arch=compute_${COMPUTE_CAP},code=sm_${COMPUTE_CAP} -Xptxas="-v" -Xcompiler "${CXXFLAGS}"

[brainless]

I have compiled cuBitCrack using CUDA 11.2, confirmed working on 2080, 2080ti, and 3070 without the multiplication issue preventing private keys from being found.

Can anyone help me create a windows binary?

https://github.com/yoyodapro/BitCrack/releases/tag/v11.2-alpha

What speed did you see with 3070?

Source code available on github, to compile for Windows?

3070 with 45 256 2096 - 1845Mkeys/s

Ive tried to make the same modifications to the VS project files and it wont compile for me.

Also i am not familiar enough with VS to begin with.

what code did you modify? I can create windows if you tell me what you modified...

I changed in the makefile

# CUDA variables
COMPUTE_CAP=75
NVCC=nvcc
NVCCFLAGS=-std=c++11 -gencode=arch=compute_${COMPUTE_CAP},code=\"sm_${COMPUTE_CAP}\" -Xptxas="-v" -Xcompiler "${CXXFLAGS}"
CUDA_HOME=/usr/local/cuda-11.2
CUDA_LIB=${CUDA_HOME}/lib64
CUDA_INCLUDE=${CUDA_HOME}/include
CUDA_MATH=$(CUR_DIR)/cudaMath

# OpenCL variables
OPENCL_LIB=${CUDA_LIB}
OPENCL_INCLUDE=${CUDA_INCLUDE}
OPENCL_VERSION=112

Ive tried modifying the .props to change

Code:

<CUDA_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include</CUDA_INCLUDE>
	<CUDA_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\lib\x64</CUDA_LIB>
    <OPENCL_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include</OPENCL_INCLUDE>
    <OPENCL_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\lib\x64</OPENCL_LIB>

[/color]

to

Code:

<CUDA_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\include</CUDA_INCLUDE>
	<CUDA_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\lib\x64</CUDA_LIB>
    <OPENCL_INCLUDE>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\include</OPENCL_INCLUDE>
    <OPENCL_LIB>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\lib\x64</OPENCL_LIB>

[/color]

Then building the CudaKeyFinder and KeyFinder in VS2019 (Release x64) but it will not work for me, I am most likely doing something wrong.


P.S. When running on linux the most up to date cuda drivers had no problems running on my 2080, 2080ti, and 3070. there is most likely just a problem with the last release and the compute capability with cuBitCrack from brichard19.

here no only cuda ver problem, cuda 11 is ok, problem is about your gcc and g++ versions,
simple install other gcc and g++ ver from 4.8 to 8.0, ( version 4.8, 5.0, 5.4, 6, 7, 7.2,
and next dont fix default, simple install, and then change Makefile
# C++ options
CXX=g++
CXXFLAGS=-O2 -std=c++11

# CUDA variables
COMPUTE_CAP=30
NVCC=nvcc

now chnage only line CXX=g++  to  CXX=g++-4.8
and then run run Make cuda, if no error, then change
CXX=g++ to CXX=g++-5.0 and same run setup make
if error then try with next g++ ver like above commands, some where your program will isntall and run success
update here your works

[NotATether]

here no only cuda ver problem, cuda 11 is ok, problem is about your gcc and g++ versions,
simple install other gcc and g++ ver from 4.8 to 8.0, ( version 4.8, 5.0, 5.4, 6, 7, 7.2,
and next dont fix default, simple install, and then change Makefile

Just to correct you, CUDA 11 requires gcc 5 to compile. It's not going to work with gcc 4.8. https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#system-requirements (see note 2)

If you use the CUDA installer for Linux it automatically installs a supported gcc for itself to use anyway.

If you're compiling on a newer Linux distro you already have a newer gcc anyway. I haven't (yet) seen a case of a newer C/C++ program compiling on an old gcc but not a newer one.

[WanderingPhilospher]

good evening to all enthusiasts.
I found many versions and modifications of this project. In addition to the original branch from the respected brichard19, I found a branch with a random search. Should I use it? the better or worse it is.
in the original branch, everything is simple (start + step + step + N step)
random points are generated in the branch. but I don’t understand after the generation, the search proceeds further by random choice or also (random point + step + step + N step)

Are you talking about the points being chosen by an RNG? I am not totally sure how long does the process of generating random numbers takes because I haven't measured it, but I'd say it could take a noticeable percentage of the time it takes to check a private key.

I still feel like pregenerating a bunch of keyspace ranges beforehand and passing those to bitcrack serially is a better approach at randomization than generating a random number 2^X times per second (X is an arbitrary number proportional to the speed of your GPU).

Anyway it would be nice if you linked that version of Bitcrack you're talking about so we can take a look at it's commit history to see what it changed.

He is probably talking about Pica's version with random feature. Many say it had some bugs in it. I neve used it.

My version generates millions of random starting points, in the bit range you desire, and then counts sequentially, from each of those random starting points. So if you only want to look in the 8F00000000000000 range, it will generate millions of starting points all starting with 8F, and then compute sequentially. It doesn't take long to generate the points, no longer than generating Kangaroos. It's fast at finding keys in any 2^48 range, but above that, It's better to just search sequentially starting with one key. IMO. So if we took #64 puzzle, and assigned people the front 2^16 range, example 8F00, and another person 8F01, and another person 8F02, etc. all the way to 8FFF, then we only need 256 people to check the 8F range quickly. Now, once that range is done, start with another one like 80, 81, 82, 83, C0, C1, etc.
Who's in?! lol 

[yoyodapro]

I have a program compiled for Bitcrack that acts as a proof of work server, it delegates random shares of the entire 2^64 bit range in 000000000-3ffffffff increments.

If anyone is interested I can post the windows binaries and we can pool our resources for a fair share of the .64 BTC depending on ranges searched.

[brainless]

good evening to all enthusiasts.
I found many versions and modifications of this project. In addition to the original branch from the respected brichard19, I found a branch with a random search. Should I use it? the better or worse it is.
in the original branch, everything is simple (start + step + step + N step)
random points are generated in the branch. but I don’t understand after the generation, the search proceeds further by random choice or also (random point + step + step + N step)

Are you talking about the points being chosen by an RNG? I am not totally sure how long does the process of generating random numbers takes because I haven't measured it, but I'd say it could take a noticeable percentage of the time it takes to check a private key.

I still feel like pregenerating a bunch of keyspace ranges beforehand and passing those to bitcrack serially is a better approach at randomization than generating a random number 2^X times per second (X is an arbitrary number proportional to the speed of your GPU).

Anyway it would be nice if you linked that version of Bitcrack you're talking about so we can take a look at it's commit history to see what it changed.

He is probably talking about Pica's version with random feature. Many say it had some bugs in it. I neve used it.

My version generates millions of random starting points, in the bit range you desire, and then counts sequentially, from each of those random starting points. So if you only want to look in the 8F00000000000000 range, it will generate millions of starting points all starting with 8F, and then compute sequentially. It doesn't take long to generate the points, no longer than generating Kangaroos. It's fast at finding keys in any 2^48 range, but above that, It's better to just search sequentially starting with one key. IMO. So if we took #64 puzzle, and assigned people the front 2^16 range, example 8F00, and another person 8F01, and another person 8F02, etc. all the way to 8FFF, then we only need 256 people to check the 8F range quickly. Now, once that range is done, start with another one like 80, 81, 82, 83, C0, C1, etc.
Who's in?! lol  

we have talked before for bitcrack modification, you modified, you tested with me, and said you lost codes, and no plan to share with me and community, maybe you afraid, some one could pick 64 puzzle and other puzzle, maybe you have your own interest

[WanderingPhilospher]

good evening to all enthusiasts.
I found many versions and modifications of this project. In addition to the original branch from the respected brichard19, I found a branch with a random search. Should I use it? the better or worse it is.
in the original branch, everything is simple (start + step + step + N step)
random points are generated in the branch. but I don’t understand after the generation, the search proceeds further by random choice or also (random point + step + step + N step)

Are you talking about the points being chosen by an RNG? I am not totally sure how long does the process of generating random numbers takes because I haven't measured it, but I'd say it could take a noticeable percentage of the time it takes to check a private key.

I still feel like pregenerating a bunch of keyspace ranges beforehand and passing those to bitcrack serially is a better approach at randomization than generating a random number 2^X times per second (X is an arbitrary number proportional to the speed of your GPU).

Anyway it would be nice if you linked that version of Bitcrack you're talking about so we can take a look at it's commit history to see what it changed.

He is probably talking about Pica's version with random feature. Many say it had some bugs in it. I neve used it.

My version generates millions of random starting points, in the bit range you desire, and then counts sequentially, from each of those random starting points. So if you only want to look in the 8F00000000000000 range, it will generate millions of starting points all starting with 8F, and then compute sequentially. It doesn't take long to generate the points, no longer than generating Kangaroos. It's fast at finding keys in any 2^48 range, but above that, It's better to just search sequentially starting with one key. IMO. So if we took #64 puzzle, and assigned people the front 2^16 range, example 8F00, and another person 8F01, and another person 8F02, etc. all the way to 8FFF, then we only need 256 people to check the 8F range quickly. Now, once that range is done, start with another one like 80, 81, 82, 83, C0, C1, etc.
Who's in?! lol  

we have talked before for bitcrack modification, you modified, you tested with me, and said you lost codes, and no plan to share with me and community, maybe you afraid, some one could pick 64 puzzle and other puzzle, maybe you have your own interest

brainless...that was for a different version, one that computes 1 key, jumps x amount, computes 1 key, jumps x amount, etc.
Did we ever discuss a random one?

[JJJansen]

Very interesting, was looking for a tool like this.
Definitely going to give it a try.

[yoyodapro]

Ive successfully compiled a release for Windows that utilizes Cuda 11.2.

https://github.com/yoyodapro/BitCrack/releases/tag/v11.2-beta

Ive compiled cuBitCrack.exe and clBitCrack.exe using 11.2 targets. clBitCrack confirmed working using -t 128 -b 256 -p 1024, if anyone could provide the recommended settings for these cards it would be greatly appreciated! cuBitCrack still not working for 20** and 30** series cards, hoping someone can help me figure it out 

[2021-01-13.23:39:32] [Info] Compression: compressed
[2021-01-13.23:39:32] [Info] Starting at: 0000000000000000000000000000000000000000000000008000000000000001
[2021-01-13.23:39:32] [Info] Ending at:   000000000000000000000000000000000000000000000000FFFFFFFFFFFFFFFF
[2021-01-13.23:39:32] [Info] Counting by: 0000000000000000000000000000000000000000000000000000000000000002
[2021-01-13.23:39:32] [Info] Compiling OpenCL kernels...
[2021-01-13.23:39:45] [Info] Initializing GeForce RTX 3070
[2021-01-13.23:39:49] [Info] Generating 33,554,432 starting points (1280.0MB)
[2021-01-13.23:39:51] [Info] 10.0%
[2021-01-13.23:39:52] [Info] 20.0%
[2021-01-13.23:39:52] [Info] 30.0%
[2021-01-13.23:39:52] [Info] 40.0%
[2021-01-13.23:39:52] [Info] 50.0%
[2021-01-13.23:39:52] [Info] 60.0%
[2021-01-13.23:39:52] [Info] 70.0%
[2021-01-13.23:39:52] [Info] 80.0%
[2021-01-13.23:39:53] [Info] 90.0%
[2021-01-13.23:39:53] [Info] 100.0%
[2021-01-13.23:39:53] [Info] Done
GeForce RTX 3070 3072 / 8192MB | 1 target 936.15 MKey/s (40,802,189,312 total) [00:00:38][2021-01-13.23:40:33]

[2021-01-13.23:39:32] [Info] Compression: compressed
[2021-01-13.23:39:32] [Info] Starting at: 0000000000000000000000000000000000000000000000008000000000000000
[2021-01-13.23:39:32] [Info] Ending at:   000000000000000000000000000000000000000000000000FFFFFFFFFFFFFFFF
[2021-01-13.23:39:32] [Info] Counting by: 0000000000000000000000000000000000000000000000000000000000000002
[2021-01-13.23:39:32] [Info] Compiling OpenCL kernels...
[2021-01-13.23:39:32] [Info] Initializing GeForce RTX 2080
[2021-01-13.23:39:35] [Info] Generating 33,554,432 starting points (1280.0MB)
[2021-01-13.23:39:38] [Info] 10.0%
[2021-01-13.23:39:38] [Info] 20.0%
[2021-01-13.23:39:39] [Info] 30.0%
[2021-01-13.23:39:39] [Info] 40.0%
[2021-01-13.23:39:39] [Info] 50.0%
[2021-01-13.23:39:39] [Info] 60.0%
[2021-01-13.23:39:39] [Info] 70.0%
[2021-01-13.23:39:39] [Info] 80.0%
[2021-01-13.23:39:39] [Info] 90.0%
[2021-01-13.23:39:40] [Info] 100.0%
[2021-01-13.23:39:40] [Info] Done
GeForce RTX 2080 3072 / 8192MB | 1 target 710.05 MKey/s (38,050,725,888 total) [00:00:51][2021-01-13.23:40:33]

[Noname400]

Very interesting, was looking for a tool like this.
Definitely going to give it a try.

https://github.com/djarumlights/BitCrack (rndom only CUDA)
https://github.com/neutron220/BitCrack (random all) low speed RX480 8gb 100m/s

[NotATether]

Ive successfully compiled a release for Windows that utilizes Cuda 11.2.

https://github.com/yoyodapro/BitCrack/releases/tag/v11.2-beta

Ive compiled cuBitCrack.exe and clBitCrack.exe using 11.2 targets. clBitCrack confirmed working using -t 128 -b 256 -p 1024, if anyone could provide the recommended settings for these cards it would be greatly appreciated! cuBitCrack still not working for 20** and 30** series cards, hoping someone can help me figure it out 

Awesome man, I'll send you a PM and see if I can get this thing working. Hopefully there is some kind of debugger bundled with the CUDA toolkit for Windows  I think it will make the problem more obvious than cuda-gdb.

I will update this post or just make a new one if I can find the optimal settings. Maybe someone can make bitcrack keep a list of GPUs known in advance and load optimal settings for them (preferably by means of some benchmarking program).

[zahid888]

Ive successfully compiled a release for Windows that utilizes Cuda 11.2.

https://github.com/yoyodapro/BitCrack/releases/tag/v11.2-beta