mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-05 22:22:27 +00:00
c156989298
* Use dictionary to config all the functions * Add init codegen logic for fmha fwd appendkv * Call HIP_CHECK_ERROR() macro to get real source info * Setup meaningfull arguments * Sync kernel name with the codegen * Add knew/vnew tensors to the kernel argument * Fix wrong K values after appending * Fix vnew append errro * Extract common logics * Fix Vnew tile dstr for row major case * Conditionally add fwd_splitkv API in fmha_fwd example * Conditionally add call to fmha_fwd_splitkv() * Remove "EXAMPLE_" prefix of cmake variables * Regsiter API handlers automatically * Early return if 0 < s_k_new is not supported * Show message if we are ignoring option * Unify CMakeLists.txt coding style * Set num_splits=1 if split-kv is not supported * Add length/stride getters for HostTensor * Add RoPE example utilities * Add reference_rotary_position_embedding() (not implemented) * Finish reference_rotary_position_embedding() impl * Fix typo of HostTensor<>::get_length() * Fix compilation errors * Fix wrong answer when interleaved=false * Fix wrong answer when interleaved=true * Append K/V in the host verification code * Simplify K appending logics * Simplify v_host_ref definition * Reduce input/output dimensions * Rename function: add "batched" prefix * Apply RoPE on host side * Rename RoPE utility function * Fix wrong tensor size * Avoid invoking deprecated method 'find_module' * Pass RoPE kernel args * Create Rotary Cos/Sin tile windows in kernel * Add compute data type alias for RoPE * Randomly generate seqlen_knew if needed * Fix seqlen_knew enabling check logic * Add minimum seqlen_k to generate compliance kvcache * Fix compilation error in debug mode * Fix wrong boundaries * Fix wrong seqlen_k for kvcache * Rename variables used in distributio encoding * Fix rotary cos/sin tensor/tile size * Add constraint to the rotary_dim option * Remove unused inner namespace * Add dram distribution for rotary_cos/rotary_sin (interleaved) * Only apply interleaved RoPE on Knew for now * Fix wrong thread starting offset * Instantiate multiple kernels for RoPE approaches * Clean-up pipeline * Fix error in RoPE host reference * Handle RoPE half-rotated logics * Support 8x rotary_dim under half-rotated RoPE * Add comment * Apply elementwise function to the loaded tiles * Unify parameter/variable naming style * Remove constness from q_ptr * Add code blocks for q_tile * Apply RoPE to q_tile * Remove debug print code in kernel * Fix wrong knew/vnew appending positions * Use better naming for tile indices * Add make_tile_window() for adding distribution only * Skip code if # of block is more than needed * Move thread locating logics into policy * Remove always true static_assert() * Rename header * Rename RotaryEmbeddingEnum * Extract rotary embedding logic out * Re-order parameters * Align naming of some tile size constants * Rename more tile size constants * Fix wrong grid size * Fix wrong shape of knew_host/vnew_host * Fix wrong index into knew_host/vnew_host * Fix wrong rotary_cos/rotary_sin memory size for Q * Extract Q/Knew vector size to helper methods * Use different rotary_cos/rotary_sin distr for Q/Knew * Update host/device specifiers * Fix wrong data type for Q rotary_cos/rotary_sin * Remove RoPEComputeDataType type alias * Shift rotary_cos/rotary_sin by cache_seqlen_k * Add comment for why I just 't' for all padding flags * Align commit message to the real comment * Fix wrong pipeline * Rename utility function * Disable host verification if API not exist * Fix wrong rope key for fp8 pipeline * Allow only apply RoPE on Q (without append KV) * Add append-kv smoke tests * Remove debug statements * Remove more debug statements * Re-arrange the 'set +x' command * Remove no-longer used method in pipeline * Add missing init code * Refine pipeline padding settings * Enlarge rotary_dim limit (8 -> 16) * Enlarge KPerThread for rotary_interleaved=false * Update rotary_dim range in smoke_test_fwd.sh * Add template argument 'kIsPagedKV' for splitkv kernels * Launch splitkv kernel if given page_block_size * Fix wrong kernel name * Fix seqlen_k_min for pre-fill case (1 -> 0) * Add copy_const<> type trait * Add another make_tile_window() * Introduce 'TileWindowNavigator' types * Simplify TileWindowNavigator interfaces * Fix tile window navigation bugs * Disable calling fmha_fwd() * Remove ununnecessary data members * Simplify more make_tile_window() overloads * Move V tile through TileWindowNavigator * Fix uneven split checking logic * Move code after decide seqlen_q/seqlen_k * Make sure we always start reading complete tile * Use 128 as minimus page_block_size * Fix wrong origin for bias * Add batch_stride_k/batch_stride_v in group mode * Unify origin * Add missing kernel arguments for group mode * Add paged-kv codegen logic for appendkv kernels * Add block_table kernel args for appendkv kernel * Add tile navigators to the appendkv kernel * Fix wrong tensor descriptor lengths * Pass re-created tile window to pipeline * Fix wrong strides for appendkv kernel * Allow transit tile_window to another page-block * Handle cross-page-block write * Donot perform write again if already in last page-block * Always add fmha_fwd() api * Add missing group mode argument * Remove debug macro usages * Rename option s_k_new to s_knew * Separate splitkv/non-splitkv args/traits * Remove fmha_fwd_dispatch() * Fix compilation errors * Remove dropout code in splitkv kernel * Allow problem types without define kHasDropout attr * Use generic lambda to init traits objects * Separate more non-splitkv & splitkv traits/args * Display more info for specific kernels * Show more detailed warning message * Rename 'max_num_blocks' to 'max_num_page_blocks' * Remove no-longer used pipeline files * Wrap code by #if directives * Move functors to the begining of validation code * Use generic lambda to init all the api traits/args * Fix wrong seqlen for kvcache * Add missing comment * Rename TileWindowNavigator to PageBlockNavigator * Only expose necessary methods (not attributes) * Re-order pipeline paremeters * Refine smoke_test_fwd.sh * Fix wrong arugment count * Make tile window directly via PageBlockNavigator * Remove unused template paremeter * Remove group mode from appendkv kernel * Fix skcheck logic * Fix wrong syntax in skcheck expr * Use meaningful options in smoke test * Remove options * Fix formatting * Fix more format * Re-organize bash functions * Pass cache_batch_idx to kernels * Support cache_batch_idx in example * Fix compilation error * Add more appendkv test * Add more case for appendkv * Fix unexisted attribute * Remove 0 < seqlen_knew constraint * Clarify the case in warning message * Remove macro checking * Force batch mode when invoking appendkv & splitkv apis * Fix mode overriding logics * Fix wrong parameter name * Randomize seqlen_k if use kvcache * Use randomized seqlen_k for kvcache * Avoid using too small rotary_cos & rotary_sin * Rename parameter * Add seqlen_q & seqlen_k rules * Add comment * Add more comments * Fix compilation errors * Fix typo in comment * Remove type argument * Avoid seqlen_k=0 for kvcache * Revert "Avoid seqlen_k=0 for kvcache" This reverts commit21c4df89e4. * Fix wrong uneven split checking logics * Only randomize kvcache seqlen_k if 1 < batch * Return earlier if split is empty * Revert "Only randomize kvcache seqlen_k if 1 < batch" This reverts commitb9a4ab0d7e. * Re-order seqlen_k_start adjustment logics * Fix compilation errors * Re-format script * Find executable from folder automatically * Fix kvcache seqlen_k generating logic * Make comment more clear * Fix wrong knew/vew appending logic on host * Add s_barrier to sync threads * Revert "Add s_barrier to sync threads" This reverts commitd3f550f30c. * Support only using 1 row of rotary_cos/rotary_sin * Rotate Q in different way * Unify tensor view creation logics * Fix wrong argument * Add mask to switch how we use the rotary_cos/sin * Move attr from traits to problem * Move has_mask to fmha_fwd_appendkv_args * Support use uint32_t as SAD operand in Alibi<> * Use sad_u32() in splitkv kernels * Store tensor views in PageBlockNavigator * Use stored tensor view to update tile windows * Enlarge tensor view size * Remove debug code * Fix wrong tensor view size * Wrap tensor view into PageBlockNavigator * Add DataType member to PageBlockNavigator * Remove unnecessary member functions * Refind macro use * Fix typo * Add blank line between directives and actual code * Re-format files * Remove type in comment --------- Co-authored-by: carlushuang <carlus.huang@amd.com> Co-authored-by: rocking <ChunYu.Lai@amd.com>
775 lines
32 KiB
C++
775 lines
32 KiB
C++
// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include "ck_tile/core.hpp"
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#include "ck_tile/host/kernel_launch.hpp"
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#include "ck_tile/ops/epilogue.hpp"
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#include "ck_tile/ops/fmha.hpp"
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#include "bias.hpp"
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#include "mask.hpp"
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#include "rotary.hpp"
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#include <type_traits>
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template <typename DataType>
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struct FmhaFwdTypeConfig;
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template <>
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struct FmhaFwdTypeConfig<ck_tile::half_t>
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{
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using QDataType = ck_tile::half_t;
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using KDataType = ck_tile::half_t;
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using VDataType = ck_tile::half_t;
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using BiasDataType = ck_tile::half_t;
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using RandValOutputDataType = uint8_t;
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using LSEDataType = float; // data type for lse(logsumexp L_j = max_j + log(l_j))
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using SaccDataType = float; // data type for first gemm accumulation
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using SMPLComputeDataType = float; // data type for reduction, softmax
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using PDataType = ck_tile::half_t; // data type for A matrix of second gemm
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using OaccDataType = float; // data type for second gemm accumulation
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using ODataType = ck_tile::half_t;
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};
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template <>
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struct FmhaFwdTypeConfig<ck_tile::bf16_t>
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{
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using QDataType = ck_tile::bf16_t;
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using KDataType = ck_tile::bf16_t;
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using VDataType = ck_tile::bf16_t;
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using BiasDataType = ck_tile::bf16_t;
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using RandValOutputDataType = uint8_t;
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using LSEDataType = float; // data type for lse(logsumexp L_j = max_j + log(l_j))
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using SaccDataType = float; // data type for first gemm accumulation
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using SMPLComputeDataType = float; // data type for reduction, softmax
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using PDataType = ck_tile::bf16_t; // data type for A matrix of second gemm
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using OaccDataType = float; // data type for second gemm accumulation
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using ODataType = ck_tile::bf16_t;
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};
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template <>
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struct FmhaFwdTypeConfig<ck_tile::fp8_t>
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{
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using QDataType = ck_tile::fp8_t;
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using KDataType = ck_tile::fp8_t;
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using VDataType = ck_tile::fp8_t;
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using BiasDataType = float;
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using RandValOutputDataType = uint8_t;
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using LSEDataType = float; // data type for lse(logsumexp L_j = max_j + log(l_j))
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using SaccDataType = float; // data type for first gemm accumulation
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using SMPLComputeDataType = float; // data type for reduction, softmax
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using PDataType = ck_tile::fp8_t; // data type for A matrix of second gemm
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using OaccDataType = float; // data type for second gemm accumulation
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using ODataType = ck_tile::fp8_t;
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};
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template <>
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struct FmhaFwdTypeConfig<ck_tile::bf8_t>
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{
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using QDataType = ck_tile::bf8_t;
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using KDataType = ck_tile::bf8_t;
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using VDataType = ck_tile::bf8_t;
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using BiasDataType = ck_tile::bf8_t;
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using RandValOutputDataType = uint8_t;
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using LSEDataType = float; // data type for lse(logsumexp L_j = max_j + log(l_j))
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using SaccDataType = float; // data type for first gemm accumulation
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using SMPLComputeDataType = float; // data type for reduction, softmax
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using PDataType = ck_tile::bf8_t; // data type for A matrix of second gemm
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using OaccDataType = float; // data type for second gemm accumulation
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using ODataType = ck_tile::bf8_t;
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};
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struct FmhaMasks
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{
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using NoMask = ck_tile::GenericAttentionMask<false>;
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using GenericMask = ck_tile::GenericAttentionMask<true, true>;
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using CausalMask = ck_tile::GenericAttentionMask<true, false>;
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};
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// runtime args, some will passed to karg, some will used to compute grids/blocks
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struct fmha_fwd_args
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{
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const void* q_ptr;
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const void* k_ptr;
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const void* v_ptr;
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const void* bias_ptr; // bias or alibi_slope pointer
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void* rand_val_ptr;
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void* lse_ptr;
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void* o_ptr;
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const void* seqstart_q_ptr;
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const void* seqstart_k_ptr;
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const void*
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seqlen_k_ptr; // only used if both 'seqstart_q_ptr' & 'seqstart_k_ptr' are not nullptr
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ck_tile::index_t seqlen_q;
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ck_tile::index_t seqlen_k;
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ck_tile::index_t batch;
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ck_tile::index_t max_seqlen_q;
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ck_tile::index_t hdim_q;
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ck_tile::index_t hdim_v;
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ck_tile::index_t nhead_q;
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ck_tile::index_t nhead_k;
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float scale_s;
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float scale_p;
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float scale_o;
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ck_tile::index_t stride_q;
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ck_tile::index_t stride_k;
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ck_tile::index_t stride_v;
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ck_tile::index_t stride_bias; // if alibi, b*h need set this to h, 1*h need set this to 0
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ck_tile::index_t stride_randval;
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ck_tile::index_t stride_o;
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ck_tile::index_t nhead_stride_q;
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ck_tile::index_t nhead_stride_k;
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ck_tile::index_t nhead_stride_v;
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ck_tile::index_t nhead_stride_bias;
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ck_tile::index_t nhead_stride_randval;
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ck_tile::index_t nhead_stride_lse;
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ck_tile::index_t nhead_stride_o;
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ck_tile::index_t batch_stride_q;
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ck_tile::index_t batch_stride_k;
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ck_tile::index_t batch_stride_v;
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ck_tile::index_t batch_stride_bias;
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ck_tile::index_t batch_stride_randval;
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ck_tile::index_t batch_stride_lse;
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ck_tile::index_t batch_stride_o;
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ck_tile::index_t window_size_left;
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ck_tile::index_t window_size_right;
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ck_tile::index_t mask_type;
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float p_drop;
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bool s_randval;
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std::tuple<uint64_t, uint64_t> drop_seed_offset;
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};
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struct fmha_fwd_splitkv_args
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{
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const void* q_ptr;
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const void* k_ptr;
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const void* v_ptr;
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const void* bias_ptr; // bias or alibi_slope pointer
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void* lse_acc_ptr;
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void* o_acc_ptr;
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void* lse_ptr;
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void* o_ptr;
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void* block_table_ptr;
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ck_tile::index_t batch_stride_block_table; // only used if 'block_table_ptr' is not nullptr
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ck_tile::index_t page_block_size; // only used if 'block_table_ptr' is not nullptr
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const void* cache_batch_idx;
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// the real seqlen_q & seqlen_k are decided by following:
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// batch mode: seqlen_q = kargs.seqlen_q
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// seqlen_k = kargs.seqlen_k
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// group mode: seqlen_q = kargs.seqstart_q_ptr[b + 1] - kargs.seqstart_q_ptr[b]
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// seqlen_k = kargs.seqstart_k_ptr[b + 1] - kargs.seqstart_k_ptr[b]
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// kvcache mode (use same kernel as batch mode):
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// seqlen_q = kargs.seqlen_q
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// seqlen_k = kargs.seqstart_k_ptr[b + 1] - kargs.seqstart_k_ptr[b]
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const void* seqstart_q_ptr;
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const void* seqstart_k_ptr;
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const void* seqlen_k_ptr;
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ck_tile::index_t seqlen_q;
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ck_tile::index_t seqlen_k;
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ck_tile::index_t batch;
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ck_tile::index_t max_seqlen_q;
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ck_tile::index_t hdim_q;
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ck_tile::index_t hdim_v;
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ck_tile::index_t nhead_q;
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ck_tile::index_t nhead_k;
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ck_tile::index_t num_splits;
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float scale_s;
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float scale_p;
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float scale_o;
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ck_tile::index_t stride_q;
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ck_tile::index_t stride_k;
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ck_tile::index_t stride_v;
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ck_tile::index_t stride_bias; // if alibi, b*h need set this to h, 1*h need set this to 0
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ck_tile::index_t stride_o_acc;
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ck_tile::index_t stride_o;
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ck_tile::index_t nhead_stride_q;
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ck_tile::index_t nhead_stride_k;
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ck_tile::index_t nhead_stride_v;
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ck_tile::index_t nhead_stride_bias;
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ck_tile::index_t nhead_stride_lse;
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ck_tile::index_t nhead_stride_lse_acc;
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ck_tile::index_t nhead_stride_o_acc;
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ck_tile::index_t nhead_stride_o;
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ck_tile::index_t batch_stride_q;
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ck_tile::index_t batch_stride_k;
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ck_tile::index_t batch_stride_v;
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ck_tile::index_t batch_stride_bias;
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ck_tile::index_t batch_stride_lse;
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ck_tile::index_t batch_stride_lse_acc;
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ck_tile::index_t batch_stride_o_acc;
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ck_tile::index_t batch_stride_o;
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ck_tile::index_t split_stride_lse_acc;
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ck_tile::index_t split_stride_o_acc;
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ck_tile::index_t window_size_left;
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ck_tile::index_t window_size_right;
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ck_tile::index_t mask_type;
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};
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struct fmha_fwd_appendkv_args
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{
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void* q_ptr;
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void* k_ptr;
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const void* knew_ptr;
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void* v_ptr;
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const void* vnew_ptr;
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const void* seqlen_k_ptr;
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ck_tile::index_t seqlen_q;
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ck_tile::index_t seqlen_knew;
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ck_tile::index_t batch;
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ck_tile::index_t hdim_q;
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ck_tile::index_t hdim_v;
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ck_tile::index_t nhead_q;
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ck_tile::index_t nhead_k;
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const void* rotary_cos_ptr; // only used if 'rotary_dim' > 0
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const void* rotary_sin_ptr; // only used if 'rotary_dim' > 0
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ck_tile::index_t rotary_dim;
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bool has_mask;
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void* block_table_ptr;
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ck_tile::index_t batch_stride_block_table; // only used if 'block_table_ptr' is not nullptr
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ck_tile::index_t page_block_size; // only used if 'block_table_ptr' is not nullptr
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const void* cache_batch_idx;
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ck_tile::index_t stride_q;
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ck_tile::index_t stride_k;
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ck_tile::index_t stride_knew;
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ck_tile::index_t stride_v;
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ck_tile::index_t stride_vnew;
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ck_tile::index_t nhead_stride_q;
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ck_tile::index_t nhead_stride_k;
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ck_tile::index_t nhead_stride_knew;
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ck_tile::index_t nhead_stride_v;
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ck_tile::index_t nhead_stride_vnew;
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ck_tile::index_t batch_stride_q;
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ck_tile::index_t batch_stride_k;
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ck_tile::index_t batch_stride_knew;
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ck_tile::index_t batch_stride_v;
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ck_tile::index_t batch_stride_vnew;
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};
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template <typename FmhaKernel>
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auto fmha_fwd_create_kargs_and_grids(fmha_fwd_args args)
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{
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assert(args.nhead_q % args.nhead_k == 0);
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auto kargs = [&] {
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// create group mode kernel arguments
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if constexpr(FmhaKernel::kIsGroupMode)
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{
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return FmhaKernel::MakeKargs(args.q_ptr,
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args.k_ptr,
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args.v_ptr,
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args.bias_ptr,
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args.rand_val_ptr,
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args.lse_ptr,
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args.o_ptr,
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args.seqstart_q_ptr,
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args.seqstart_k_ptr,
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args.seqlen_k_ptr,
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args.hdim_q,
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args.hdim_v,
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args.nhead_q,
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args.nhead_q / args.nhead_k,
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args.scale_s,
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args.scale_p,
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args.scale_o,
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args.stride_q,
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args.stride_k,
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args.stride_v,
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args.stride_bias,
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args.stride_randval,
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args.stride_o,
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args.nhead_stride_q,
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args.nhead_stride_k,
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args.nhead_stride_v,
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args.nhead_stride_bias,
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args.nhead_stride_randval,
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args.nhead_stride_lse,
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args.nhead_stride_o,
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args.window_size_left,
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args.window_size_right,
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args.mask_type,
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args.p_drop,
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args.s_randval,
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args.drop_seed_offset);
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}
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else
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{ // create batch mode kernel arguments
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return FmhaKernel::MakeKargs(args.q_ptr,
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args.k_ptr,
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args.v_ptr,
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args.bias_ptr,
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args.rand_val_ptr,
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args.lse_ptr,
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args.o_ptr,
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args.seqlen_q,
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args.seqlen_k,
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args.hdim_q,
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args.hdim_v,
|
|
args.nhead_q,
|
|
args.nhead_q / args.nhead_k,
|
|
args.scale_s,
|
|
args.scale_p,
|
|
args.scale_o,
|
|
args.stride_q,
|
|
args.stride_k,
|
|
args.stride_v,
|
|
args.stride_bias,
|
|
args.stride_randval,
|
|
args.stride_o,
|
|
args.nhead_stride_q,
|
|
args.nhead_stride_k,
|
|
args.nhead_stride_v,
|
|
args.nhead_stride_bias,
|
|
args.nhead_stride_randval,
|
|
args.nhead_stride_lse,
|
|
args.nhead_stride_o,
|
|
args.batch_stride_q,
|
|
args.batch_stride_k,
|
|
args.batch_stride_v,
|
|
args.batch_stride_bias,
|
|
args.batch_stride_randval,
|
|
args.batch_stride_lse,
|
|
args.batch_stride_o,
|
|
args.window_size_left,
|
|
args.window_size_right,
|
|
args.mask_type,
|
|
args.p_drop,
|
|
args.s_randval,
|
|
args.drop_seed_offset);
|
|
}
|
|
}();
|
|
|
|
dim3 grids = FmhaKernel::GridSize(args.batch, args.nhead_q, args.max_seqlen_q, args.hdim_v);
|
|
return ck_tile::make_tuple(kargs, grids);
|
|
}
|
|
|
|
template <typename Kernel>
|
|
auto fmha_fwd_splitkv_create_kargs_and_grids(fmha_fwd_splitkv_args args)
|
|
{
|
|
assert(args.nhead_q % args.nhead_k == 0);
|
|
auto kargs = [&] {
|
|
// create group mode kernel arguments
|
|
if constexpr(Kernel::kIsGroupMode)
|
|
{
|
|
return Kernel::MakeKargs(args.q_ptr,
|
|
args.k_ptr,
|
|
args.v_ptr,
|
|
args.bias_ptr,
|
|
args.lse_acc_ptr,
|
|
args.o_acc_ptr,
|
|
args.batch,
|
|
args.seqstart_q_ptr,
|
|
args.seqstart_k_ptr,
|
|
args.seqlen_k_ptr,
|
|
args.hdim_q,
|
|
args.hdim_v,
|
|
args.nhead_q,
|
|
args.nhead_q / args.nhead_k,
|
|
args.num_splits,
|
|
args.scale_s,
|
|
args.scale_p,
|
|
args.stride_q,
|
|
args.stride_k,
|
|
args.stride_v,
|
|
args.stride_bias,
|
|
args.stride_o_acc,
|
|
args.nhead_stride_q,
|
|
args.nhead_stride_k,
|
|
args.nhead_stride_v,
|
|
args.nhead_stride_bias,
|
|
args.nhead_stride_lse_acc,
|
|
args.nhead_stride_o_acc,
|
|
args.batch_stride_k,
|
|
args.batch_stride_v,
|
|
args.batch_stride_lse_acc,
|
|
args.batch_stride_o_acc,
|
|
args.split_stride_lse_acc,
|
|
args.split_stride_o_acc,
|
|
args.window_size_left,
|
|
args.window_size_right,
|
|
args.mask_type);
|
|
}
|
|
else
|
|
{ // create batch mode kernel arguments
|
|
return Kernel::MakeKargs(args.q_ptr,
|
|
args.k_ptr,
|
|
args.v_ptr,
|
|
args.bias_ptr,
|
|
args.lse_acc_ptr,
|
|
args.o_acc_ptr,
|
|
args.batch,
|
|
args.seqlen_q,
|
|
args.seqlen_k,
|
|
args.seqlen_k_ptr,
|
|
args.hdim_q,
|
|
args.hdim_v,
|
|
args.nhead_q,
|
|
args.nhead_q / args.nhead_k,
|
|
args.num_splits,
|
|
args.block_table_ptr,
|
|
args.batch_stride_block_table,
|
|
args.page_block_size,
|
|
args.cache_batch_idx,
|
|
args.scale_s,
|
|
args.scale_p,
|
|
args.stride_q,
|
|
args.stride_k,
|
|
args.stride_v,
|
|
args.stride_bias,
|
|
args.stride_o_acc,
|
|
args.nhead_stride_q,
|
|
args.nhead_stride_k,
|
|
args.nhead_stride_v,
|
|
args.nhead_stride_bias,
|
|
args.nhead_stride_lse_acc,
|
|
args.nhead_stride_o_acc,
|
|
args.batch_stride_q,
|
|
args.batch_stride_k,
|
|
args.batch_stride_v,
|
|
args.batch_stride_bias,
|
|
args.batch_stride_lse_acc,
|
|
args.batch_stride_o_acc,
|
|
args.split_stride_lse_acc,
|
|
args.split_stride_o_acc,
|
|
args.window_size_left,
|
|
args.window_size_right,
|
|
args.mask_type);
|
|
}
|
|
}();
|
|
|
|
dim3 grids =
|
|
Kernel::GridSize(args.batch, args.nhead_q, args.max_seqlen_q, args.hdim_v, args.num_splits);
|
|
|
|
return ck_tile::make_tuple(kargs, grids);
|
|
}
|
|
|
|
template <typename Kernel>
|
|
auto fmha_fwd_splitkv_combine_create_kargs_and_grids(fmha_fwd_splitkv_args args)
|
|
{
|
|
assert(args.nhead_q % args.nhead_k == 0);
|
|
auto kargs = [&] {
|
|
// create group mode kernel argumentszs
|
|
if constexpr(Kernel::kIsGroupMode)
|
|
{
|
|
return Kernel::MakeKargs(args.lse_acc_ptr,
|
|
args.o_acc_ptr,
|
|
args.lse_ptr,
|
|
args.o_ptr,
|
|
args.batch,
|
|
args.max_seqlen_q,
|
|
args.seqstart_q_ptr,
|
|
args.hdim_v,
|
|
args.num_splits,
|
|
args.scale_o,
|
|
args.stride_o_acc,
|
|
args.stride_o,
|
|
args.nhead_stride_lse_acc,
|
|
args.nhead_stride_o_acc,
|
|
args.nhead_stride_lse,
|
|
args.nhead_stride_o,
|
|
args.batch_stride_o_acc,
|
|
args.split_stride_lse_acc,
|
|
args.split_stride_o_acc);
|
|
}
|
|
else
|
|
{ // create batch mode kernel arguments
|
|
return Kernel::MakeKargs(args.lse_acc_ptr,
|
|
args.o_acc_ptr,
|
|
args.lse_ptr,
|
|
args.o_ptr,
|
|
args.batch,
|
|
args.max_seqlen_q,
|
|
args.seqlen_q,
|
|
args.hdim_v,
|
|
args.num_splits,
|
|
args.scale_o,
|
|
args.stride_o_acc,
|
|
args.stride_o,
|
|
args.nhead_stride_lse_acc,
|
|
args.nhead_stride_o_acc,
|
|
args.nhead_stride_lse,
|
|
args.nhead_stride_o,
|
|
args.batch_stride_lse_acc,
|
|
args.batch_stride_o_acc,
|
|
args.batch_stride_lse,
|
|
args.batch_stride_o,
|
|
args.split_stride_lse_acc,
|
|
args.split_stride_o_acc);
|
|
}
|
|
}();
|
|
|
|
dim3 grids = Kernel::GridSize(args.batch, args.nhead_q, args.max_seqlen_q, args.hdim_v);
|
|
|
|
return ck_tile::make_tuple(kargs, grids);
|
|
}
|
|
|
|
template <typename Kernel>
|
|
auto fmha_fwd_appendkv_create_kargs_and_grids(fmha_fwd_appendkv_args args)
|
|
{
|
|
assert(args.nhead_q % args.nhead_k == 0);
|
|
auto kargs = Kernel::MakeKargs(args.q_ptr,
|
|
args.k_ptr,
|
|
args.knew_ptr,
|
|
args.v_ptr,
|
|
args.vnew_ptr,
|
|
args.seqlen_q,
|
|
args.seqlen_k_ptr,
|
|
args.seqlen_knew,
|
|
args.hdim_q,
|
|
args.hdim_v,
|
|
args.nhead_q,
|
|
args.nhead_q / args.nhead_k,
|
|
args.rotary_cos_ptr,
|
|
args.rotary_sin_ptr,
|
|
args.rotary_dim,
|
|
args.has_mask,
|
|
args.block_table_ptr,
|
|
args.batch_stride_block_table,
|
|
args.page_block_size,
|
|
args.cache_batch_idx,
|
|
args.stride_q,
|
|
args.stride_k,
|
|
args.stride_knew,
|
|
args.stride_v,
|
|
args.stride_vnew,
|
|
args.nhead_stride_q,
|
|
args.nhead_stride_k,
|
|
args.nhead_stride_knew,
|
|
args.nhead_stride_v,
|
|
args.nhead_stride_vnew,
|
|
args.batch_stride_q,
|
|
args.batch_stride_k,
|
|
args.batch_stride_knew,
|
|
args.batch_stride_v,
|
|
args.batch_stride_vnew);
|
|
|
|
dim3 grids = Kernel::GridSize(args.batch, args.nhead_q, args.seqlen_q, args.seqlen_knew);
|
|
|
|
return ck_tile::make_tuple(kargs, grids);
|
|
}
|
|
|
|
// this is used to pattern-match internl kernel implementation, not to instantiate kernel
|
|
template <ck_tile::index_t HDim_,
|
|
typename DataType_,
|
|
bool kIsGroupMode_,
|
|
ck_tile::index_t kM0_,
|
|
ck_tile::index_t kN0_,
|
|
ck_tile::index_t kK0_,
|
|
ck_tile::index_t kN1_,
|
|
ck_tile::index_t kK1_,
|
|
ck_tile::index_t kK0BlockLength_,
|
|
bool kIsVLayoutRowMajor_,
|
|
ck_tile::BlockFmhaPipelineEnum FmhaPipelineEnum_,
|
|
typename FmhaMask_,
|
|
ck_tile::BlockAttentionBiasEnum BiasEnum_,
|
|
bool kStoreLse_,
|
|
bool kHasDropout_,
|
|
bool kDoFp8StaticQuant_,
|
|
bool kPadS_,
|
|
bool kPadSK_,
|
|
bool kPadD_,
|
|
bool kPadDv_>
|
|
struct fmha_fwd_traits_
|
|
{
|
|
static constexpr ck_tile::index_t HDim = HDim_;
|
|
using DataType = ck_tile::remove_cvref_t<DataType_>;
|
|
static constexpr bool kIsGroupMode = kIsGroupMode_;
|
|
static constexpr ck_tile::index_t kM0 = kM0_;
|
|
static constexpr ck_tile::index_t kN0 = kN0_;
|
|
static constexpr ck_tile::index_t kK0 = kK0_;
|
|
static constexpr ck_tile::index_t kN1 = kN1_;
|
|
static constexpr ck_tile::index_t kK1 = kK1_;
|
|
static constexpr ck_tile::index_t kK0BlockLength = kK0BlockLength_;
|
|
static constexpr bool kIsVLayoutRowMajor = kIsVLayoutRowMajor_;
|
|
static constexpr auto FmhaPipelineEnum = FmhaPipelineEnum_;
|
|
using FmhaMask = ck_tile::remove_cvref_t<FmhaMask_>;
|
|
static constexpr auto BiasEnum = BiasEnum_;
|
|
static constexpr bool kStoreLse = kStoreLse_;
|
|
static constexpr bool kHasDropout = kHasDropout_;
|
|
static constexpr bool kDoFp8StaticQuant = kDoFp8StaticQuant_;
|
|
static constexpr bool kPadS = kPadS_;
|
|
static constexpr bool kPadSK = kPadSK_;
|
|
static constexpr bool kPadD = kPadD_;
|
|
static constexpr bool kPadDv = kPadDv_;
|
|
};
|
|
|
|
template <typename Traits_>
|
|
float fmha_fwd_(const ck_tile::stream_config&, fmha_fwd_args);
|
|
|
|
template <ck_tile::index_t HDim_,
|
|
typename DataType_,
|
|
bool kIsGroupMode_,
|
|
ck_tile::index_t kM0_,
|
|
ck_tile::index_t kN0_,
|
|
ck_tile::index_t kK0_,
|
|
ck_tile::index_t kN1_,
|
|
ck_tile::index_t kK1_,
|
|
ck_tile::index_t kK0BlockLength_,
|
|
bool kIsVLayoutRowMajor_,
|
|
ck_tile::BlockFmhaPipelineEnum FmhaPipelineEnum_,
|
|
typename FmhaMask_,
|
|
ck_tile::BlockAttentionBiasEnum BiasEnum_,
|
|
bool kStoreLse_,
|
|
bool kDoFp8StaticQuant_,
|
|
bool kIsPagedKV_,
|
|
bool kPadS_,
|
|
bool kPadSK_,
|
|
bool kPadD_,
|
|
bool kPadDv_>
|
|
struct fmha_fwd_splitkv_traits_
|
|
{
|
|
static constexpr ck_tile::index_t HDim = HDim_;
|
|
using DataType = ck_tile::remove_cvref_t<DataType_>;
|
|
static constexpr bool kIsGroupMode = kIsGroupMode_;
|
|
static constexpr ck_tile::index_t kM0 = kM0_;
|
|
static constexpr ck_tile::index_t kN0 = kN0_;
|
|
static constexpr ck_tile::index_t kK0 = kK0_;
|
|
static constexpr ck_tile::index_t kN1 = kN1_;
|
|
static constexpr ck_tile::index_t kK1 = kK1_;
|
|
static constexpr ck_tile::index_t kK0BlockLength = kK0BlockLength_;
|
|
static constexpr bool kIsVLayoutRowMajor = kIsVLayoutRowMajor_;
|
|
static constexpr auto FmhaPipelineEnum = FmhaPipelineEnum_;
|
|
using FmhaMask = ck_tile::remove_cvref_t<FmhaMask_>;
|
|
static constexpr auto BiasEnum = BiasEnum_;
|
|
static constexpr bool kStoreLse = kStoreLse_;
|
|
static constexpr bool kDoFp8StaticQuant = kDoFp8StaticQuant_;
|
|
static constexpr bool kPadS = kPadS_;
|
|
static constexpr bool kPadSK = kPadSK_;
|
|
static constexpr bool kPadD = kPadD_;
|
|
static constexpr bool kPadDv = kPadDv_;
|
|
static constexpr bool kIsPagedKV = kIsPagedKV_;
|
|
};
|
|
|
|
template <typename Traits_>
|
|
void fmha_fwd_splitkv_oneshot_(const ck_tile::stream_config&, fmha_fwd_splitkv_args);
|
|
|
|
template <typename Traits_>
|
|
std::string fmha_fwd_splitkv_get_name_();
|
|
|
|
template <ck_tile::index_t HDim_,
|
|
typename DataType_,
|
|
bool kIsGroupMode_,
|
|
ck_tile::index_t kM0_,
|
|
ck_tile::index_t kN1_,
|
|
bool kStoreLse_,
|
|
bool kDoFp8StaticQuant_,
|
|
bool kPadS_,
|
|
bool kPadDv_>
|
|
struct fmha_fwd_splitkv_combine_traits_
|
|
{
|
|
static constexpr ck_tile::index_t HDim = HDim_;
|
|
using DataType = ck_tile::remove_cvref_t<DataType_>;
|
|
static constexpr bool kIsGroupMode = kIsGroupMode_;
|
|
static constexpr ck_tile::index_t kM0 = kM0_;
|
|
static constexpr ck_tile::index_t kN1 = kN1_;
|
|
static constexpr bool kStoreLse = kStoreLse_;
|
|
static constexpr bool kDoFp8StaticQuant = kDoFp8StaticQuant_;
|
|
static constexpr bool kPadS = kPadS_;
|
|
static constexpr bool kPadDv = kPadDv_;
|
|
};
|
|
|
|
template <typename Traits_>
|
|
void fmha_fwd_splitkv_combine_oneshot_(const ck_tile::stream_config&, fmha_fwd_splitkv_args);
|
|
|
|
template <typename Traits_>
|
|
std::string fmha_fwd_splitkv_combine_get_name_();
|
|
|
|
// this is used to pattern-match internl kernel implementation, not to instantiate kernel
|
|
template <ck_tile::index_t HDim_,
|
|
typename DataType_,
|
|
ck_tile::index_t kTileSizeS_,
|
|
ck_tile::index_t kTileSizeSk_,
|
|
ck_tile::index_t kTileSizeD_,
|
|
ck_tile::index_t kTileSizeDv_,
|
|
bool kIsVLayoutRowMajor_,
|
|
bool kPadS_,
|
|
bool kPadSk_,
|
|
bool kPadD_,
|
|
bool kPadDv_,
|
|
ck_tile::RotaryEmbeddingEnum RotaryEnum_,
|
|
bool kIsPagedKV_>
|
|
struct fmha_fwd_appendkv_traits_
|
|
{
|
|
static constexpr ck_tile::index_t HDim = HDim_;
|
|
using DataType = ck_tile::remove_cvref_t<DataType_>;
|
|
static constexpr ck_tile::index_t kTileSizeS = kTileSizeS_;
|
|
static constexpr ck_tile::index_t kTileSizeSk = kTileSizeSk_;
|
|
static constexpr ck_tile::index_t kTileSizeD = kTileSizeD_;
|
|
static constexpr ck_tile::index_t kTileSizeDv = kTileSizeDv_;
|
|
static constexpr bool kIsVLayoutRowMajor = kIsVLayoutRowMajor_;
|
|
static constexpr bool kPadS = kPadS_;
|
|
static constexpr bool kPadSk = kPadSk_;
|
|
static constexpr bool kPadD = kPadD_;
|
|
static constexpr bool kPadDv = kPadDv_;
|
|
static constexpr auto RotaryEnum = RotaryEnum_;
|
|
static constexpr bool kIsPagedKV = kIsPagedKV_;
|
|
};
|
|
|
|
template <typename Traits_>
|
|
float fmha_fwd_appendkv_(const ck_tile::stream_config&, fmha_fwd_appendkv_args);
|
|
|
|
// This is the public API, will be generated by script
|
|
struct fmha_fwd_traits
|
|
{
|
|
int hdim_q;
|
|
int hdim_v;
|
|
std::string data_type;
|
|
bool is_group_mode;
|
|
bool is_v_rowmajor;
|
|
mask_enum mask_type;
|
|
bias_enum bias_type; // 0:no bias, 1:elementwise bias, 2:alibi. sync with BlockAttentionBiasEnum
|
|
bool has_lse;
|
|
bool has_dropout;
|
|
bool do_fp8_static_quant;
|
|
// TODO: padding check is inside this api
|
|
};
|
|
float fmha_fwd(fmha_fwd_traits, fmha_fwd_args, const ck_tile::stream_config&);
|
|
|
|
struct fmha_fwd_splitkv_traits
|
|
{
|
|
int hdim_q;
|
|
int hdim_v;
|
|
std::string data_type;
|
|
bool is_group_mode;
|
|
bool is_v_rowmajor;
|
|
mask_enum mask_type;
|
|
bias_enum bias_type; // 0:no bias, 1:elementwise bias, 2:alibi. sync with BlockAttentionBiasEnum
|
|
bool has_lse;
|
|
bool do_fp8_static_quant;
|
|
// TODO: padding check is inside this api
|
|
};
|
|
float fmha_fwd_splitkv(fmha_fwd_splitkv_traits,
|
|
fmha_fwd_splitkv_args,
|
|
const ck_tile::stream_config&);
|
|
|
|
struct fmha_fwd_appendkv_traits
|
|
{
|
|
int hdim_q;
|
|
int hdim_v;
|
|
std::string data_type;
|
|
bool is_v_rowmajor;
|
|
rope_enum rope_type;
|
|
};
|
|
float fmha_fwd_appendkv(fmha_fwd_appendkv_traits,
|
|
fmha_fwd_appendkv_args,
|
|
const ck_tile::stream_config&);
|