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seissol: new package (#41176)

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Co-authored-by: Bernhard Kaindl <bernhardkaindl7@gmail.com>
This commit is contained in:
Thomas-Ulrich 2024-10-24 14:36:37 +02:00 committed by GitHub
parent cdde7c3ccf
commit f09ce00fe1
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5 changed files with 414 additions and 1 deletions
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1
var/spack/repos/builtin/packages/easi/package.py
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@ -32,6 +32,7 @@ class Easi(CMakePackage):
variant("python", default=True, description="Install python bindings")
extends("python", when="+python")
depends_on("mpi", when="+python")
variant("asagi", default=True, description="build with ASAGI support")
variant(

6
var/spack/repos/builtin/packages/libxsmm/package.py
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@ -28,7 +28,11 @@ class Libxsmm(MakefilePackage):
version("main-2023-11", commit="0d9be905527ba575c14ca5d3b4c9673916c868b2")
version("main", branch="main")
version("1.17-cp2k", commit="6f883620f58afdeebab28039fc9cf580e76a5ec6")
version("1.17", sha256="8b642127880e92e8a75400125307724635ecdf4020ca4481e5efe7640451bb92")
version(
"1.17",
sha256="8b642127880e92e8a75400125307724635ecdf4020ca4481e5efe7640451bb92",
preferred=True,
)
version("1.16.3", sha256="e491ccadebc5cdcd1fc08b5b4509a0aba4e2c096f53d7880062a66b82a0baf84")
version("1.16.2", sha256="bdc7554b56b9e0a380fc9c7b4f4394b41be863344858bc633bc9c25835c4c64e")
version("1.16.1", sha256="93dc7a3ec40401988729ddb2c6ea2294911261f7e6cd979cf061b5c3691d729d")

30
var/spack/repos/builtin/packages/py-chainforgecodegen/package.py Normal file
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@ -0,0 +1,30 @@
# Copyright 2013-2024 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 PyChainforgecodegen(PythonPackage):
"""A code generator that fuses subsequent batched matrix multiplications (GEMMs)
into a single GPU kernel, holding intermediate results in shared memory as long as necessary.
"""
git = "https://github.com/SeisSol/chainforge.git"
maintainers("davschneller", "Thomas-Ulrich")
license("BSD-3-Clause")
version("master", branch="master")
depends_on("py-numpy")
depends_on("py-graphviz", type=("build", "run"))
depends_on("py-jinja2", type=("build", "run"))
depends_on("py-lark", type=("build", "run"))
depends_on("py-pyyaml", type=("build", "run"))
depends_on("py-setuptools", type="build")
def setup_run_environment(self, env):
env.prepend_path("PATH", self.spec.prefix)
env.prepend_path("PYTHONPATH", self.spec.prefix)

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var/spack/repos/builtin/packages/py-gemmforge/package.py Normal file
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@ -0,0 +1,27 @@
# Copyright 2013-2024 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 PyGemmforge(PythonPackage):
"""GPU-GEMM generator for the Discontinuous Galerkin method"""
homepage = "https://github.com/SeisSol/gemmforge/blob/master/README.md"
git = "https://github.com/SeisSol/gemmforge.git"
maintainers("davschneller", "Thomas-Ulrich")
license("BSD-3-Clause")
version("master", branch="master")
depends_on("py-numpy")
depends_on("py-jinja2", type=("build", "run"))
depends_on("py-pyyaml", type=("build", "run"))
depends_on("py-setuptools", type="build")
def setup_run_environment(self, env):
env.prepend_path("PATH", self.spec.prefix)
env.prepend_path("PYTHONPATH", self.spec.prefix)

351
var/spack/repos/builtin/packages/seissol/package.py Normal file
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@ -0,0 +1,351 @@
# Copyright 2013-2024 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 Seissol(CMakePackage, CudaPackage, ROCmPackage):
"""Seissol - A scientific software for the numerical simulation
of seismic wave phenomena and earthquake dynamics.
"""
homepage = "http://www.seissol.org"
git = "https://github.com/SeisSol/SeisSol.git"
version("master", branch="master", submodules=True)
# we cannot use the tar.gz file because it does not contains submodules
version(
"1.2.0", tag="v1.2.0", commit="2057e6e81965e0789128c6d177592800bcf956e1", submodules=True
)
version(
"1.1.4", tag="v1.1.4", commit="6d301757378ad8446173e0a12c095a695a708aaf", submodules=True
)
version(
"1.1.3", tag="v1.1.3", commit="01ae1b127fcc6f766b819d2e797df6a3547d730a", submodules=True
)
version(
"1.1.2", tag="v1.1.2", commit="71002c1c1498ebd6f50a954731da68fa4f9d436b", submodules=True
)
maintainers("Thomas-Ulrich", "davschneller", "vikaskurapati")
variant("asagi", default=True, description="Use ASAGI for material input")
variant(
"convergence_order",
default="4",
description="polynomial degree plus one",
values=(str(v) for v in range(2, 9)),
multi=False,
)
variant(
"precision",
default="double",
description="float numerical precision",
values=("single", "double"),
multi=False,
)
variant(
"dr_quad_rule",
default="stroud",
description="dynamic rupture quadrature rule",
values=("stroud", "dunavant"),
multi=False,
)
variant(
"plasticity_method",
default="nb",
description="Plasticity method",
values=("nb", "ib"),
multi=False,
)
variant(
"equations",
default="elastic",
description="equation set used",
values=("elastic", "anisotropic", "viscoelastic2", "poroelastic"),
multi=False,
)
variant(
"number_of_mechanisms", default="3", description="number of mechanisms for viscoelasticity"
)
variant("netcdf", default=True, description="Enable Netcdf")
variant(
"graph_partitioning_libs",
default="parmetis",
description="graph partitioning library for mesh partitioning",
values=("none", "parmetis", "ptscotch", "parhip"),
multi=True,
)
# GPU options
variant("intel_gpu", default=False, description="Compile for Intel GPUs")
variant(
"intel_gpu_arch",
default="none",
values=("none", "bdw", "skl", "pvc"),
description="The Intel GPU to compile for",
when="+intel_gpu",
)
forwarded_variants = ["cuda", "intel_gpu", "rocm"]
for v in forwarded_variants:
variant(
"sycl_backend",
default="acpp",
description="SYCL backend to use for DR and point sources",
values=("acpp", "oneapi"),
when=f"+{v}",
)
variant(
"sycl_gemm",
default=False,
description="Use SYCL also for the wave propagation part (default for Intel GPUs)",
when=f"+{v}",
)
requires(
"-cuda -rocm -intel_gpu",
"+cuda",
"+rocm",
"+intel_gpu",
policy="one_of",
msg="You may either compile for one GPU backend, or for CPU.",
)
requires("%oneapi", when="sycl_backend=oneapi")
depends_on("hipsycl@0.9.3: +cuda", when="+cuda sycl_backend=acpp")
# TODO: this one needs to be +rocm as well--but that's not implemented yet
depends_on("hipsycl@develop", when="+rocm sycl_backend=acpp")
# TODO: extend as soon as level zero is available
depends_on("hipsycl@develop", when="+intel_gpu sycl_backend=acpp")
# TODO: once adaptivecpp supports NVHPC, forward that (SYCL_USE_NVHPC)
# GPU architecture requirements
conflicts(
"cuda_arch=none",
when="+cuda",
msg="A value for cuda_arch must be specified. Add cuda_arch=XX",
)
conflicts(
"amdgpu_target=none",
when="+rocm",
msg="A value for amdgpu_arch must be specified. Add amdgpu_arch=XX",
)
conflicts(
"intel_gpu_arch=none",
when="+intel_gpu",
msg="A value for intel_gpu_arch must be specified. Add intel_gpu_arch=XX",
)
variant(
"gemm_tools_list",
default="LIBXSMM,PSpaMM",
description="gemm toolkit(s) for the (CPU) code generator",
values=("LIBXSMM", "MKL", "OpenBLAS", "BLIS", "PSpaMM", "Eigen", "LIBXSMM_JIT"),
multi=True,
)
variant("memkind", default=True, description="Use memkind library for hbw memory support")
depends_on("mpi")
with when("+cuda"):
for var in ["openmpi", "mpich", "mvapich", "mvapich2", "mvapich2-gdr"]:
depends_on(f"{var} +cuda", when=f"^[virtuals=mpi] {var}")
with when("+rocm"):
for var in ["mpich", "mvapich2-gdr"]:
depends_on(f"{var} +rocm", when=f"^[virtuals=mpi] {var}")
# with cuda 12 and llvm 14:15, we have the issue: "error: no template named 'texture"
# https://github.com/llvm/llvm-project/issues/61340
conflicts("cuda@12", when="+cuda ^llvm@14:15")
depends_on("cuda@11:", when="+cuda")
depends_on("hip", when="+rocm")
# graph partitioning
with when("graph_partitioning_libs=parmetis"):
depends_on("parmetis +int64 +shared")
depends_on("metis +int64 +shared")
depends_on(
"scotch +mpi +mpi_thread +shared +threads +int64", when="graph_partitioning_libs=ptscotch"
)
depends_on("kahip", when="graph_partitioning_libs=parhip")
depends_on("hdf5 +shared +threadsafe +hl +mpi")
depends_on("netcdf-c@4.6: +shared +mpi", when="+netcdf")
depends_on("asagi +mpi +mpi3", when="+asagi")
depends_on("easi ~asagi jit=impalajit,lua", when="~asagi")
depends_on("easi +asagi jit=impalajit,lua", when="+asagi")
depends_on("intel-mkl threads=none", when="gemm_tools_list=MKL")
depends_on("blis threads=none", when="gemm_tools_list=BLIS")
depends_on("openblas threads=none", when="gemm_tools_list=OpenBLAS")
depends_on("libxsmm@main", when="gemm_tools_list=LIBXSMM_JIT")
conflicts("gemm_tools_list=LIBXSMM", when="gemm_tools_list=LIBXSMM_JIT")
depends_on("memkind", when="+memkind target=x86_64:")
depends_on("yaml-cpp@0.6.2")
depends_on("eigen@3.4.0")
# build dependencies (code generation)
with default_args(type="build"):
# https://seissol.readthedocs.io/en/latest/installing-dependencies.html
depends_on("cmake@3.20:")
depends_on("python@3.9:")
depends_on("py-setuptools")
depends_on("py-numpy@1.12:")
depends_on("py-scipy")
depends_on("py-matplotlib")
depends_on("py-pspamm", when="gemm_tools_list=PSpaMM")
forwarded_variants = ["cuda", "intel_gpu", "rocm"]
for v in forwarded_variants:
depends_on("py-gemmforge", when=f"+{v}")
depends_on("py-chainforgecodegen", when=f"+{v}")
depends_on("libxsmm@=1.17 +generator", when="gemm_tools_list=LIBXSMM target=x86_64:")
def cmake_args(self):
args = [
"-DMPI=ON",
self.define_from_variant("ASAGI", "asagi"),
self.define_from_variant("PRECISION", "precision"),
self.define_from_variant("PLASTICITY_METHOD", "plasticity_method"),
self.define_from_variant("DR_QUAD_RULE", "dr_quad_rule"),
self.define_from_variant("ORDER", "convergence_order"),
self.define_from_variant("EQUATIONS", "equations"),
self.define_from_variant("NETCDF", "netcdf"),
]
gemm_tools_list = ",".join(self.spec.variants["gemm_tools_list"].value)
args.append(f"-DGEMM_TOOLS_LIST={gemm_tools_list}")
graph_partitioning_libs = ",".join(self.spec.variants["graph_partitioning_libs"].value)
args.append(f"-DGRAPH_PARTITIONING_LIBS={graph_partitioning_libs}")
if self.spec.variants["equations"].value != "viscoelastic2":
args.append("-DNUMBER_OF_MECHANISMS=0")
else:
args.append(self.define_from_variant("NUMBER_OF_MECHANISMS", "number_of_mechanisms"))
with_gpu = (
self.spec.satisfies("+cuda")
or self.spec.satisfies("+rocm")
or self.spec.satisfies("+intel_gpu")
)
if with_gpu:
# Nvidia GPUs
if self.spec.satisfies("+cuda"):
cuda_arch = self.spec.variants["cuda_arch"].value[0]
args.append(f"-DDEVICE_ARCH=sm_{cuda_arch}")
args.append("-DUSE_GRAPH_CAPTURING=ON -DENABLE_PROFILING_MARKERS=ON")
if self.spec.satisfies("~sycl_gemm"):
args.append("-DDEVICE_BACKEND=cuda")
# ROCm/AMD GPUs
if self.spec.satisfies("+rocm"):
amdgpu_target = self.spec.variants["amdgpu_target"].value[0]
args.append(f"-DDEVICE_ARCH={amdgpu_target}")
args.append("-DENABLE_PROFILING_MARKERS=ON")
if self.spec.satisfies("+rocm@:5.6"):
args.append("-DUSE_GRAPH_CAPTURING=OFF")
else:
args.append("-DUSE_GRAPH_CAPTURING=ON")
if self.spec.satisfies("~sycl_gemm"):
args.append("-DDEVICE_BACKEND=hip")
# Intel GPUs
if self.spec.satisfies("+intel_gpu"):
assert self.spec.variants["intel_gpu_arch"].value != "none"
intel_gpu_arch = self.spec.variants["intel_gpu_arch"].value
if self.spec.satisfies("@:1.1.3"):
args.append("-DUSE_GRAPH_CAPTURING=OFF")
else:
args.append("-DUSE_GRAPH_CAPTURING=ON")
args.append(f"-DDEVICE_ARCH={intel_gpu_arch}")
# SYCL
sycl_backends = {"acpp": "hipsycl", "oneapi": "oneapi"}
syclcc_backends = {"acpp": "hipsycl", "oneapi": "dpcpp"}
sycl_backend = self.spec.variants["sycl_backend"].value
args.append(f"-DSYCLCC={syclcc_backends[sycl_backend]}")
if self.spec.satisfies("+sycl_gemm"):
args.append(f"-DDEVICE_BACKEND={sycl_backends[sycl_backend]}")
# CPU arch
# cf. https://spack.readthedocs.io/en/latest/basic_usage.html#support-for-specific-microarchitectures
# basic family matching
hostarch = "noarch"
if str(self.spec.target) == "aarch64":
hostarch = "neon"
if str(self.spec.target) == "x86_64":
# pure x86_64v1 doesn't support anything above SSE3
hostarch = "noarch"
if str(self.spec.target) == "x86_64_v2":
# AVX is only required for x86_64v3 and upwards
hostarch = "wsm"
if str(self.spec.target) == "x86_64_v3":
hostarch = "hsw"
if str(self.spec.target) == "x86_64_v4":
hostarch = "skx"
# specific architecture matching
if self.spec.target >= "westmere":
hostarch = "wsm"
if self.spec.target >= "sandybridge":
hostarch = "snb"
if self.spec.target >= "haswell":
hostarch = "hsw"
if self.spec.target >= "mic_knl":
hostarch = "knl"
if self.spec.target >= "skylake_avx512":
hostarch = "skx"
if self.spec.target >= "zen":
hostarch = "naples"
if self.spec.target >= "zen2":
hostarch = "rome"
if self.spec.target >= "zen3":
hostarch = "milan"
if self.spec.target >= "zen4":
hostarch = "bergamo"
if self.spec.target >= "thunderx2":
hostarch = "thunderx2t99"
if self.spec.target >= "power9":
hostarch = "power9"
if self.spec.target >= "m1":
hostarch = "apple-m1"
if self.spec.target >= "m2":
hostarch = "apple-m2"
if self.spec.target >= "a64fx":
hostarch = "a64fx"
args.append(f"-DHOST_ARCH={hostarch}")
args.append(self.define("PYTHON_EXECUTABLE", self.spec["python"].command.path))
return args
def setup_run_environment(self, env):
# for seissol-launch
env.prepend_path("PATH", self.prefix.share)