mirror of
https://github.com/deepseek-ai/DeepGEMM
synced 2025-05-05 23:34:22 +00:00
114 lines
3.8 KiB
Python
114 lines
3.8 KiB
Python
import os
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import time
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from typing import Any, Callable, Dict, List, Optional, Type
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import cuda.bindings.driver as cuda
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from .utils import run_gemm
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class Runtime:
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def __init__(self, path: str, kernel_name: str, caller: Callable[..., cuda.CUresult], args: List[str]) -> None:
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self.path = path
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self.lib = None
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self.kernel = None
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self.kernel_name = kernel_name
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self.caller = caller
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self.args = args
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assert self.is_path_valid(self.path)
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@staticmethod
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def is_path_valid(path: str) -> bool:
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# Exists and is a directory
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if not os.path.exists(path) or not os.path.isdir(path):
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return False
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# Contains all necessary files
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files = ['kernel.cubin']
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return all(os.path.exists(os.path.join(path, file)) for file in files)
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def __call__(self, **kwargs: Dict[str, Any]) -> cuda.CUresult:
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# Load CUBIN
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if self.kernel is None:
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start_time = time.time_ns()
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res, lib = cuda.cuLibraryLoadFromFile(
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bytes(os.path.join(self.path, 'kernel.cubin'), 'utf-8'), [], [], 0, [], [], 0)
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if res != cuda.CUresult.CUDA_SUCCESS:
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raise Exception(f'Failed to load library: {res}')
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res, kernel_count = cuda.cuLibraryGetKernelCount(lib)
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if res != cuda.CUresult.CUDA_SUCCESS:
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raise Exception(f'Failed to get kernel count: {res}')
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res, kernels = cuda.cuLibraryEnumerateKernels(kernel_count, lib)
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if res != cuda.CUresult.CUDA_SUCCESS:
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raise Exception(f'Failed to enumerate kernels: {res}')
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for kernel in kernels:
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res, kernel_name = cuda.cuKernelGetName(kernel)
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if res != cuda.CUresult.CUDA_SUCCESS:
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raise Exception(f'Failed to get kernel name: {res}')
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if bytes(self.kernel_name, encoding='utf-8') in kernel_name:
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self.kernel = kernel
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break
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if self.kernel is not None:
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self.lib = lib
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else:
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raise Exception('Failed to find required kernel')
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end_time = time.time_ns()
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elapsed_time = (end_time - start_time) / 1000
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if os.getenv('DG_JIT_DEBUG', None):
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print(
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f'Loading JIT runtime {self.path} took {elapsed_time:.2f} us.')
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return self.caller(
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self.kernel,
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*[kwargs[arg] for arg in self.args]
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)
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def __del__(self) -> None:
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if self.lib is not None:
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res = cuda.cuLibraryUnload(self.lib)[0]
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if res != cuda.CUresult.CUDA_SUCCESS:
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raise Exception(f'Failed to unload library {self.path}: {res}')
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class Fp8GemmRuntime(Runtime):
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def __init__(self, path: str) -> None:
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super().__init__(path, 'fp8_gemm', run_gemm, [
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'NUM_TMA_MULTICAST',
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'M',
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'BLOCK_M',
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'GMEM_D',
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'SCALES_B',
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'GROUPED_LAYOUT',
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'NUM_SMS',
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'SMEM_SIZE',
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'TENSOR_MAP_A',
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'TENSOR_MAP_B',
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'TENSOR_MAP_SCALES_A',
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'TENSOR_MAP_D',
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'STREAM',
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])
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class RuntimeCache:
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def __init__(self) -> None:
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self.cache = {}
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def __setitem__(self, path, runtime) -> None:
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self.cache[path] = runtime
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def get(self, path: str, runtime_cls: Type[Runtime] = Fp8GemmRuntime) -> Optional[Runtime]:
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# In Python runtime
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if path in self.cache:
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return self.cache[path]
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# Already compiled
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if os.path.exists(path) and Runtime.is_path_valid(path):
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runtime = runtime_cls(path)
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self.cache[path] = runtime
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return runtime
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return None |