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__init__.py
cpujit.py 25.44 KiB
r"""
*pystencils* automatically searches for a compiler, so in most cases no explicit configuration is required.
On Linux make sure that 'gcc' and 'g++' are installed and in your path.
On Windows a recent Visual Studio installation is required.
In case anything does not work as expected or a special compiler should be used, changes can be specified
in a configuration file.
*pystencils* looks for a configuration file in JSON format at the following locations in the listed order.
1. at the path specified in the environment variable ``PYSTENCILS_CONFIG``
2. in the current working direction for a file named ``pystencils.json``
3. or in your home directory at ``~/.config/pystencils/config.json`` (Linux) or
``%HOMEPATH%\.pystencils\config.json`` (Windows)
If no configuration file is found, a default configuration is created at the above mentioned location in your home.
So run *pystencils* once, then edit the created configuration file.
Compiler Config (Linux)
-----------------------
- **'os'**: should be detected automatically as 'linux'
- **'command'**: path to C++ compiler (defaults to 'g++')
- **'flags'**: space separated list of compiler flags. Make sure to activate OpenMP in your compiler
- **'restrict_qualifier'**: the restrict qualifier is not standardized accross compilers.
For most Linux compilers the qualifier is ``__restrict__``
Compiler Config (Windows)
-------------------------
*pystencils* uses the mechanism of *setuptools.msvc* to search for a compilation environment.
Then 'cl.exe' is used to compile.
- **'os'**: should be detected automatically as 'windows'
- **'msvc_version'**: either a version number, year number, 'auto' or 'latest' for automatic detection of latest
installed version or 'setuptools' for setuptools-based detection. Alternatively path to folder
where Visual Studio is installed. This path has to contain a file called 'vcvarsall.bat'
- **'arch'**: 'x86' or 'x64'
- **'flags'**: flags passed to 'cl.exe', make sure OpenMP is activated
- **'restrict_qualifier'**: the restrict qualifier is not standardized across compilers.
For Windows compilers the qualifier should be ``__restrict``
"""
import hashlib
import json
import os
import platform
import shutil
import subprocess
import textwrap
from collections import OrderedDict
from sysconfig import get_paths
from tempfile import TemporaryDirectory
import numpy as np
from appdirs import user_cache_dir, user_config_dir
from pystencils import FieldType
from pystencils.backends.cbackend import generate_c, get_headers
from pystencils.data_types import cast_func, VectorType
from pystencils.include import get_pystencils_include_path
from pystencils.kernel_wrapper import KernelWrapper
from pystencils.utils import atomic_file_write, file_handle_for_atomic_write, recursive_dict_update
def make_python_function(kernel_function_node, custom_backend=None):
"""
Creates C code from the abstract syntax tree, compiles it and makes it accessible as Python function
The parameters of the kernel are:
- numpy arrays for each field used in the kernel. The keyword argument name is the name of the field
- all symbols which are not defined in the kernel itself are expected as parameters
:param kernel_function_node: the abstract syntax tree
:return: kernel functor
"""
result = compile_and_load(kernel_function_node, custom_backend)
return result
def set_config(config):
"""
Override the configuration provided in config file
Configuration of compiler parameters:
If this function is not called the configuration is taken from a config file in JSON format which
is searched in the following locations in the order specified:
- at location provided in environment variable PYSTENCILS_CONFIG (if this variable exists)
- a file called ".pystencils.json" in the current working directory
- ~/.pystencils.json in your home
If none of these files exist a file ~/.pystencils.json is created with a default configuration using
the GNU 'g++'
An example JSON file with all possible keys. If not all keys are specified, default values are used
``
{
'compiler' :
{
"command": "/software/intel/2017/bin/icpc",
"flags": "-Ofast -DNDEBUG -fPIC -march=native -fopenmp",
"env": {
"LM_PROJECT": "iwia",
}
}
}
``
"""
global _config
_config = config.copy()
def get_configuration_file_path():
config_path_in_home = os.path.join(user_config_dir('pystencils'), 'config.json')
# 1) Read path from environment variable if found
if 'PYSTENCILS_CONFIG' in os.environ:
return os.environ['PYSTENCILS_CONFIG'], True
# 2) Look in current directory for pystencils.json
elif os.path.exists("pystencils.json"):
return "pystencils.json", True
# 3) Try ~/.pystencils.json
elif os.path.exists(config_path_in_home):
return config_path_in_home, True
else:
return config_path_in_home, False
def create_folder(path, is_file):
if is_file:
path = os.path.split(path)[0]
try:
os.makedirs(path)
except os.error:
pass
def get_llc_command():
"""Try to get executable for llvm's IR compiler llc
We try if one of the following is in PATH: llc, llc-10, llc-9, llc-8, llc-7, llc-6
"""
candidates = ['llc', 'llc-10', 'llc-9', 'llc-8', 'llc-7', 'llc-6']
found_executables = (e for e in candidates if shutil.which(e))
return next(found_executables, None)
def read_config():
if platform.system().lower() == 'linux':
default_compiler_config = OrderedDict([
('os', 'linux'),
('command', 'g++'),
('llc_command', get_llc_command() or 'llc'),
('flags', '-Ofast -DNDEBUG -fPIC -march=native -fopenmp -std=c++11'),
('restrict_qualifier', '__restrict__')
])
elif platform.system().lower() == 'windows':
default_compiler_config = OrderedDict([
('os', 'windows'),
('msvc_version', 'latest'),
('llc_command', get_llc_command() or 'llc'),
('arch', 'x64'),
('flags', '/Ox /fp:fast /OpenMP /arch:avx'),
('restrict_qualifier', '__restrict')
])
elif platform.system().lower() == 'darwin':
default_compiler_config = OrderedDict([
('os', 'darwin'),
('command', 'clang++'),
('llc_command', get_llc_command() or 'llc'),
('flags', '-Ofast -DNDEBUG -fPIC -march=native -Xclang -fopenmp -std=c++11'),
('restrict_qualifier', '__restrict__')
])
if platform.machine() == 'arm64':
default_compiler_config['flags'] = default_compiler_config['flags'].replace('-march=native ', '')
for libomp in ['/opt/local/lib/libomp/libomp.dylib', '/usr/local/lib/libomp.dylib',
'/opt/homebrew/lib/libomp.dylib']:
if os.path.exists(libomp):
default_compiler_config['flags'] += ' ' + libomp
break
default_cache_config = OrderedDict([
('object_cache', os.path.join(user_cache_dir('pystencils'), 'objectcache')),
('clear_cache_on_start', False),
])
default_config = OrderedDict([('compiler', default_compiler_config),
('cache', default_cache_config)])
config_path, config_exists = get_configuration_file_path()
config = default_config.copy()
if config_exists:
with open(config_path, 'r') as json_config_file:
loaded_config = json.load(json_config_file)
config = recursive_dict_update(config, loaded_config)
else:
create_folder(config_path, True)
with open(config_path, 'w') as f:
json.dump(config, f, indent=4)
if config['cache']['object_cache'] is not False:
config['cache']['object_cache'] = os.path.expanduser(config['cache']['object_cache']).format(pid=os.getpid())
if config['cache']['clear_cache_on_start']:
shutil.rmtree(config['cache']['object_cache'], ignore_errors=True)
create_folder(config['cache']['object_cache'], False)
if config['compiler']['os'] == 'windows':
from pystencils.cpu.msvc_detection import get_environment
msvc_env = get_environment(config['compiler']['msvc_version'], config['compiler']['arch'])
if 'env' not in config['compiler']:
config['compiler']['env'] = {}
config['compiler']['env'].update(msvc_env)
return config
_config = read_config()
def get_compiler_config():
return _config['compiler']
def get_cache_config():
return _config['cache']
def add_or_change_compiler_flags(flags):
if not isinstance(flags, list) and not isinstance(flags, tuple):
flags = [flags]
compiler_config = get_compiler_config()
cache_config = get_cache_config()
cache_config['object_cache'] = False # disable cache
for flag in flags:
flag = flag.strip()
if '=' in flag:
base = flag.split('=')[0].strip()
else:
base = flag
new_flags = [c for c in compiler_config['flags'].split() if not c.startswith(base)]
new_flags.append(flag)
compiler_config['flags'] = ' '.join(new_flags)
def clear_cache():
cache_config = get_cache_config()
if cache_config['object_cache'] is not False:
shutil.rmtree(cache_config['object_cache'], ignore_errors=True)
create_folder(cache_config['object_cache'], False)
type_mapping = {
np.float32: ('PyFloat_AsDouble', 'float'),
np.float64: ('PyFloat_AsDouble', 'double'),
np.int16: ('PyLong_AsLong', 'int16_t'),
np.int32: ('PyLong_AsLong', 'int32_t'),
np.int64: ('PyLong_AsLong', 'int64_t'),
np.uint16: ('PyLong_AsUnsignedLong', 'uint16_t'),
np.uint32: ('PyLong_AsUnsignedLong', 'uint32_t'),
np.uint64: ('PyLong_AsUnsignedLong', 'uint64_t'),
np.complex64: (('PyComplex_RealAsDouble', 'PyComplex_ImagAsDouble'), 'ComplexFloat'),
np.complex128: (('PyComplex_RealAsDouble', 'PyComplex_ImagAsDouble'), 'ComplexDouble'),
}
template_extract_scalar = """
PyObject * obj_{name} = PyDict_GetItemString(kwargs, "{name}");
if( obj_{name} == NULL) {{ PyErr_SetString(PyExc_TypeError, "Keyword argument '{name}' missing"); return NULL; }};
{target_type} {name} = ({target_type}) {extract_function}( obj_{name} );
if( PyErr_Occurred() ) {{ return NULL; }}
"""
template_extract_complex = """
PyObject * obj_{name} = PyDict_GetItemString(kwargs, "{name}");
if( obj_{name} == NULL) {{ PyErr_SetString(PyExc_TypeError, "Keyword argument '{name}' missing"); return NULL; }};
{target_type} {name}{{ ({real_type}) {extract_function_real}( obj_{name} ),
({real_type}) {extract_function_imag}( obj_{name} ) }};
if( PyErr_Occurred() ) {{ return NULL; }}
"""
template_extract_array = """
PyObject * obj_{name} = PyDict_GetItemString(kwargs, "{name}");
if( obj_{name} == NULL) {{ PyErr_SetString(PyExc_TypeError, "Keyword argument '{name}' missing"); return NULL; }};
Py_buffer buffer_{name};
int buffer_{name}_res = PyObject_GetBuffer(obj_{name}, &buffer_{name}, PyBUF_STRIDES | PyBUF_WRITABLE | PyBUF_FORMAT);
if (buffer_{name}_res == -1) {{ return NULL; }}
"""
template_release_buffer = """
PyBuffer_Release(&buffer_{name});
"""
template_function_boilerplate = """
static PyObject * {func_name}(PyObject * self, PyObject * args, PyObject * kwargs)
{{
if( !kwargs || !PyDict_Check(kwargs) ) {{
PyErr_SetString(PyExc_TypeError, "No keyword arguments passed");
return NULL;
}}
{pre_call_code}
kernel_{func_name}({parameters});
{post_call_code}
Py_RETURN_NONE;
}}
"""
template_check_array = """
if(!({cond})) {{
PyErr_SetString(PyExc_ValueError, "Wrong {what} of array {name}. Expected {expected}");
return NULL;
}}
"""
template_size_check = """
if(!({cond})) {{
PyErr_SetString(PyExc_TypeError, "Arrays must have same shape"); return NULL;
}}"""
template_module_boilerplate = """
static PyMethodDef method_definitions[] = {{
{method_definitions}
{{NULL, NULL, 0, NULL}}
}};
static struct PyModuleDef module_definition = {{
PyModuleDef_HEAD_INIT,
"{module_name}", /* name of module */
NULL, /* module documentation, may be NULL */
-1, /* size of per-interpreter state of the module,
or -1 if the module keeps state in global variables. */
method_definitions
}};
PyMODINIT_FUNC
PyInit_{module_name}(void)
{{
return PyModule_Create(&module_definition);
}}
"""
def equal_size_check(fields):
fields = list(fields)
if len(fields) <= 1:
return ""
ref_field = fields[0]
cond = ["(buffer_{field.name}.shape[{i}] == buffer_{ref_field.name}.shape[{i}])".format(ref_field=ref_field,
field=field_to_test, i=i)
for field_to_test in fields[1:]
for i in range(fields[0].spatial_dimensions)]
cond = " && ".join(cond)
return template_size_check.format(cond=cond)
def create_function_boilerplate_code(parameter_info, name, ast_node, insert_checks=True):
pre_call_code = ""
parameters = []
post_call_code = ""
variable_sized_normal_fields = set()
variable_sized_index_fields = set()
for param in parameter_info:
if param.is_field_pointer:
field = param.fields[0]
pre_call_code += template_extract_array.format(name=field.name)
post_call_code += template_release_buffer.format(name=field.name)
parameters.append(f"({str(field.dtype)} *)buffer_{field.name}.buf")
if insert_checks:
np_dtype = field.dtype.numpy_dtype
item_size = np_dtype.itemsize
aligned = any([a.lhs.args[2] for a in ast_node.assignments
if hasattr(a, 'lhs') and isinstance(a.lhs, cast_func)
and hasattr(a.lhs, 'dtype') and isinstance(a.lhs.dtype, VectorType)])
if ast_node.instruction_set and aligned:
byte_width = ast_node.instruction_set['width'] * item_size
offset = max(max(ast_node.ghost_layers)) * item_size
offset_cond = f"(((uintptr_t) buffer_{field.name}.buf) + {offset}) % {byte_width} == 0"
message = str(offset) + ". This is probably due to a different number of ghost_layers chosen for " \
"the arrays and the kernel creation. If the number of ghost layers for " \
"the kernel creation is not specified it will choose a suitable value " \
"automatically. This value might not " \
"be compatible with the allocated arrays."
pre_call_code += template_check_array.format(cond=offset_cond, what="offset", name=field.name,
expected=message)
if (np_dtype.isbuiltin and FieldType.is_generic(field)
and not np.issubdtype(field.dtype.numpy_dtype, np.complexfloating)):
dtype_cond = "buffer_{name}.format[0] == '{format}'".format(name=field.name,
format=field.dtype.numpy_dtype.char)
pre_call_code += template_check_array.format(cond=dtype_cond, what="data type", name=field.name,
expected=str(field.dtype.numpy_dtype))
item_size_cond = f"buffer_{field.name}.itemsize == {item_size}"
pre_call_code += template_check_array.format(cond=item_size_cond, what="itemsize", name=field.name,
expected=item_size)
if field.has_fixed_shape:
shape_cond = [f"buffer_{field.name}.shape[{i}] == {s}"
for i, s in enumerate(field.spatial_shape)]
shape_cond = " && ".join(shape_cond)
pre_call_code += template_check_array.format(cond=shape_cond, what="shape", name=field.name,
expected=str(field.shape))
expected_strides = [e * item_size for e in field.spatial_strides]
stride_check_code = "(buffer_{name}.strides[{i}] == {s} || buffer_{name}.shape[{i}]<=1)"
strides_cond = " && ".join([stride_check_code.format(s=s, i=i, name=field.name)
for i, s in enumerate(expected_strides)])
pre_call_code += template_check_array.format(cond=strides_cond, what="strides", name=field.name,
expected=str(expected_strides))
else:
if FieldType.is_generic(field):
variable_sized_normal_fields.add(field)
elif FieldType.is_indexed(field):
variable_sized_index_fields.add(field)
elif param.is_field_stride:
field = param.fields[0]
item_size = field.dtype.numpy_dtype.itemsize
parameters.append("buffer_{name}.strides[{i}] / {bytes}".format(bytes=item_size, i=param.symbol.coordinate,
name=field.name))
elif param.is_field_shape:
parameters.append(f"buffer_{param.field_name}.shape[{param.symbol.coordinate}]")
else:
extract_function, target_type = type_mapping[param.symbol.dtype.numpy_dtype.type]
if np.issubdtype(param.symbol.dtype.numpy_dtype, np.complexfloating):
pre_call_code += template_extract_complex.format(extract_function_real=extract_function[0],
extract_function_imag=extract_function[1],
target_type=target_type,
real_type="float" if target_type == "ComplexFloat"
else "double",
name=param.symbol.name)
else:
pre_call_code += template_extract_scalar.format(extract_function=extract_function,
target_type=target_type,
name=param.symbol.name)
parameters.append(param.symbol.name)
pre_call_code += equal_size_check(variable_sized_normal_fields)
pre_call_code += equal_size_check(variable_sized_index_fields)
pre_call_code = textwrap.indent(pre_call_code, ' ')
post_call_code = textwrap.indent(post_call_code, ' ')
return template_function_boilerplate.format(func_name=name, pre_call_code=pre_call_code,
post_call_code=post_call_code, parameters=", ".join(parameters))
def create_module_boilerplate_code(module_name, names):
method_definition = '{{"{name}", (PyCFunction){name}, METH_VARARGS | METH_KEYWORDS, ""}},'
method_definitions = "\n".join([method_definition.format(name=name) for name in names])
return template_module_boilerplate.format(module_name=module_name, method_definitions=method_definitions)
def load_kernel_from_file(module_name, function_name, path):
from importlib.util import spec_from_file_location, module_from_spec
try:
spec = spec_from_file_location(name=module_name, location=path)
mod = module_from_spec(spec)
spec.loader.exec_module(mod)
except ImportError:
import time
import warnings
warnings.warn("Could not load " + path + ", trying on more time...")
time.sleep(1)
spec = spec_from_file_location(name=module_name, location=path)
mod = module_from_spec(spec)
spec.loader.exec_module(mod)
return getattr(mod, function_name)
def run_compile_step(command):
compiler_config = get_compiler_config()
config_env = compiler_config['env'] if 'env' in compiler_config else {}
compile_environment = os.environ.copy()
compile_environment.update(config_env)
try:
shell = True if compiler_config['os'].lower() == 'windows' else False
subprocess.check_output(command, env=compile_environment, stderr=subprocess.STDOUT, shell=shell)
except subprocess.CalledProcessError as e:
print(" ".join(command))
print(e.output.decode('utf8'))
raise e
class ExtensionModuleCode:
def __init__(self, module_name='generated', custom_backend=None):
self.module_name = module_name
self._ast_nodes = []
self._function_names = []
self._custom_backend = custom_backend
def add_function(self, ast, name=None):
self._ast_nodes.append(ast)
self._function_names.append(name if name is not None else ast.function_name)
def write_to_file(self, restrict_qualifier, function_prefix, file):
headers = {'<math.h>', '<stdint.h>'}
for ast in self._ast_nodes:
headers.update(get_headers(ast))
header_list = list(headers)
header_list.sort()
header_list.insert(0, '"Python.h"')
includes = "\n".join(["#include %s" % (include_file,) for include_file in header_list])
print(includes, file=file)
print("\n", file=file)
print(f"#define RESTRICT {restrict_qualifier}", file=file)
print(f"#define FUNC_PREFIX {function_prefix}", file=file)
print("\n", file=file)
for ast, name in zip(self._ast_nodes, self._function_names):
old_name = ast.function_name
ast.function_name = "kernel_" + name
print(generate_c(ast, custom_backend=self._custom_backend), file=file)
print(create_function_boilerplate_code(ast.get_parameters(), name, ast), file=file)
ast.function_name = old_name
print(create_module_boilerplate_code(self.module_name, self._function_names), file=file)
def compile_module(code, code_hash, base_dir):
compiler_config = get_compiler_config()
extra_flags = ['-I' + get_paths()['include'], '-I' + get_pystencils_include_path()]
if compiler_config['os'].lower() == 'windows':
function_prefix = '__declspec(dllexport)'
lib_suffix = '.pyd'
object_suffix = '.obj'
windows = True
else:
function_prefix = ''
lib_suffix = '.so'
object_suffix = '.o'
windows = False
src_file = os.path.join(base_dir, code_hash + ".cpp")
lib_file = os.path.join(base_dir, code_hash + lib_suffix)
object_file = os.path.join(base_dir, code_hash + object_suffix)
if not os.path.exists(object_file):
with file_handle_for_atomic_write(src_file) as f:
code.write_to_file(compiler_config['restrict_qualifier'], function_prefix, f)
if windows:
compile_cmd = ['cl.exe', '/c', '/EHsc'] + compiler_config['flags'].split()
compile_cmd += [*extra_flags, src_file, '/Fo' + object_file]
run_compile_step(compile_cmd)
else:
with atomic_file_write(object_file) as file_name:
compile_cmd = [compiler_config['command'], '-c'] + compiler_config['flags'].split()
compile_cmd += [*extra_flags, '-o', file_name, src_file]
run_compile_step(compile_cmd)
# Linking
if windows:
import sysconfig
config_vars = sysconfig.get_config_vars()
py_lib = os.path.join(config_vars["installed_base"], "libs",
f"python{config_vars['py_version_nodot']}.lib")
run_compile_step(['link.exe', py_lib, '/DLL', '/out:' + lib_file, object_file])
elif platform.system().lower() == 'darwin':
with atomic_file_write(lib_file) as file_name:
run_compile_step([compiler_config['command'], '-shared', object_file, '-o', file_name, '-undefined',
'dynamic_lookup']
+ compiler_config['flags'].split())
else:
with atomic_file_write(lib_file) as file_name:
run_compile_step([compiler_config['command'], '-shared', object_file, '-o', file_name]
+ compiler_config['flags'].split())
return lib_file
def compile_and_load(ast, custom_backend=None):
cache_config = get_cache_config()
generated_code = generate_c(ast, dialect='c', custom_backend=custom_backend)
fields_accessed = str(ast.fields_accessed)
# Also the information of the field size should be contained in the hash string. Due to padding the generated code
# can look similar for different field sizes.
code_hash_str = "mod_" + hashlib.sha256((generated_code + fields_accessed).encode()).hexdigest()
code = ExtensionModuleCode(module_name=code_hash_str, custom_backend=custom_backend)
code.add_function(ast, ast.function_name)
if cache_config['object_cache'] is False:
with TemporaryDirectory() as base_dir:
lib_file = compile_module(code, code_hash_str, base_dir)
result = load_kernel_from_file(code_hash_str, ast.function_name, lib_file)
else:
lib_file = compile_module(code, code_hash_str, base_dir=cache_config['object_cache'])
result = load_kernel_from_file(code_hash_str, ast.function_name, lib_file)
return KernelWrapper(result, ast.get_parameters(), ast)