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All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are met: * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of the NVIDIA CORPORATION nor the * names of its contributors may be used to endorse or promote products * derived from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE * DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * ******************************************************************************/ #pragma once #include #include #ifdef OLD_GENERATOR_PATH #include #else #include #endif #include #include constexpr int TOTAL_DIM = 0; constexpr int THREE_DIM = 1; constexpr int H_DIM = 2; constexpr int D_DIM = 3; //////////////////////////////////////////////////////////////////////////////////////////////////// struct Qkv_params { // The QKV matrices. void * __restrict__ qkv_ptr; // The stride between rows of the Q, K and V matrices. // size_t qkv_stride_in_elts; // size_t qkv_stride_in_bytes; // TD [2022-04-16]: We're using 32-bit indexing to save registers. // The code probably won't work for arrays larger than 2GB. uint32_t qkv_stride_in_elts; uint32_t qkv_stride_in_bytes; // The number of heads. int h; }; //////////////////////////////////////////////////////////////////////////////////////////////////// struct Fused_multihead_attention_fprop_params : public Qkv_params { // The dQKV matrices. void * __restrict__ dqkv_ptr; // Temporary for dKV. void * __restrict__ dkv_ptr; // The O matrix (output). void * __restrict__ o_ptr; // The stride between rows of O. // size_t o_stride_in_elts; // size_t o_stride_in_bytes; uint32_t o_stride_in_elts; uint32_t o_stride_in_bytes; // The pointer to the O_tmp matrix, which holds O intermediate value during // the loop; void *__restrict__ o_tmp_ptr; // The dO matrix . void * __restrict__ do_ptr; // The pointer to the S matrix, overwritten by the dP matrix (bwd). void * __restrict__ s_ptr; // The stride between rows of the S matrix. // int64_t s_stride_in_bytes; uint32_t s_stride_in_bytes; // The pointer to the softmax sum. void * __restrict__ softmax_lse_ptr; // The pointer to the softmax d sum. void * __restrict__ dsoftmax_sum; // The dimensions. int b, s, d; // The scaling factors for the kernel. float scale_bmm1f; uint32_t scale_bmm1, scale_softmax, scale_bmm2; // array of length b+1 holding starting offset of each sequence. int * __restrict__ cu_seqlens; int *__restrict__ blockmask; // The dropout probability (probability of keeping an activation). float p_dropout; uint32_t p_dropout_in_uint; uint16_t p_dropout_in_uint16_t; // Scale factor of 1 / (1 - p_dropout). float rp_dropout; // Scale factor of 1 / (1 - p_dropout), in half2. uint32_t scale_dropout; // Random state. at::PhiloxCudaState philox_args; bool is_causal; }; //////////////////////////////////////////////////////////////////////////////////////////////////// template struct Launch_params{ Launch_params(cudaDeviceProp * props_, cudaStream_t stream_, bool is_dropout_, bool return_softmax_) : elts_per_thread(0) , props(props_) , stream(stream_) , is_dropout(is_dropout_) , return_softmax(return_softmax_) { } size_t elts_per_thread; cudaDeviceProp * props; cudaStream_t stream; bool is_dropout; bool return_softmax; Kernel_params params; int num_full_heads; int num_main_groups; int heads_last_wave; int main_steps; int rest_steps; }; //////////////////////////////////////////////////////////////////////////////////////////////////// void run_fmha_fp16_sm80(Launch_params &launch_params, const bool configure); void run_fmha_dgrad_fp16_sm80(const Fused_multihead_attention_fprop_params ¶ms, cudaStream_t stream); void run_fmha_block_fp16_sm80(Launch_params &launch_params, const bool configure); void run_fmha_block_dgrad_fp16_sm80(const Fused_multihead_attention_fprop_params ¶ms, cudaStream_t stream);