File size: 3,249 Bytes
57c3a10 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 | /*
* SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights
* reserved. SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef FLASHINFER_FP4_GEMM_CUTLASS_H_
#define FLASHINFER_FP4_GEMM_CUTLASS_H_
#include <cuda_runtime_api.h>
#include <vector>
#include "flashinfer/gemm/cutlass_gemm_configs.h"
namespace flashinfer {
namespace gemm {
/*
This runner supports:
FP4 inputs (A and B)
float blockwise scaling factor
float alpha scalings
T output (D) where T = {float, half, __nv_bfloat16}
Activations, biases and outputs are all assumed to be row-major.
Weights are assumed to be column-major.
Block scaling factor are interleaved.
*/
class CutlassFp4GemmRunnerInterface {
public:
CutlassFp4GemmRunnerInterface() {}
virtual ~CutlassFp4GemmRunnerInterface() {}
virtual void gemm(void* D, void const* A, void const* B, void const* input_sf,
void const* weight_sf, float const* global_sf, int m, int n, int k,
int batch_count, CutlassGemmConfig gemmConfig, char* workspace,
const size_t workspaceBytes, cudaStream_t stream) = 0;
// Returns desired workspace size in bytes.
virtual size_t getWorkspaceSize(int const m, int const n, int const k, int batch_count) = 0;
virtual std::vector<CutlassGemmConfig> getConfigs() const = 0;
};
enum class FP4GemmType {
W4A4_NVFP4_NVFP4,
};
template <typename T, FP4GemmType gemmType = FP4GemmType::W4A4_NVFP4_NVFP4>
class CutlassFp4GemmRunner : public virtual CutlassFp4GemmRunnerInterface {
public:
CutlassFp4GemmRunner();
~CutlassFp4GemmRunner();
void gemm(void* D, void const* A, void const* B, void const* input_sf, void const* weight_sf,
float const* global_sf, int m, int n, int k, int batch_count,
CutlassGemmConfig gemmConfig, char* workspace, const size_t workspaceBytes,
cudaStream_t stream) override;
// Returns desired workspace size in bytes.
size_t getWorkspaceSize(int const m, int const n, int const k, int const batch_count) override;
std::vector<CutlassGemmConfig> getConfigs() const override;
private:
size_t dispatchToArch(T* D, void const* A, void const* B, void const* input_sf,
void const* weight_sf, float const* global_sf, int m, int n, int k,
int batch_count, CutlassGemmConfig gemmConfig, char* workspace,
const size_t workspaceBytes, cudaStream_t stream, int* occupancy = nullptr);
size_t getWorkspaceSizeImpl(int const m, int const n, int const k, int const batch_count);
};
} // namespace gemm
} // namespace flashinfer
#endif // FLASHINFER_FP4_GEMM_CUTLASS_H_
|