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# Copyright (C) 2017-2018 Chris N. Richardson and Garth N. Wells
#
# This file is part of DOLFINx (https://www.fenicsproject.org)
#
# SPDX-License-Identifier: LGPL-3.0-or-later
"""Just-in-time (JIT) compilation using FFCx"""
import functools
import json
import os
import sys
from pathlib import Path
from typing import Optional
from mpi4py import MPI
import ffcx
import ffcx.codegeneration.jit
import ufl
__all__ = ["ffcx_jit", "get_options", "mpi_jit_decorator"]
DOLFINX_DEFAULT_JIT_OPTIONS = {
"cache_dir": (
os.getenv("XDG_CACHE_HOME", default=Path.home().joinpath(".cache")) / Path("fenics"),
"Path for storing DOLFINx JIT cache. "
"Default prefix ~/.cache/ can be changed using XDG_CACHE_HOME environment variable.",
),
"cffi_debug": (False, "CFFI debug mode"),
"cffi_verbose": (False, "CFFI verbose mode"),
"cffi_libraries": (None, "Extra libraries to link"),
"timeout": (10, "Timeout for JIT compilation"),
}
if sys.platform.startswith("win32"):
DOLFINX_DEFAULT_JIT_OPTIONS["cffi_extra_compile_args"] = (
["-O2"],
"Extra C compiler arguments to pass to CFFI",
)
else:
DOLFINX_DEFAULT_JIT_OPTIONS["cffi_extra_compile_args"] = (
["-O2", "-g0"],
"Extra C compiler arguments to pass to CFFI",
)
def mpi_jit_decorator(local_jit, *args, **kwargs):
"""A decorator for jit compilation.
Use this function as a decorator to any jit compiler function. In a
parallel run, this function will first call the jit compilation
function on the first process. When this is done, and the module is
in the cache, it will call the jit compiler on the remaining
processes, which will then use the cached module.
"""
@functools.wraps(local_jit)
def mpi_jit(comm, *args, **kwargs):
# Just call JIT compiler when running in serial
if comm.size == 1:
return local_jit(*args, **kwargs)
# Default status (0 == ok, 1 == fail)
status = 0
# Compile first on process 0
root = comm.rank == 0
if root:
try:
output = local_jit(*args, **kwargs)
except Exception as e:
status = 1
error_msg = str(e)
# TODO: This would have lower overhead if using the dijitso.jit
# features to inject a waiting callback instead of waiting out
# here. That approach allows all processes to first look in the
# cache, introducing a barrier only on cache miss. There's also
# a sketch in dijitso of how to make only one process per
# physical cache directory do the compilation.
# Wait for the compiling process to finish and get status
# TODO: Would be better to broadcast the status from root but
# this works.
global_status = comm.allreduce(status, op=MPI.MAX)
if global_status == 0:
# Success, call jit on all other processes (this should just
# read the cache)
if not root:
output = local_jit(*args, **kwargs)
else:
# Fail simultaneously on all processes, to allow catching
# the error without deadlock
if not root:
error_msg = "Compilation failed on root node."
raise RuntimeError(f"Failed just-in-time compilation of form: {error_msg}")
return output
# Return the decorated jit function
return mpi_jit
@functools.cache
def _load_options():
"""Loads options from JSON files."""
user_config_file = os.getenv("XDG_CONFIG_HOME", default=Path.home().joinpath(".config")) / Path(
"dolfinx", "dolfinx_jit_options.json"
)
try:
with open(user_config_file) as f:
user_options = json.load(f)
except FileNotFoundError:
user_options = dict()
pwd_config_file = Path.cwd().joinpath("dolfinx_jit_options.json")
try:
with open(pwd_config_file) as f:
pwd_options = json.load(f)
except FileNotFoundError:
pwd_options = dict()
return (user_options, pwd_options)
def get_options(priority_options: Optional[dict] = None) -> dict:
"""Return a copy of the merged JIT option values for DOLFINx.
Args:
priority_options: Take priority over all other option values
(see notes).
Returns:
dict: Merged option values.
Note:
See :func:`ffcx_jit` for user facing documentation.
"""
options = dict()
for param, (value, _) in DOLFINX_DEFAULT_JIT_OPTIONS.items():
options[param] = value
# NOTE: _load_options uses functools.lru_cache
user_options, pwd_options = _load_options()
options.update(user_options)
options.update(pwd_options)
if priority_options is not None:
options.update(priority_options)
options["cache_dir"] = Path(str(options["cache_dir"])).expanduser()
return options
@mpi_jit_decorator
def ffcx_jit(
ufl_object, form_compiler_options: Optional[dict] = None, jit_options: Optional[dict] = None
):
"""Compile UFL object with FFCx and CFFI.
Args:
ufl_object: Object to compile, e.g. ``ufl.Form``.
form_compiler_options: Options used in FFCx compilation of
this form. Run ``ffcx --help`` at the command line to see
all available options. Takes priority over all other option
values.
jit_options: Options used in CFFI JIT compilation of C code
generated by FFCx. See ``python/dolfinx/jit.py`` for all
available options. Takes priority over all other option
values.
Returns:
(compiled object, module, (header code, implementation code))
Note:
Priority ordering of options controlling DOLFINx JIT
compilation from highest to lowest is:
- **jit_options** (API)
- **$PWD/dolfinx_jit_options.json** (local options)
- **$XDG_CONFIG_HOME/dolfinx/dolfinx_jit_options.json**
(user options)
- **DOLFINX_DEFAULT_JIT_OPTIONS** in `dolfinx.jit`
Priority ordering of options controlling FFCx from highest to
lowest is:
- **form_compiler_optionss** (API)
- **$PWD/ffcx_options.json** (local options)
- **$XDG_CONFIG_HOME/ffcx/ffcx_options.json** (user options)
- **FFCX_DEFAULT_OPTIONS** in `ffcx.options`
`$XDG_CONFIG_HOME` is `~/.config/` if the environment variable is not set.
The contents of the `dolfinx_options.json` files are cached
on the first call. Subsequent calls to this function use this
cache.
Example `dolfinx_jit_options.json` file:
**{ "cffi_extra_compile_args": ["-O2", "-march=native" ], "cffi_verbose": True }**
"""
p_ffcx = ffcx.get_options(form_compiler_options)
p_jit = get_options(jit_options)
# Switch on type and compile, returning cffi object
if isinstance(ufl_object, ufl.Form):
r = ffcx.codegeneration.jit.compile_forms([ufl_object], options=p_ffcx, **p_jit)
elif isinstance(ufl_object, ufl.Mesh):
r = ffcx.codegeneration.jit.compile_coordinate_maps([ufl_object], options=p_ffcx, **p_jit)
elif isinstance(ufl_object, tuple) and isinstance(ufl_object[0], ufl.core.expr.Expr):
r = ffcx.codegeneration.jit.compile_expressions([ufl_object], options=p_ffcx, **p_jit)
else:
raise TypeError(type(ufl_object))
return (r[0][0], r[1], r[2])
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