Build instructions:

Dependencies:

• Boost 1.54+

Windows:

Windows builds made by us are available here: https://github.com/crypticcoinvip/nheqminer/releases

Download and install:

• CUDA SDK (if not needed remove USE_CUDA_TROMP and USE_CUDA_DJEZO from nheqminer Preprocessor definitions under Properties > C/C++ > Preprocessor)
• Visual Studio 2015 Community
• boost 1.62: https://boost.teeks99.com/bin/1.62.0/
• 64 bit version only

Open nheqminer.sln under nheqminer/nheqminer.sln and build. You will have to build Release cuda_djezo project, then select Release and build nheqminer.

Enabled solvers:

• USE_CUDA_DJEZO

If you don't wan't to build with all solvers you can go to nheqminer Properties > C/C++ > Preprocessor > Preprocessor Definitions and remove the solver you don't need.

Linux

Work in progress.

Working solvers: CPU_TROMP, CUDA_TROMP, CUDA_DJEZO

Linux (Ubuntu 14.04 / 16.04) Build CPU_TROMP:

• Open terminal and run the following commands:
  • sudo apt-get install cmake build-essential libboost-all-dev
  • git clone https://github.com/crypticcoinvip/nheqminer.git
  • cd nheqminer
  • cmake -DUSE_CPU_XENONCAT=OFF -DUSE_CUDA_TROMP=OFF -DUSE_CPU_TROMP=ON -DUSE_CUDA_DJEZO=OFF .
  • make -j $(nproc)

Linux (Ubuntu 14.04 / 16.04) Build CUDA_DJEZO:

• Open terminal and run the following commands:
  • Ubuntu 14.04:
    • wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/cuda-repo-ubuntu1404_8.0.44-1_amd64.deb
    • sudo dpkg -i cuda-repo-ubuntu1404_8.0.44-1_amd64.deb
  • Ubuntu 16.04:
    • wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_8.0.44-1_amd64.deb
    • sudo dpkg -i cuda-repo-ubuntu1604_8.0.44-1_amd64.deb
  • sudo apt-get update
  • sudo apt-get install cuda
  • sudo apt-get install cuda-toolkit-8-0
  • sudo apt-get install cmake build-essential libboost-all-dev
  • git clone https://github.com/crypticcoinvip/nheqminer.git
  • cd nheqminer && CUDA_CUDART_LIBRARY="/usr/local/cuda/lib64/libcudart.so" && cmake -DUSE_CPU_XENONCAT=OFF -DUSE_CUDA_TROMP=OFF -DUSE_CPU_TROMP=ON -DUSE_CUDA_DJEZO=ON -DCMAKE_BUILD_TYPE=Release -DCUDA_CUDART_LIBRARY=CUDA_CUDART_LIBRARY . && make -j $(nproc)
  • If your GPU compute capability isn't supported by default, specify it explicitly (for example 80) like so cd nheqminer && CUDA_CUDART_LIBRARY="/usr/local/cuda/lib64/libcudart.so" && cmake COMPUTE=80 -DUSE_CPU_XENONCAT=OFF -DUSE_CUDA_TROMP=OFF -DUSE_CPU_TROMP=ON -DUSE_CUDA_DJEZO=ON -DCMAKE_BUILD_TYPE=Release -DCUDA_CUDART_LIBRARY=CUDA_CUDART_LIBRARY . && make -j $(nproc)

Run instructions:

Parameters: -h Print this help and quit -l [location] Stratum server:port -u [username] Username (bitcoinaddress) -a [port] Local API port (default: 0 = do not bind) -d [level] Debug print level (0 = print all, 5 = fatal only, default: 2) -b [hashes] Run in benchmark mode (default: 200 iterations)

CPU settings -t [num_thrds] Number of CPU threads -e [ext] Solver to use (0 = SSE2 tromp, 1 = AVX tromp, 2 = AVX2 xenoncat)

NVIDIA CUDA settings -ci CUDA info
-cv Solver to use (0 = GPU-djezo, 1 = GPU-tromp) -cd [devices] Enable CUDA mining on spec. devices -cb [blocks] Number of blocks -ct [tpb] Number of threads per block Example: -cd 0 2 -cb 12 16 -ct 64 128

If run without parameters, miner will start mining with 75% of available logical CPU cores. Use parameter -h to learn about available parameters:

Example to run benchmark on your CPU:

    nheqminer -b

Example to mine on your CPU AVX1 with your own CrypticCoin address and worker1 on CrypticPool server, using 4 threads (make sure your executable contains CPU-tromp solver):

    nheqminer -l crypticpool.com:44444 -u YOUR_CRYPTICCOIN_ADDRESS_HERE.worker1 -e 1 -t 4

Example to mine on your GPU with your own CrypticCoin address and worker3 on CrypticPool server, using 8 threads (make sure your executable contains GPU-djezo solver):

    nheqminer -l crypticpool.com:55555 -u YOUR_CRYPTICCOIN_ADDRESS_HERE.worker3 -cv 0 -cd 0

Note: if you have a 4-core CPU with hyper threading enabled (total 8 threads) it is best to run with only 6 threads (experimental benchmarks shows that best results are achieved with 75% threads utilized)