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samples of the Gpu Speed, #15
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Interesting request...Running this on Ubuntu 20.04 Curious, I am getting better compute performance from my Ryzen CPU as compared to an Nvidia RTX 2080ti using OpenCL?? There is something wrong here as my GPU under any other case whether its CUDA kernel or OpenCL, or the CPU using opencl, typically thoroughly smokes the CPU (non-opencl) in compute intensive tasks. As you will see that is not the case here. I am not sure but it would seem the dev needs to dive in and take a closer look. I am inserting below some copy/paste(s) to show performance of ./oclvan... vs. ./van...One possibility I thought it could be that a setting is below the compute max for my GPU which is 75 but that is only for CUDA kernel not opencl. Also using pocl opencl icd for AMD ryzen, yet, still non-opencl on the AMD Ryzen CPU is crushing the CPU. If I saw this behavior in other applications like bitcrack or btcrecover I would suspect an issue on my end, however, that is not the case...So, we can postulate that the opencl performance issue is on the dev side, unless there is some configuration specifically for this source or some compiler flags that need to be set or perhaps a different version of g++, as revisions of openssl among other things I have noticed in other sources can significantly affect performance but I have not had the time to really dive in and investigate this further, and it is showing a dramatic increase in performance for other sources in my current revisions of what is being used for openssl, g++, nvcc (for CUDA), etc... Any help from the developer on this would be advantageous as the performance difference between ./oclvan and ./van are substantial, in favor of ./van...by almost 30X the performance (which it should be the opposite)... For OpenCL using BOTH GPU && CPU: ./oclvan... ./oclvanitygen++ -F compressed -k -i 19y73CRa -o 19y73CRa.txt For AMD Ryzen CPU with threadcount set to 44 of 48: ./van... ./vanitygen++ -F compressed -k -i 19y73CRa -o 19y73CRa.txt -t 44 Some simple math: 15,220,0000 / 508,410 = 29.94 so approximately 30X faster than the opencl implementation. Typically its the other way around so the expected computational speed of the GPU && the CPU using 48 threads, should be somewhere between 500 MKeys/sec to 1 BKeys/sec. This is in line with the performance I get from bitcrack and other sources using opencl. For CUDA that smokes opencl, however, this source does not include a make for CUDA kernel, only opencl - perhaps a CUDA port of the source would be beneficial for the developer to offer... Output of clinfo: ┌──(Luv㉿To-Phuk-Hard)-[~] Platform Name Portable Computing Language Platform Name NVIDIA CUDA Platform Name Portable Computing Language NULL platform behavior ICD loader properties Hope this helps with the benchmarking analysis request you have posted... /Zap |
Difficulty: 873388193410 |
hi there 10gic,. need you here, JeanLucPons/VanitySearch#52 (comment) this one you said does 256-64 what is it doing, is it not doing 192 if substracted, or i see wrong, how can i use keyspace in here, with -Z all 0000's i get lost there, -with -l 64 it needs the -Z, but how many 0's i need. is that 64bits range only.? thanks again, "$((256-20)) is equal to 236 in bash. i got stuck with this one. |
Note that the private key start with
If we run As the private key up to 64 hex characters (256 binary), If you want to solve puzzle, you can just set |
ok great to get this part all cleared now, will close this one to. thanks guys, |
guys would really like to know what is your gpu speed,
or who is using it and what is you'r average speed, maybe screenshot,.
would like to get more juice out of this one, thanks a lot
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