9239bf718e
Signed-off-by: ElizaWszola <eliza@neuralmagic.com> Signed-off-by: ElizaWszola <ewszola@redhat.com> Co-authored-by: Lucas Wilkinson <wilkinson.lucas@gmail.com>
62 lines
1.9 KiB
C++
62 lines
1.9 KiB
C++
#pragma once
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#include "cutlass/cutlass.h"
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#include <climits>
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#include "cuda_runtime.h"
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#include <iostream>
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/**
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* Helper function for checking CUTLASS errors
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*/
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#define CUTLASS_CHECK(status) \
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{ \
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cutlass::Status error = status; \
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TORCH_CHECK(error == cutlass::Status::kSuccess, \
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cutlassGetStatusString(error)); \
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}
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/**
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* Panic wrapper for unwinding CUDA runtime errors
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*/
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#define CUDA_CHECK(status) \
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{ \
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cudaError_t error = status; \
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TORCH_CHECK(error == cudaSuccess, cudaGetErrorString(error)); \
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}
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inline int get_cuda_max_shared_memory_per_block_opt_in(int const device) {
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int max_shared_mem_per_block_opt_in = 0;
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cudaDeviceGetAttribute(&max_shared_mem_per_block_opt_in,
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cudaDevAttrMaxSharedMemoryPerBlockOptin, device);
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return max_shared_mem_per_block_opt_in;
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}
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int32_t get_sm_version_num();
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/**
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* A wrapper for a kernel that is used to guard against compilation on
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* architectures that will never use the kernel. The purpose of this is to
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* reduce the size of the compiled binary.
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* __CUDA_ARCH__ is not defined in host code, so this lets us smuggle the ifdef
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* into code that will be executed on the device where it is defined.
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*/
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template <typename Kernel>
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struct enable_sm90_or_later : Kernel {
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template <typename... Args>
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CUTLASS_DEVICE void operator()(Args&&... args) {
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#if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 900
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Kernel::operator()(std::forward<Args>(args)...);
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#endif
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}
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};
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template <typename Kernel>
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struct enable_sm90_only : Kernel {
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template <typename... Args>
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CUTLASS_DEVICE void operator()(Args&&... args) {
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#if defined __CUDA_ARCH__ && __CUDA_ARCH__ == 900
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Kernel::operator()(std::forward<Args>(args)...);
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#endif
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}
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};
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