107 lines
3.9 KiB
Plaintext
107 lines
3.9 KiB
Plaintext
#pragma once
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// clang-format will break include orders
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// clang-format off
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#include <torch/all.h>
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#include <ATen/cuda/CUDAContext.h>
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#include "cutlass/cutlass.h"
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#include "cute/tensor.hpp"
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#include "cute/atom/mma_atom.hpp"
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#include "cutlass/numeric_types.h"
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#include "cutlass/gemm/device/gemm_universal_adapter.h"
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#include "cutlass/gemm/kernel/gemm_universal.hpp"
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#include "cutlass/epilogue/collective/collective_builder.hpp"
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#include "cutlass/gemm/collective/collective_builder.hpp"
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#include "cutlass/util/packed_stride.hpp"
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#include "core/math.hpp"
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#include "cutlass_extensions/common.hpp"
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// clang-format on
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namespace vllm::c3x {
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static inline cute::Shape<int, int, int, int> get_problem_shape(
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torch::Tensor const& a, torch::Tensor const& b) {
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int32_t m = a.size(0), n = b.size(1), k = a.size(1);
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return {m, n, k, 1};
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}
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template <typename GemmKernel>
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void cutlass_gemm_caller(
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torch::Device device, cute::Shape<int, int, int, int> prob_shape,
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typename GemmKernel::MainloopArguments mainloop_args,
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typename GemmKernel::EpilogueArguments epilogue_args,
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typename GemmKernel::TileSchedulerArguments scheduler = {}) {
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cutlass::KernelHardwareInfo hw_info;
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typename GemmKernel::Arguments args{cutlass::gemm::GemmUniversalMode::kGemm,
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prob_shape,
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mainloop_args,
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epilogue_args,
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hw_info,
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scheduler};
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// Launch the CUTLASS GEMM kernel.
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using GemmOp = cutlass::gemm::device::GemmUniversalAdapter<GemmKernel>;
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GemmOp gemm_op;
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CUTLASS_CHECK(gemm_op.can_implement(args));
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size_t workspace_size = gemm_op.get_workspace_size(args);
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auto const workspace_options =
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torch::TensorOptions().dtype(torch::kUInt8).device(device);
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auto workspace = torch::empty(workspace_size, workspace_options);
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auto stream = at::cuda::getCurrentCUDAStream(device.index());
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cutlass::Status status = gemm_op.run(args, workspace.data_ptr(), stream);
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CUTLASS_CHECK(status);
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}
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template <typename Gemm, typename... EpilogueArgs>
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void cutlass_gemm_caller(torch::Tensor& out, torch::Tensor const& a,
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torch::Tensor const& b,
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EpilogueArgs&&... epilogue_params) {
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using ElementAB = typename Gemm::ElementAB;
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using ElementC = typename Gemm::ElementC;
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using ElementD = typename Gemm::ElementD;
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using GemmKernel = typename Gemm::GemmKernel;
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using StrideA = typename Gemm::GemmKernel::StrideA;
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using StrideB = typename Gemm::GemmKernel::StrideB;
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using StrideC = typename Gemm::GemmKernel::StrideC;
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using StrideD = StrideC;
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using StrideAux = StrideC;
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typename GemmKernel::ProblemShape prob_shape = get_problem_shape(a, b);
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auto [M, N, K, L] = prob_shape;
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StrideA a_stride =
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cutlass::make_cute_packed_stride(StrideA{}, cute::make_shape(M, K, L));
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StrideB b_stride =
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cutlass::make_cute_packed_stride(StrideB{}, cute::make_shape(N, K, L));
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StrideC c_stride =
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cutlass::make_cute_packed_stride(StrideC{}, cute::make_shape(M, N, L));
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StrideD d_stride =
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cutlass::make_cute_packed_stride(StrideD{}, cute::make_shape(M, N, L));
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StrideAux aux_stride = d_stride;
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auto a_ptr = static_cast<ElementAB*>(a.data_ptr());
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auto b_ptr = static_cast<ElementAB*>(b.data_ptr());
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typename GemmKernel::MainloopArguments mainloop_args{a_ptr, a_stride, b_ptr,
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b_stride};
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auto c_ptr = static_cast<ElementD*>(out.data_ptr());
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// auto d_ptr = static_cast<ElementC*>(out.data_ptr());
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typename GemmKernel::EpilogueArguments epilogue_args{
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Gemm::Epilogue::prepare_args(
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std::forward<EpilogueArgs>(epilogue_params)...),
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c_ptr, c_stride, c_ptr, d_stride};
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cutlass_gemm_caller<GemmKernel>(a.device(), prob_shape, mainloop_args,
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epilogue_args);
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}
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} // namespace vllm::c3x |