rhminer v2.3

Principe et fonctionnement du minage de crypto-monnaies.
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falcomann
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Enregistré le : lun. 2 nov. 2020 01:55

lun. 9 nov. 2020 11:28

rhminer

RandomHash miner for the PascalCoin blockchain.
Support Intel/AMD 64 bit CPU and NVidia GPU.
Support stratum and solo mining
Works on Windows 7,10 and Ubuntu 18

Click to download

Mining with pool
To mine with pool you'll need PascalCoin address (local wallet or exchange).

Code : Tout sélectionner

Pool mining examples:

For exchange wallet :  rhminer.exe -cpu -cputhreads 8 -s pasc-eu1.nanopool.org:15555 -su YOUR_WALLET_ADDRESS.YOUR_PAYMENT_ID.YOUR_WORKER_NAME/YOUR_EMAIL -fo pasc-eu2.nanopool.org:15555 -fou YOUR_WALLET_ADDRESS.YOUR_PAYMENT_ID.YOUR_WORKER_NAME/YOUR_EMAIL -r 20 -v 2 -logfilename rhminer.log

For local wallet :  rhminer.exe -cpu -cputhreads 8 -s pasc-eu1.nanopool.org:15555 -su YOUR_WALLET_ADDRESS.0.YOUR_WORKER_NAME/YOUR_EMAIL -fo pasc-eu2.nanopool.org:15555 -fou YOUR_WALLET_ADDRESS.0.YOUR_WORKER_NAME/YOUR_EMAIL -r 20 -v 2 -logfilename rhminer.log
Supported Cuda architecture
  • Kepler GTX 700 series, Tesla K40/K80
  • Maxwell GTX 900 series, Quadro M series, GTX Titan X
  • Pascal GTX 1000 series, Titan Xp, Tesla P40, Tesla P4,GP100/Tesla P100 – DGX-1
  • Volta GTX 1100 series (GV104), Tesla V100
Gpu mining
To mine using gpu you must provide the gpu numbers and the amount of threads for each gpu.
If you only have one gpu, use -gpu 0 and -gputhreads {amount of threads}
If you have more than one gpus, you can see their number by executing the miner with the list option:

Code : Tout sélectionner

C:>rhminer -list 

  rhminer v0.9 beta for CPU and NVIDIA GPUs by polyminer1 (http://github.com/polyminer1)
  NVIDIA CUDA SDK 9.2

  Donations : Pascal account 529692-23
  Donations : Bitcoin address 19GfXGpRJfwcHPx2Nf8wHgMps8Eat1o4Jp

List of gpus and cpus:
GPU0 : GeForce GTX 1060 3GB
GPU1 : GeForce GTX 1060 3GB
GPU2 : GeForce GTX 950 2GB
CPU  : Intel(R) Core(TM) i5-4460 CPU @ 3.20GHz
Ideal CUDA threads count
To find the ideal maximum amount of threads, start with 75% of the memory divided by 8.8.
For a GTX 1060 3GB that is 3000 * 0.75 / 8.8 = 255 threads.
Then run 2 minutes and if everything is stable, raise by say 32 until you get no crashes after 2 min.
To help you in that process, look for the log line that say "CUDA: Using " when the miner starts. It will indicate how much memory you take and how much is left depending on your selected thread count.
ALLWAYS let at lease 150 meg of free memory, for internal OS operations, or you have stability issues.

Tested on
- CPU: I3, I5, Core2, Xeon, Athlon
- GPU: GTX 950, GTX 1060, GTX 1070
- CUDA: Linux CUDA 9.1, Windows CUDA 9.2

Upcoming
- CPU optimization using SSe4 and AVX
- Adding more stability to GPU mining
- GPU optimizations
- curl Api for stats and control
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