Files
nixpkgs/pkgs/by-name/sp/spla/package.nix
Dark Steveneq 646b892680
Some checks failed
Periodic Merges (6h) / master → staging-nixos (push) Failing after 12m50s
Periodic Merges (6h) / master → staging-next (push) Failing after 12m54s
Periodic Merges (24h) / merge-base(master,staging) → haskell-updates (push) Failing after 11m54s
Periodic Merges (6h) / staging-next → staging (push) Failing after 12m13s
Periodic Merges (24h) / staging-next-25.05 → staging-25.05 (push) Failing after 13m24s
Periodic Merges (24h) / release-25.05 → staging-next-25.05 (push) Failing after 14m28s
push sheeet
2025-10-09 14:15:47 +02:00

89 lines
1.8 KiB
Nix

{
stdenv,
lib,
fetchFromGitHub,
cmake,
mpi,
blas,
gfortran,
llvmPackages,
cudaPackages,
rocmPackages,
config,
gpuBackend ? (
if config.cudaSupport then
"cuda"
else if config.rocmSupport then
"rocm"
else
"none"
),
}:
assert builtins.elem gpuBackend [
"none"
"cuda"
"rocm"
];
stdenv.mkDerivation rec {
pname = "spla";
version = "1.6.1";
src = fetchFromGitHub {
owner = "eth-cscs";
repo = "spla";
rev = "v${version}";
hash = "sha256-fNH1IOKV1Re8G7GH9Xfn3itR80eonTbEGKQRRD16/2k=";
};
outputs = [
"out"
"dev"
];
postPatch = ''
substituteInPlace src/gpu_util/gpu_blas_api.hpp \
--replace '#include <rocblas.h>' '#include <rocblas/rocblas.h>'
'';
nativeBuildInputs = [
cmake
gfortran
];
buildInputs = [
blas
mpi
]
++ lib.optional (gpuBackend == "cuda") cudaPackages.cudatoolkit
++ lib.optionals (gpuBackend == "rocm") [
rocmPackages.clr
rocmPackages.rocblas
]
++ lib.optional stdenv.hostPlatform.isDarwin llvmPackages.openmp;
cmakeFlags = [
"-DSPLA_OMP=ON"
"-DSPLA_FORTRAN=ON"
"-DSPLA_INSTALL=ON"
# Required due to broken CMake files
"-DCMAKE_INSTALL_LIBDIR=lib"
"-DCMAKE_INSTALL_INCLUDEDIR=include"
]
++ lib.optional (gpuBackend == "cuda") "-DSPLA_GPU_BACKEND=CUDA"
++ lib.optional (gpuBackend == "rocm") [ "-DSPLA_GPU_BACKEND=ROCM" ];
preFixup = ''
substituteInPlace $out/lib/cmake/SPLA/SPLASharedTargets-release.cmake \
--replace-fail "\''${_IMPORT_PREFIX}" "$out"
'';
meta = with lib; {
description = "Specialized Parallel Linear Algebra, providing distributed GEMM functionality for specific matrix distributions with optional GPU acceleration";
homepage = "https://github.com/eth-cscs/spla";
license = licenses.bsd3;
maintainers = [ maintainers.sheepforce ];
};
}