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docs(GPUSimulators): add documentation for CudaContext

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Anthony Berg 2025-02-14 16:29:47 +01:00
parent ef207432db
commit 7c312c255f
1 changed files with 36 additions and 10 deletions
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46
GPUSimulators/CudaContext.py
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@ -44,8 +44,10 @@ class CudaContext(object):
def __init__(self, device=None, context_flags=None, use_cache=True, autotuning=True): def __init__(self, device=None, context_flags=None, use_cache=True, autotuning=True):
""" """
Create a new CUDA context Create a new CUDA context
Set device to an id or pci_bus_id to select a specific GPU
Set context_flags to cuda.ctx_flags.SCHED_BLOCKING_SYNC for a blocking context Args:
device: To use a specific GPU, provide either an ``id`` or ``pci_bus_id`` for the GPU.
context_flags: To set a blocking context, provide ``cuda.ctx_flags.SCHED_BLOCKING_SYNC``.
""" """
self.use_cache = use_cache self.use_cache = use_cache
@ -119,8 +121,21 @@ class CudaContext(object):
def __str__(self): def __str__(self):
return "CudaContext id " + str(self.cuda_context.handle) return "CudaContext id " + str(self.cuda_context.handle)
def hash_kernel(kernel_filename, include_dirs): def hash_kernel(self, kernel_filename: str, include_dirs: list[str]) -> str:
# Generate a kernel ID for our caches """
Generate a kernel ID for our caches.
Args:
kernel_filename: Path to the kernel file.
include_dirs: Directories to search for ``#include`` in the kernel file.
Returns:
MD5 has for the kernel in the cache.
Raises:
RuntimeError: When the number of ``#include``s surpassed the maximum (101) permitted ``#include``s.
"""
num_includes = 0 num_includes = 0
max_includes = 100 max_includes = 100
kernel_hasher = hashlib.md5() kernel_hasher = hashlib.md5()
@ -131,7 +146,7 @@ class CudaContext(object):
while len(files): while len(files):
if (num_includes > max_includes): if (num_includes > max_includes):
raise("Maximum number of includes reached - circular include in {:}?".format(kernel_filename)) raise RuntimeError("Maximum number of includes reached - circular include in {:}?".format(kernel_filename))
filename = files.pop() filename = files.pop()
@ -166,12 +181,23 @@ class CudaContext(object):
return kernel_hasher.hexdigest() return kernel_hasher.hexdigest()
def get_module(self, kernel_filename, def get_module(self, kernel_filename: str,
include_dirs=[], \ include_dirs: list[str]=[], \
defines={}, \ defines: dict={}, \
compile_args={'no_extern_c', True}, jit_compile_args={}): compile_args: dict={'no_extern_c': True}, jit_compile_args: dict={}) -> cuda.Module:
""" """
Reads a text file and creates an OpenCL kernel from that Reads a text file and creates an OpenCL kernel from that.
Args:
kernel_filename: The file to use for the kernel.
include_dirs: List of directories for the ``#include``s referenced.
defines: Adds ``#define`` tags to the kernel, such as: ``#define key value``.
compile_args: Adds other compiler options (parameters) for ``pycuda.compiler.compile()``.
jit_compile_args: Adds other just-in-time compilation options (parameters)
for ``pycuda.driver.module_from_buffer()``.
Returns:
The kernel module (pycuda.driver.Module).
""" """
def cuda_compile_message_handler(compile_success_bool, info_str, error_str): def cuda_compile_message_handler(compile_success_bool, info_str, error_str):