Make tensorflow (and a bunch of ther things) use CUDA-compatible toolchain. Introduces cudaPackages.backendStdenv
72 lines
1.8 KiB
Nix
72 lines
1.8 KiB
Nix
{ lib, backendStdenv, fetchFromGitHub
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, cmake, addOpenGLRunpath
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, cudatoolkit
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, cutensor
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}:
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let
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rev = "5aab680905d853bce0dbad4c488e4f7e9f7b2302";
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src = fetchFromGitHub {
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owner = "NVIDIA";
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repo = "CUDALibrarySamples";
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inherit rev;
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sha256 = "0gwgbkq05ygrfgg5hk07lmap7n7ampxv0ha1axrv8qb748ph81xs";
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};
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commonAttrs = {
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version = lib.strings.substring 0 7 rev + "-" + lib.versions.majorMinor cudatoolkit.version;
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nativeBuildInputs = [ cmake addOpenGLRunpath ];
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buildInputs = [ cudatoolkit ];
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postFixup = ''
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for exe in $out/bin/*; do
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addOpenGLRunpath $exe
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done
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'';
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meta = {
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description = "examples of using libraries using CUDA";
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longDescription = ''
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CUDA Library Samples contains examples demonstrating the use of
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features in the math and image processing libraries cuBLAS, cuTENSOR,
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cuSPARSE, cuSOLVER, cuFFT, cuRAND, NPP and nvJPEG.
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'';
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license = lib.licenses.bsd3;
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maintainers = with lib.maintainers; [ obsidian-systems-maintenance ];
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};
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};
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in
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{
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cublas = backendStdenv.mkDerivation (commonAttrs // {
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pname = "cuda-library-samples-cublas";
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src = "${src}/cuBLASLt";
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});
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cusolver = backendStdenv.mkDerivation (commonAttrs // {
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pname = "cuda-library-samples-cusolver";
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src = "${src}/cuSOLVER";
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sourceRoot = "cuSOLVER/gesv";
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});
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cutensor = backendStdenv.mkDerivation (commonAttrs // {
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pname = "cuda-library-samples-cutensor";
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src = "${src}/cuTENSOR";
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buildInputs = [ cutensor ];
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cmakeFlags = [
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"-DCUTENSOR_EXAMPLE_BINARY_INSTALL_DIR=${builtins.placeholder "out"}/bin"
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];
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# CUTENSOR_ROOT is double escaped
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postPatch = ''
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substituteInPlace CMakeLists.txt \
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--replace "\''${CUTENSOR_ROOT}/include" "${cutensor.dev}/include"
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'';
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CUTENSOR_ROOT = cutensor;
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});
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}
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