7e47f3658e
GitOrigin-RevId: 1925c603f17fc89f4c8f6bf6f631a802ad85d784
62 lines
1.3 KiB
Nix
62 lines
1.3 KiB
Nix
{ lib, stdenv, fetchFromGitHub, gfortran
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, python3, util-linux, which
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, enableStatic ? stdenv.hostPlatform.isStatic
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}:
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stdenv.mkDerivation rec {
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pname = "libxsmm";
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version = "1.17";
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src = fetchFromGitHub {
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owner = "libxsmm";
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repo = "libxsmm";
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rev = version;
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sha256 = "sha256-s/NEFU4IwQPLyPLwMmrrpMDd73q22Sk2BNid/kedawY=";
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};
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# Fixes /build references in the rpath
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patches = [ ./rpath.patch ];
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outputs = [ "out" "dev" "doc" ];
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nativeBuildInputs = [
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gfortran
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python3
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util-linux
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which
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];
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enableParallelBuilding = true;
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dontConfigure = true;
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makeFlags = let
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static = if enableStatic then "1" else "0";
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in [
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"OMP=1"
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"PREFIX=$(out)"
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"STATIC=${static}"
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];
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postInstall = ''
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mkdir -p $dev/lib/pkgconfig
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mv $out/lib/*.pc $dev/lib/pkgconfig
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moveToOutput "share/libxsmm" ''${!outputDoc}
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'';
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prePatch = ''
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patchShebangs .
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'';
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meta = with lib; {
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broken = (stdenv.hostPlatform.isLinux && stdenv.hostPlatform.isAarch64);
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description = "Library targeting Intel Architecture for specialized dense and sparse matrix operations, and deep learning primitives";
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mainProgram = "libxsmm_gemm_generator";
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license = licenses.bsd3;
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homepage = "https://github.com/hfp/libxsmm";
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platforms = platforms.linux;
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maintainers = with lib.maintainers; [ chessai ];
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};
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}
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