xmr-stak/doc/compile_Windows.md

Compile xmr-stak for Windows

Install Dependencies

Preparation

• Open a command line (Windows key + r) and enter cmd
• Execute mkdir C:\xmr-stak-dep

Visual Studio Community 2017

• Download and install Visual Studio Community 2017
• During install choose following components:
  • Desktop development with C++ (left side)
  • VC++ 2015.3 v140 toolset for desktop (right side - NOT needed for CUDA 9 or AMD GPU)
  • Since release of VS2017 15.5 (12/04/17), require VC++ 2017 version 15.4 v14.11 toolset (under tab Individual Components, section Compilers, build tools, and runtimes), as CUDA 9.1 is not compatible with compiler 14.12.X

CMake for Win64

• Download and install latest version from https://cmake.org/download/
• Tested version: cmake 3.9
• During install choose option: Add CMake to the system PATH for all users

Cuda 8.0+ (only needed for NVIDIA GPUs)

• Download and install https://developer.nvidia.com/cuda-downloads
• For minimal install choose Custom installation options during the install and select
  • CUDA/Development
  • CUDA/Visual Studio Integration (ignore the warning during the install that VS2017 is not supported)
  • CUDA/Runtime
  • Driver components

AMD APP SDK 3.0 (only needed for AMD GPUs)

• Download and install the latest version from http://developer.amd.com/amd-accelerated-parallel-processing-app-sdk/

Dependencies OpenSSL/Hwloc and Microhttpd

• For CUDA 8*:
  • Download version 1 of the precompiled binary from https://github.com/fireice-uk/xmr-stak-dep/releases/download/v1/xmr-stak-dep.zip
  • Version 1 of the pre-compiled dependencies is not compatible with Visual Studio Toolset v141
• For CUDA 9* and/or AMD GPUs, CPU:
  • Download version 2 of the precompiled binary from https://github.com/fireice-uk/xmr-stak-dep/releases/download/v2/xmr-stak-dep.zip
  • Version 2 of the pre-compiled dependencies is not compatible with Visual Studio Toolset v140
• Extract archive to C:\xmr-stak-dep

Validate the Dependency Folder

• Open a command line (Windows key + r) and enter cmd
• Execute

  cd c:\xmr-stak-dep
  tree .
  

• You should see something like this:

    C:\xmr-stak-dep>tree .
    Folder PATH listing for volume Windows
    Volume serial number is XX02-XXXX
    C:\XMR-STAK-DEP
    ├───hwloc
    │   ├───include
    │   │   ├───hwloc
    │   │   │   └───autogen
    │   │   └───private
    │   │       └───autogen
    │   └───lib
    ├───libmicrohttpd
    │   ├───include
    │   └───lib
    └───openssl
        ├───bin
        ├───include
        │   └───openssl
        └───lib
  

Compile

• Download xmr-stak Source Code.zip and save to a location in your home folder (C:\Users\USERNAME)
• Extract Source Code.zip (e.g. to C:\Users\USERNAME\xmr-stak-<version>)
• Open a command line (Windows key + r) and enter cmd
• Go to extracted source code directory (e.g. cd C:\Users\USERNAME\xmr-stak-<version>)
• Execute the following commands (NOTE: path to Visual Studio Community 2017 can be different)

  # Execute next line only if compiling for Cuda 9.1 and using Visual Studio 2017 >= 15.5 (released 12/04/17)
  "C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\VC\Auxiliary\Build\vcvarsall.bat" x64 -vcvars_ver=14.11  
  
  "C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\Common7\Tools\VsMSBuildCmd.bat"
  

• Sometimes Windows will change the directory to C:\Users\USERNAME\source\ instead of C:\Users\USERNAME\xmr-stak-<version>\. If that's the case execute cd C:\Users\USERNAME\xmr-stak-<version> followed by:

  mkdir build
  
  cd build
  
  set CMAKE_PREFIX_PATH=C:\xmr-stak-dep\hwloc;C:\xmr-stak-dep\libmicrohttpd;C:\xmr-stak-dep\openssl
  

CMake

• See build options to enable or disable dependencies.
• For CUDA 8* execute: cmake -G "Visual Studio 15 2017 Win64" -T v140,host=x64 ..
• For CUDA 9* and/or AMD GPUs, CPU execute: cmake -G "Visual Studio 15 2017 Win64" -T v141,host=x64 ..
• Then execute

  cmake --build . --config Release --target install
  
  cd bin\Release
  
  copy C:\xmr-stak-dep\openssl\bin\* .
  

• Miner is by default compiled for NVIDIA GPUs (if CUDA is installed), AMD GPUs (if the AMD APP SDK is installed) and CPUs.