mirror of
https://github.com/vllm-project/vllm.git
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Chris Leonard
59d0236193
Signed-off-by: Chris Leonard <chleonar@redhat.com> Signed-off-by: Shengqi Chen <harry-chen@outlook.com> Co-authored-by: Shengqi Chen <harry-chen@outlook.com>
80 lines
2.2 KiB
C++
80 lines
2.2 KiB
C++
/*
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* Copyright (c) 2026, NVIDIA CORPORATION. All rights reserved.
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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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#pragma once
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#include <cuda_bf16.h>
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#include <cuda_fp16.h>
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#include <torch/headeronly/core/ScalarType.h>
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namespace vllm {
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namespace tensorrt_llm {
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template <typename DType>
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struct ElemsPerAccess;
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template <>
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struct ElemsPerAccess<half> {
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static constexpr int value = 8;
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using vec_type = float4;
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};
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template <>
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struct ElemsPerAccess<nv_bfloat16> {
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static constexpr int value = 8;
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using vec_type = float4;
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};
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template <>
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struct ElemsPerAccess<float> {
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static constexpr int value = 4;
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using vec_type = float4;
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};
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template <typename DType>
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static constexpr int kElemsPerAccess = ElemsPerAccess<DType>::value;
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struct MiniMaxReduceRMSParams {
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int nranks{};
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int rank{};
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torch::headeronly::ScalarType dtype{torch::headeronly::ScalarType::Undefined};
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int size_q{};
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int hidden_dim{};
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int size_k{};
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int hidden_dim_k{};
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int stride_q{}; // row stride for q input (elements); when > hidden_dim,
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// q is part of a wider qkv tensor
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int stride_k{}; // row stride for k input (elements); when > hidden_dim_k,
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// k is part of a wider qkv tensor
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int stride_q_out{}; // row stride for q output (elements); 0 = contiguous
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int stride_k_out{}; // row stride for k output (elements); 0 = contiguous
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void** workspace{};
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void* allreduce_in{};
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void* rms_norm_out{};
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void* rms_gamma{};
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void* allreduce_in_k{};
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void* rms_norm_out_k{};
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void* rms_gamma_k{};
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float rms_eps{};
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cudaStream_t stream{};
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};
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void minimax_reduce_rms_op(MiniMaxReduceRMSParams const& params);
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} // namespace tensorrt_llm
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} // namespace vllm
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