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# Copyright 2013-2023 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack.package import *
class Dbcsr(CMakePackage, CudaPackage, ROCmPackage):
"""Distributed Block Compressed Sparse Row matrix library."""
homepage = "https://github.com/cp2k/dbcsr"
git = "https://github.com/cp2k/dbcsr.git"
url = "https://github.com/cp2k/dbcsr/releases/download/v2.2.0/dbcsr-2.2.0.tar.gz"
list_url = "https://github.com/cp2k/dbcsr/releases"
maintainers("dev-zero", "mtaillefumier")
version("develop", branch="develop")
version("2.6.0", sha256="c67b02ff9abc7c1f529af446a9f01f3ef9e5b0574f220259128da8d5ca7e9dc6")
version("2.5.0", sha256="91fda9b2502e5d0a2a6cdd5a73ef096253cc7e75bd01ba5189a4726ad86aef08")
version("2.4.1", sha256="b3d5ae62ca582b72707a2c932e8074a4f2f61d61085d97bd374213c70b8dbdcf")
version("2.4.0", sha256="cf2b774328c9a30677501f49b79955841bd08915a7ca53c8533bfdf14a8f9bd4")
version("2.3.0", sha256="f750de586cffa66852b646f7f85eb831eeb64fa2d25ce50ed10e1df016dd3364")
version("2.2.0", sha256="245b0382ddc7b80f85af8288f75bd03d56ec51cdfb6968acb4931529b35173ec")
version("2.1.0", sha256="9e58fd998f224632f356e479d18b5032570d00d87b86736b6a6ac2d03f8d4b3c")
version("2.0.1", sha256="61d5531b661e1dab043353a1d67939ddcde3893d3dc7b0ab3d05074d448b485c")
variant("mpi", default=True, description="Compile with MPI")
variant("openmp", default=False, description="Build with OpenMP support")
variant("shared", default=True, description="Build shared library")
variant(
"smm",
default="libxsmm",
values=("libxsmm", "blas"),
description="Library for small matrix multiplications",
)
variant(
"cuda_arch_35_k20x",
default=False,
description=(
"CP2K (resp. DBCSR) has specific parameter sets for"
" different GPU models. Enable this when building"
" with cuda_arch=35 for a K20x instead of a K40"
),
)
variant("opencl", default=False, description="Enable OpenCL backend")
variant("mpi_f08", default=False, when="@2.6:", description="Use mpi F08 module")
depends_on("blas")
depends_on("lapack")
depends_on("mpi", when="+mpi")
depends_on("libxsmm@1.11:~header-only", when="smm=libxsmm")
depends_on("cmake@3.10:", type="build")
depends_on("cmake@3.12:", type="build", when="@2.1:")
depends_on("cmake@3.17:", type="build", when="@2.2:")
depends_on("cmake@3.22:", type="build", when="@2.3:")
depends_on("py-fypp", type="build")
depends_on("py-fypp@3.1:", type="build", when="@2.6:")
depends_on("pkgconfig", type="build")
depends_on("python@3.6:", type="build", when="+cuda")
depends_on("hipblas", when="+rocm")
depends_on("opencl", when="+opencl")
# We only support specific gpu archs for which we have parameter files
# for optimal kernels. Note that we don't override the parent class arch
# properties, since the parent class defines constraints for different archs
# Instead just mark all unsupported cuda archs as conflicting.
dbcsr_cuda_archs = ("35", "37", "60", "70", "80")
cuda_msg = "dbcsr only supports cuda_arch {0}".format(dbcsr_cuda_archs)
for arch in CudaPackage.cuda_arch_values:
if arch not in dbcsr_cuda_archs:
conflicts("+cuda", when="cuda_arch={0}".format(arch), msg=cuda_msg)
conflicts("+cuda", when="cuda_arch=none", msg=cuda_msg)
dbcsr_amdgpu_targets = {"gfx906", "gfx910", "gfx90a", "gfx90a:xnack-", "gfx90a:xnack+"}
amd_msg = "DBCSR only supports amdgpu_target {0}".format(dbcsr_amdgpu_targets)
for arch in ROCmPackage.amdgpu_targets:
if arch not in dbcsr_amdgpu_targets:
conflicts("+rocm", when="amdgpu_target={0}".format(arch), msg=amd_msg)
accel_msg = "CUDA, ROCm and OpenCL support are mutually exlusive"
conflicts("+cuda", when="+rocm", msg=accel_msg)
conflicts("+cuda", when="+opencl", msg=accel_msg)
conflicts("+rocm", when="+opencl", msg=accel_msg)
# Require openmp threading for OpenBLAS by making other options conflict
conflicts("^openblas threads=pthreads", when="+openmp")
conflicts("^openblas threads=none", when="+openmp")
conflicts("smm=blas", when="+opencl")
with when("+mpi"):
# When using mpich 4.1 or higher, mpi_f08 has to be used, otherwise:
# Error: Type mismatch in argument 'baseptr' at (1); passed TYPE(c_ptr)
# to INTEGER(8)
conflicts("^mpich@4.1:", when="@:2.5")
conflicts("~mpi_f08", when="^mpich@4.1:")
depends_on("mpich+fortran", when="^mpich")
generator("ninja")
depends_on("ninja@1.10:", type="build")
def cmake_args(self):
spec = self.spec
if "+cuda" in spec and len(spec.variants["cuda_arch"].value) > 1:
raise InstallError("dbcsr supports only one cuda_arch at a time")
if "+rocm" in spec and len(spec.variants["amdgpu_target"].value) > 1:
raise InstallError("DBCSR supports only one amdgpu_arch at a time")
args = [
"-DUSE_SMM=%s" % ("libxsmm" if "smm=libxsmm" in spec else "blas"),
self.define_from_variant("USE_MPI", "mpi"),
self.define_from_variant("USE_OPENMP", "openmp"),
# C API needs MPI
self.define_from_variant("WITH_C_API", "mpi"),
"-DBLAS_FOUND=true",
"-DBLAS_LIBRARIES=%s" % (spec["blas"].libs.joined(";")),
"-DLAPACK_FOUND=true",
"-DLAPACK_LIBRARIES=%s" % (spec["lapack"].libs.joined(";")),
self.define_from_variant("BUILD_SHARED_LIBS", "shared"),
]
# Switch necessary as a result of a bug.
if "@2.1:2.2" in spec:
args += ["-DBUILD_TESTING=ON"]
if self.spec.satisfies("+cuda"):
cuda_arch = self.spec.variants["cuda_arch"].value[0]
gpu_map = {"35": "K40", "37": "K80", "60": "P100", "70": "V100", "80": "A100"}
gpuver = gpu_map[cuda_arch]
if cuda_arch == "35" and self.spec.satisfies("+cuda_arch_35_k20x"):
gpuver = "K20X"
args += ["-DWITH_GPU=%s" % gpuver, "-DUSE_ACCEL=cuda"]
if self.spec.satisfies("+rocm"):
amd_arch = self.spec.variants["amdgpu_target"].value[0]
gpuver = {
"gfx906": "Mi50",
"gfx908": "Mi100",
"gfx90a": "Mi250",
"gfx90a:xnack-": "Mi250",
"gfx90a:xnack+": "Mi250",
}[amd_arch]
args += ["-DWITH_GPU={0}".format(gpuver), "-DUSE_ACCEL=hip"]
if self.spec.satisfies("+opencl"):
args += ["-DUSE_ACCEL=opencl"]
if self.spec.satisfies("+mpi_f08"):
args += ["-DUSE_MPI_F08=ON"]
return args
def check(self):
"""Override CMakePackage's check() to enforce seralized test runs
since they are already parallelized"""
with working_dir(self.build_directory):
self._if_ninja_target_execute("test", parallel=False)
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