92 lines
3.2 KiB
C++
92 lines
3.2 KiB
C++
/*
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* SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights
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* reserved. SPDX-License-Identifier: Apache-2.0
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef FLASHINFER_FP4_GEMM_CUTLASS_H_
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#define FLASHINFER_FP4_GEMM_CUTLASS_H_
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#include <cuda_runtime_api.h>
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#include <vector>
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#include "flashinfer/gemm/cutlass_gemm_configs.h"
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namespace flashinfer {
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namespace gemm {
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/*
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This runner supports:
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FP4 inputs (A and B)
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float blockwise scaling factor
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float alpha scalings
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T output (D) where T = {float, half, __nv_bfloat16}
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Activations, biases and outputs are all assumed to be row-major.
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Weights are assumed to be column-major.
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Block scaling factor are interleaved.
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*/
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class CutlassFp4GemmRunnerInterface {
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public:
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CutlassFp4GemmRunnerInterface() {}
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virtual ~CutlassFp4GemmRunnerInterface() {}
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virtual void gemm(void* D, void const* A, void const* B, void const* input_sf,
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void const* weight_sf, float const* global_sf, int m, int n, int k,
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int batch_count, CutlassGemmConfig gemmConfig, char* workspace,
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const size_t workspaceBytes, cudaStream_t stream) = 0;
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// Returns desired workspace size in bytes.
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virtual size_t getWorkspaceSize(int const m, int const n, int const k, int batch_count) = 0;
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virtual std::vector<CutlassGemmConfig> getConfigs() const = 0;
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};
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enum class FP4GemmType {
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W4A4_NVFP4_NVFP4,
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};
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template <typename T, FP4GemmType gemmType = FP4GemmType::W4A4_NVFP4_NVFP4>
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class CutlassFp4GemmRunner : public virtual CutlassFp4GemmRunnerInterface {
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public:
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CutlassFp4GemmRunner();
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~CutlassFp4GemmRunner();
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void gemm(void* D, void const* A, void const* B, void const* input_sf, void const* weight_sf,
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float const* global_sf, int m, int n, int k, int batch_count,
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CutlassGemmConfig gemmConfig, char* workspace, const size_t workspaceBytes,
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cudaStream_t stream) override;
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// Returns desired workspace size in bytes.
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size_t getWorkspaceSize(int const m, int const n, int const k, int const batch_count) override;
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std::vector<CutlassGemmConfig> getConfigs() const override;
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private:
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size_t dispatchToArch(T* D, void const* A, void const* B, void const* input_sf,
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void const* weight_sf, float const* global_sf, int m, int n, int k,
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int batch_count, CutlassGemmConfig gemmConfig, char* workspace,
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const size_t workspaceBytes, cudaStream_t stream, int* occupancy = nullptr);
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size_t getWorkspaceSizeImpl(int const m, int const n, int const k, int const batch_count);
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};
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} // namespace gemm
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} // namespace flashinfer
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#endif // FLASHINFER_FP4_GEMM_CUTLASS_H_
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