mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-03 05:01:25 +00:00
05292b3604
* Let fmha_fwd_v3() compatible with fmha_fwd() * Decouple get_fwd_blobs() and FmhaFwdKernel * Decouple compatibility checks from get_fwd_blobs() * Extract product feature checks out from get_fwd_blobs() * Remove duplicated code in factories and redundant checks * Remove FmhaFwdKernel<>::GetName() * Let FmhaFwdApiPool support pipelines with different mask_impl * Add tile setting for fmha fwd v3 pipeline * Add fwd v3 instances to tile_example_fmha_fwd manually * Remove unused function import * Undo irrelevant changes * Remove fwd v3 instances from tile_example_fmha_fwd * Finish fmha fwd v3 kernel instance codegen * Fix formatting * Remove unused F_idx attribute * Add is_generic_attention_mask<> traits * Add constraints to the fmha fwd v3 pipeline * Unify traits & problem used for fmha fwd v3 * Unify kernel launch code for fmha fwd v2 & v3 * Unify kernel template selection logic * Use same kernel codegen template for both v2 & v3 * Rename api() property as render() method * Allow specifying filter for fmha fwd api pool * Allow specifying function name when rendering api pool items * Separate fmha fwd v3 kernel dispatching logic from v2 * Remove lambda assignment * Add simple v2/v3 dispatch logic * Stop generating empty if-clauses Skip iterating over dictionaries that have no traits, and avoid assigning i_* to them. * Use "".join() to concatenate fmha fwd api string content * Add more feature checks for fmha fwd v3 pipeline * Check features before dispatch to fmha_fwd_v3() * Add more feature checks for fmha_fwd_v3() * Add missing filter call * Use Tuple to reserve the dtype orders * Fix wrong pipeline matching logic * Add fmha fwd v3 group mode instances * Add functor_transform<> * Add type constraints to make_tile_window() * Remove fmha fwd v3 example * Fix wrong product(aiter mha_fwd()) config * Fix wrong fmha fwd v2/v3 selection logic * Fix formatting * Add comment to warning v3 kernel users * Fix wrong codegen logics * Remove unnecessary param * Fix format --------- Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
1502 lines
64 KiB
C++
1502 lines
64 KiB
C++
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#pragma once
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#include "ck_tile/core.hpp"
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#include "ck_tile/host/device_prop.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 "quant.hpp"
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#include "rotary.hpp"
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#include <type_traits>
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#include <utility>
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#include <variant>
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struct FmhaFwdFp32
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{
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};
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struct FmhaFwdFp16
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{
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};
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struct FmhaFwdBf16
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{
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};
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struct FmhaFwdFp8
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{
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};
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struct FmhaFwdBf8
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{
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};
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struct FmhaFwdFp8Fp16
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{
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};
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struct FmhaFwdFp8Bf16
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{
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};
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struct FmhaFwdFp8Fp32
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{
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};
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template <typename DataType>
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struct FmhaFwdTypeConfig;
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template <>
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struct FmhaFwdTypeConfig<FmhaFwdFp32>
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{
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using QDataType = float;
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using KDataType = float;
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using VDataType = float;
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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 = float; // 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 = float;
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};
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template <>
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struct FmhaFwdTypeConfig<FmhaFwdFp16>
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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<FmhaFwdBf16>
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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<FmhaFwdFp8>
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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<FmhaFwdBf8>
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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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template <>
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struct FmhaFwdTypeConfig<FmhaFwdFp8Bf16>
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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::bf16_t;
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};
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template <>
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struct FmhaFwdTypeConfig<FmhaFwdFp8Fp32>
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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 = float;
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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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const void* q_descale_ptr;
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const void* k_descale_ptr;
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const void* v_descale_ptr;
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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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// Usage notes for sequence length pointer parameters:
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//
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// [Note: Define "Group mode" vs "Batch mode" here if possible, e.g., "Group mode handles
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// MQA/GQA..."]
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//
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// With padding:
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// Group mode:
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// - seqstart_q_ptr, seqstart_k_ptr: Record cumulative physical (including padding) sequence
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// lengths. [array size: batch + 1]
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// - seqlen_q_ptr/seqlen_k_ptr: Records logical (excluding padding) length for each
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// sequence. [array size: batch]
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// - cu_seqlen_q_ptr/cu_seqlen_k_ptr: Records cumulative logical (excluding padding)
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// sequence lengths. [array size: batch + 1]
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// - seqlen_q_ptr (per-sequence) and cu_seqlen_q_ptr (cumulative logical) are mutually
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// exclusive. Use one set, not both.
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//
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// Batch mode:
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// - cu_seqlen_q_ptr/cu_seqlen_k_ptr: Records cumulative logical (excluding padding)
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// sequence lengths. [array size: batch + 1]
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// - seqstart_* and seqlen_* pointers must be nullptr.
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//
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// Without padding:
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// (Note: Physical length equals logical length)
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//
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// Group mode:
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// - seqstart_q_ptr, seqstart_k_ptr: Record cumulative physical sequence lengths. [array
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// size: batch + 1]
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// - seqlen_q_ptr/seqlen_k_ptr and cu_seqlen_q_ptr/cu_seqlen_k_ptr must be nullptr.
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//
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// Batch mode:
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// - All sequence length pointers (seqstart_*, seqlen_*, cu_seqlen_*) must be nullptr.
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//
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const void* seqstart_q_ptr =
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nullptr; // Cumulative physical sequence length array [batch + 1]. (Used in Group mode)
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const void* seqstart_k_ptr =
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nullptr; // Cumulative physical sequence length array [batch + 1]. (Used in Group mode)
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const void* seqlen_q_ptr = nullptr; // Per-sequence logical (excluding padding) length array
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// [batch]. (Used in Group mode with padding)
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const void* seqlen_k_ptr = nullptr; // Per-sequence logical (excluding padding) length array
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// [batch]. (Used in Group mode with padding)
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const void* cu_seqlen_q_ptr = nullptr; // Cumulative logical (excluding padding) sequence length
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// array [batch + 1]. (Used with padding)
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const void* cu_seqlen_k_ptr = nullptr; // Cumulative logical (excluding padding) sequence length
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// array [batch + 1]. (Used with padding)
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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 logits_soft_cap;
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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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ck_tile::index_t min_seqlen_q;
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float p_drop;
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bool s_randval;
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std::variant<std::pair<uint64_t, uint64_t>, std::pair<const void*, const void*>>
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drop_seed_offset;
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};
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struct fmha_fwd_pagedkv_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_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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bool is_gappy; // differentiate seqstart_k_ptr usage. only used if 'block_table_ptr' is not
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// 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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// or kargs.seqlen_k_ptr[b]
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//
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// batch mode (kvcache):
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// seqlen_q = kargs.seqlen_q
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// seqlen_k = kargs.seqlen_k_ptr[b]
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// group mode (kvcache):
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// seqlen_q = kargs.seqstart_q_ptr[b + 1] - kargs.seqstart_q_ptr[b]
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//
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// when is_gappy=true:
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// seqlen_k = kargs.seqlen_k_ptr[b]
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// seqstart_k_ptr[b] now store local offset of each batch
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//
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// when is_gappy=false:
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// seqlen_k = kargs.seqstart_k_ptr[b + 1] - kargs.seqstart_k_ptr[b]
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// or kargs.seqlen_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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float scale_s;
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float scale_p;
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float scale_o;
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float logits_soft_cap;
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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;
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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_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_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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ck_tile::index_t min_seqlen_q;
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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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bool is_gappy; // differentiate seqstart_k_ptr usage. only used if 'block_table_ptr' is not
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// 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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// or kargs.seqlen_k_ptr[b]
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//
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// batch mode (kvcache):
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// seqlen_q = kargs.seqlen_q
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// seqlen_k = kargs.seqlen_k_ptr[b]
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// group mode (kvcache):
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// seqlen_q = kargs.seqstart_q_ptr[b + 1] - kargs.seqstart_q_ptr[b]
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//
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// when is_gappy=true:
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// seqlen_k = kargs.seqlen_k_ptr[b]
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// seqstart_k_ptr[b] now store local offset of each batch
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//
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// when is_gappy=false:
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// seqlen_k = kargs.seqstart_k_ptr[b + 1] - kargs.seqstart_k_ptr[b]
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// or kargs.seqlen_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;
|
|
ck_tile::index_t max_seqlen_q;
|
|
ck_tile::index_t hdim_q;
|
|
ck_tile::index_t hdim_v;
|
|
ck_tile::index_t nhead_q;
|
|
ck_tile::index_t nhead_k;
|
|
ck_tile::index_t num_splits;
|
|
|
|
float scale_s;
|
|
float scale_p;
|
|
float scale_o;
|
|
|
|
float logits_soft_cap;
|
|
|
|
ck_tile::index_t stride_q;
|
|
ck_tile::index_t stride_k;
|
|
ck_tile::index_t stride_v;
|
|
ck_tile::index_t stride_bias; // if alibi, b*h need set this to h, 1*h need set this to 0
|
|
ck_tile::index_t stride_o_acc;
|
|
ck_tile::index_t stride_o;
|
|
ck_tile::index_t nhead_stride_q;
|
|
ck_tile::index_t nhead_stride_k;
|
|
ck_tile::index_t nhead_stride_v;
|
|
ck_tile::index_t nhead_stride_bias;
|
|
ck_tile::index_t nhead_stride_lse;
|
|
ck_tile::index_t nhead_stride_lse_acc;
|
|
ck_tile::index_t nhead_stride_o_acc;
|
|
ck_tile::index_t nhead_stride_o;
|
|
ck_tile::index_t batch_stride_q;
|
|
ck_tile::index_t batch_stride_k;
|
|
ck_tile::index_t batch_stride_v;
|
|
ck_tile::index_t batch_stride_bias;
|
|
ck_tile::index_t batch_stride_lse;
|
|
ck_tile::index_t batch_stride_lse_acc;
|
|
ck_tile::index_t batch_stride_o_acc;
|
|
ck_tile::index_t batch_stride_o;
|
|
ck_tile::index_t split_stride_lse_acc;
|
|
ck_tile::index_t split_stride_o_acc;
|
|
|
|
ck_tile::index_t window_size_left;
|
|
ck_tile::index_t window_size_right;
|
|
ck_tile::index_t mask_type;
|
|
};
|
|
|
|
struct fmha_fwd_appendkv_args
|
|
{
|
|
void* q_ptr;
|
|
void* k_ptr;
|
|
const void* knew_ptr;
|
|
void* v_ptr;
|
|
const void* vnew_ptr;
|
|
|
|
const void* seqlen_k_ptr;
|
|
|
|
ck_tile::index_t seqlen_q;
|
|
ck_tile::index_t seqlen_knew;
|
|
ck_tile::index_t batch;
|
|
ck_tile::index_t hdim_q;
|
|
ck_tile::index_t hdim_v;
|
|
ck_tile::index_t nhead_q;
|
|
ck_tile::index_t nhead_k;
|
|
|
|
const void* rotary_cos_ptr; // only used if 'rotary_dim' > 0
|
|
const void* rotary_sin_ptr; // only used if 'rotary_dim' > 0
|
|
ck_tile::index_t rotary_dim;
|
|
bool has_mask;
|
|
|
|
void* block_table_ptr;
|
|
ck_tile::index_t batch_stride_block_table; // only used if 'block_table_ptr' is not nullptr
|
|
ck_tile::index_t page_block_size; // only used if 'block_table_ptr' is not nullptr
|
|
|
|
const void* cache_batch_idx; // only used if block_table_ptr is nullptr -> batch mode (kvcache)
|
|
|
|
ck_tile::index_t stride_q;
|
|
ck_tile::index_t stride_k;
|
|
ck_tile::index_t stride_knew;
|
|
ck_tile::index_t stride_v;
|
|
ck_tile::index_t stride_vnew;
|
|
ck_tile::index_t nhead_stride_q;
|
|
ck_tile::index_t nhead_stride_k;
|
|
ck_tile::index_t nhead_stride_knew;
|
|
ck_tile::index_t nhead_stride_v;
|
|
ck_tile::index_t nhead_stride_vnew;
|
|
ck_tile::index_t batch_stride_q;
|
|
ck_tile::index_t batch_stride_k;
|
|
ck_tile::index_t batch_stride_knew;
|
|
ck_tile::index_t batch_stride_v;
|
|
ck_tile::index_t batch_stride_vnew;
|
|
};
|
|
|
|
struct fmha_batch_prefill_args
|
|
{
|
|
const void* q_ptr;
|
|
const void* k_ptr;
|
|
const void* v_ptr;
|
|
const void* bias_ptr; // bias or alibi_slope pointer
|
|
void* rand_val_ptr;
|
|
void* lse_ptr;
|
|
void* o_ptr;
|
|
|
|
// the real seqlen_q & seqlen_k are decided by following:
|
|
// batch mode (kvcache):
|
|
// seqlen_q = kargs.seqlen_q
|
|
// seqlen_k = kargs.page_block_size * (kargs.kv_indptr[b + 1] - kargs.kv_indptr[b] -
|
|
// 1) +
|
|
// kargs.kv_last_page_lens[b]
|
|
// group mode (kvcache):
|
|
// seqlen_q = kargs.seqstart_q_ptr[b + 1] - kargs.seqstart_q_ptr[b]
|
|
// seqlen_k = kargs.page_block_size * (kargs.kv_indptr[b + 1] - kargs.kv_indptr[b] -
|
|
// 1) +
|
|
// kargs.kv_last_page_lens[b]
|
|
const void* seqstart_q_ptr;
|
|
|
|
ck_tile::index_t seqlen_q;
|
|
ck_tile::index_t seqlen_k;
|
|
ck_tile::index_t batch;
|
|
ck_tile::index_t max_seqlen_q;
|
|
ck_tile::index_t hdim_q;
|
|
ck_tile::index_t hdim_v;
|
|
ck_tile::index_t nhead_q;
|
|
ck_tile::index_t nhead_k;
|
|
|
|
// SGLang-style page table
|
|
int32_t num_total_pages;
|
|
void* kv_indptr;
|
|
void* kv_page_indices;
|
|
#if 0 // we assume page_block_size=1 for now
|
|
void* kv_last_page_lens;
|
|
ck_tile::index_t page_block_size;
|
|
#endif
|
|
|
|
float scale_s;
|
|
float scale_p;
|
|
float scale_o;
|
|
|
|
float logits_soft_cap;
|
|
|
|
ck_tile::index_t stride_q;
|
|
ck_tile::index_t stride_k;
|
|
ck_tile::index_t stride_v;
|
|
ck_tile::index_t stride_bias; // if alibi, b*h need set this to h, 1*h need set this to 0
|
|
ck_tile::index_t stride_randval;
|
|
ck_tile::index_t stride_o;
|
|
ck_tile::index_t nhead_stride_q;
|
|
ck_tile::index_t nhead_stride_k;
|
|
ck_tile::index_t nhead_stride_v;
|
|
ck_tile::index_t nhead_stride_bias;
|
|
ck_tile::index_t nhead_stride_randval;
|
|
ck_tile::index_t nhead_stride_lse;
|
|
ck_tile::index_t nhead_stride_o;
|
|
ck_tile::index_t batch_stride_q;
|
|
ck_tile::index_t batch_stride_k;
|
|
ck_tile::index_t batch_stride_v;
|
|
ck_tile::index_t batch_stride_bias;
|
|
ck_tile::index_t batch_stride_randval;
|
|
ck_tile::index_t batch_stride_lse;
|
|
ck_tile::index_t batch_stride_o;
|
|
|
|
ck_tile::index_t window_size_left;
|
|
ck_tile::index_t window_size_right;
|
|
ck_tile::index_t mask_type;
|
|
|
|
float p_drop;
|
|
bool s_randval;
|
|
|
|
std::variant<std::pair<uint64_t, uint64_t>, std::pair<const void*, const void*>>
|
|
drop_seed_offset;
|
|
};
|
|
|
|
template <typename FmhaKernel>
|
|
auto fmha_fwd_create_kargs_and_grids(fmha_fwd_args args)
|
|
{
|
|
assert(args.nhead_q % args.nhead_k == 0);
|
|
auto kargs = [&] {
|
|
// create group mode kernel arguments
|
|
if constexpr(FmhaKernel::kIsGroupMode)
|
|
{
|
|
return FmhaKernel::MakeKargsImpl(args.q_ptr,
|
|
args.k_ptr,
|
|
args.v_ptr,
|
|
args.bias_ptr,
|
|
args.q_descale_ptr,
|
|
args.k_descale_ptr,
|
|
args.v_descale_ptr,
|
|
args.rand_val_ptr,
|
|
args.lse_ptr,
|
|
args.o_ptr,
|
|
args.seqstart_q_ptr,
|
|
args.seqstart_k_ptr,
|
|
args.seqlen_q_ptr,
|
|
args.seqlen_k_ptr,
|
|
args.hdim_q,
|
|
args.hdim_v,
|
|
args.nhead_q,
|
|
args.nhead_q / args.nhead_k,
|
|
args.scale_s,
|
|
args.logits_soft_cap,
|
|
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.window_size_left,
|
|
args.window_size_right,
|
|
args.mask_type,
|
|
args.min_seqlen_q,
|
|
args.p_drop,
|
|
args.s_randval,
|
|
args.drop_seed_offset,
|
|
args.cu_seqlen_q_ptr,
|
|
args.cu_seqlen_k_ptr);
|
|
}
|
|
else
|
|
{ // create batch mode kernel arguments
|
|
return FmhaKernel::MakeKargsImpl(args.q_ptr,
|
|
args.k_ptr,
|
|
args.v_ptr,
|
|
args.bias_ptr,
|
|
args.q_descale_ptr,
|
|
args.k_descale_ptr,
|
|
args.v_descale_ptr,
|
|
args.rand_val_ptr,
|
|
args.lse_ptr,
|
|
args.o_ptr,
|
|
args.seqlen_q,
|
|
args.seqlen_k,
|
|
args.hdim_q,
|
|
args.hdim_v,
|
|
args.nhead_q,
|
|
args.nhead_q / args.nhead_k,
|
|
args.scale_s,
|
|
args.logits_soft_cap,
|
|
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,
|
|
args.cu_seqlen_q_ptr,
|
|
args.cu_seqlen_k_ptr);
|
|
}
|
|
}();
|
|
|
|
if constexpr(FmhaKernel::kIsGroupMode)
|
|
{
|
|
dim3 grids = FmhaKernel::GridSize(
|
|
args.batch, args.nhead_q, args.max_seqlen_q, args.hdim_v, args.seqlen_k_ptr != nullptr);
|
|
return ck_tile::make_tuple(kargs, grids);
|
|
}
|
|
else
|
|
{
|
|
dim3 grids =
|
|
FmhaKernel::GridSize(args.batch, args.nhead_q, args.max_seqlen_q, args.hdim_v, false);
|
|
return ck_tile::make_tuple(kargs, grids);
|
|
}
|
|
}
|
|
|
|
template <typename FmhaKernel>
|
|
auto fmha_fwd_v3_create_kargs_and_grids(fmha_fwd_args args)
|
|
{
|
|
/// NOTICE: This was borrowed from Aiter. Make sure the selected remap_opt setting truly
|
|
/// maximizes the kernel's performance.
|
|
int remap_opt = 2;
|
|
if(args.mask_type != static_cast<int>(mask_enum::no_mask) &&
|
|
((args.nhead_q % 8 != 0) || (16384 < args.seqlen_q)))
|
|
{
|
|
if(65536 <= args.seqlen_q)
|
|
{
|
|
remap_opt = 0;
|
|
}
|
|
else
|
|
{
|
|
remap_opt = 1;
|
|
}
|
|
}
|
|
|
|
auto kargs = [&] {
|
|
if constexpr(FmhaKernel::kIsGroupMode)
|
|
{
|
|
return FmhaKernel::MakeKargs(args.q_ptr,
|
|
args.k_ptr,
|
|
args.v_ptr,
|
|
nullptr, // lse_ptr
|
|
args.o_ptr,
|
|
args.seqstart_q_ptr,
|
|
args.seqstart_k_ptr,
|
|
args.seqlen_q_ptr,
|
|
args.seqlen_k_ptr,
|
|
args.hdim_q,
|
|
args.hdim_v,
|
|
args.nhead_q,
|
|
args.nhead_q / args.nhead_k,
|
|
args.scale_s,
|
|
args.stride_q,
|
|
args.stride_k,
|
|
args.stride_v,
|
|
args.stride_o,
|
|
args.nhead_stride_q,
|
|
args.nhead_stride_k,
|
|
args.nhead_stride_v,
|
|
0, // nhead_stride_lse
|
|
args.nhead_stride_o,
|
|
args.window_size_left,
|
|
args.window_size_right,
|
|
args.mask_type,
|
|
remap_opt,
|
|
args.cu_seqlen_q_ptr,
|
|
args.cu_seqlen_k_ptr);
|
|
}
|
|
else
|
|
{
|
|
return FmhaKernel::MakeKargs(args.q_ptr,
|
|
args.k_ptr,
|
|
args.v_ptr,
|
|
nullptr, // lse_ptr
|
|
args.o_ptr,
|
|
args.seqlen_q,
|
|
args.seqlen_k,
|
|
args.hdim_q,
|
|
args.hdim_v,
|
|
args.nhead_q,
|
|
args.nhead_q / args.nhead_k,
|
|
args.scale_s,
|
|
args.stride_q,
|
|
args.stride_k,
|
|
args.stride_v,
|
|
args.stride_o,
|
|
args.nhead_stride_q,
|
|
args.nhead_stride_k,
|
|
args.nhead_stride_v,
|
|
0, // nhead_stride_lse
|
|
args.nhead_stride_o,
|
|
args.batch_stride_q,
|
|
args.batch_stride_k,
|
|
args.batch_stride_v,
|
|
0, // batch_stride_lse
|
|
args.batch_stride_o,
|
|
args.window_size_left,
|
|
args.window_size_right,
|
|
args.mask_type,
|
|
remap_opt,
|
|
args.cu_seqlen_q_ptr,
|
|
args.cu_seqlen_k_ptr);
|
|
}
|
|
}();
|
|
|
|
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 FmhaKernel>
|
|
auto fmha_fwd_pagedkv_create_kargs_and_grids(fmha_fwd_pagedkv_args args)
|
|
{
|
|
assert(args.nhead_q % args.nhead_k == 0);
|
|
auto kargs = [&] {
|
|
// create group mode kernel arguments
|
|
if constexpr(FmhaKernel::kIsGroupMode)
|
|
{
|
|
return FmhaKernel::MakeKargs(args.q_ptr,
|
|
args.k_ptr,
|
|
args.v_ptr,
|
|
args.bias_ptr,
|
|
args.lse_ptr,
|
|
args.o_ptr,
|
|
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.block_table_ptr,
|
|
args.batch_stride_block_table,
|
|
args.page_block_size,
|
|
args.is_gappy,
|
|
args.scale_s,
|
|
args.scale_p,
|
|
args.scale_o,
|
|
args.logits_soft_cap,
|
|
args.stride_q,
|
|
args.stride_k,
|
|
args.stride_v,
|
|
args.stride_bias,
|
|
args.stride_o,
|
|
args.nhead_stride_q,
|
|
args.nhead_stride_k,
|
|
args.nhead_stride_v,
|
|
args.nhead_stride_bias,
|
|
args.nhead_stride_lse,
|
|
args.nhead_stride_o,
|
|
args.batch_stride_k,
|
|
args.batch_stride_v,
|
|
args.window_size_left,
|
|
args.window_size_right,
|
|
args.mask_type,
|
|
args.min_seqlen_q);
|
|
}
|
|
else
|
|
{ // create batch mode kernel arguments
|
|
return FmhaKernel::MakeKargs(args.q_ptr,
|
|
args.k_ptr,
|
|
args.v_ptr,
|
|
args.bias_ptr,
|
|
args.lse_ptr,
|
|
args.o_ptr,
|
|
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.block_table_ptr,
|
|
args.batch_stride_block_table,
|
|
args.page_block_size,
|
|
args.cache_batch_idx,
|
|
args.scale_s,
|
|
args.scale_p,
|
|
args.scale_o,
|
|
args.logits_soft_cap,
|
|
args.stride_q,
|
|
args.stride_k,
|
|
args.stride_v,
|
|
args.stride_bias,
|
|
args.stride_o,
|
|
args.nhead_stride_q,
|
|
args.nhead_stride_k,
|
|
args.nhead_stride_v,
|
|
args.nhead_stride_bias,
|
|
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_lse,
|
|
args.batch_stride_o,
|
|
args.window_size_left,
|
|
args.window_size_right,
|
|
args.mask_type);
|
|
}
|
|
}();
|
|
|
|
// FmhaKernel::PrintParameters(kargs, args.batch);
|
|
if constexpr(FmhaKernel::kIsGroupMode)
|
|
{
|
|
dim3 grids = FmhaKernel::GridSize(
|
|
args.batch, args.nhead_q, args.max_seqlen_q, args.hdim_v, args.seqlen_k_ptr != nullptr);
|
|
return ck_tile::make_tuple(kargs, grids);
|
|
}
|
|
else
|
|
{
|
|
dim3 grids =
|
|
FmhaKernel::GridSize(args.batch, args.nhead_q, args.max_seqlen_q, args.hdim_v, false);
|
|
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.block_table_ptr,
|
|
args.batch_stride_block_table,
|
|
args.page_block_size,
|
|
args.is_gappy,
|
|
args.scale_s,
|
|
args.scale_p,
|
|
args.logits_soft_cap,
|
|
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, // only used for paged-kvcache
|
|
args.batch_stride_v, // only used for paged-kvcache
|
|
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.logits_soft_cap,
|
|
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.nhead_k, 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.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.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.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);
|
|
}
|
|
|
|
template <typename FmhaKernel>
|
|
auto fmha_batch_prefill_create_kargs_and_grids(fmha_batch_prefill_args args)
|
|
{
|
|
assert(args.nhead_q % args.nhead_k == 0);
|
|
auto kargs = [&] {
|
|
// create group mode kernel arguments
|
|
if constexpr(FmhaKernel::kIsGroupMode)
|
|
{
|
|
return FmhaKernel::MakeKargs(args.q_ptr,
|
|
args.k_ptr,
|
|
args.v_ptr,
|
|
args.bias_ptr,
|
|
args.rand_val_ptr,
|
|
args.lse_ptr,
|
|
args.o_ptr,
|
|
args.seqstart_q_ptr,
|
|
args.hdim_q,
|
|
args.hdim_v,
|
|
args.nhead_q,
|
|
args.nhead_q / args.nhead_k,
|
|
args.num_total_pages,
|
|
args.kv_indptr,
|
|
args.kv_page_indices,
|
|
#if 0 // we assume page_block_size=1 for now
|
|
args.kv_last_page_lens,
|
|
args.page_block_size,
|
|
#endif
|
|
args.scale_s,
|
|
args.scale_p,
|
|
args.scale_o,
|
|
args.logits_soft_cap,
|
|
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_k,
|
|
args.batch_stride_v,
|
|
args.window_size_left,
|
|
args.window_size_right,
|
|
args.mask_type,
|
|
args.p_drop,
|
|
args.s_randval,
|
|
args.drop_seed_offset);
|
|
}
|
|
else
|
|
{ // create batch mode kernel arguments
|
|
return FmhaKernel::MakeKargs(args.q_ptr,
|
|
args.k_ptr,
|
|
args.v_ptr,
|
|
args.bias_ptr,
|
|
args.rand_val_ptr,
|
|
args.lse_ptr,
|
|
args.o_ptr,
|
|
args.seqlen_q,
|
|
args.hdim_q,
|
|
args.hdim_v,
|
|
args.nhead_q,
|
|
args.nhead_q / args.nhead_k,
|
|
args.num_total_pages,
|
|
args.kv_indptr,
|
|
args.kv_page_indices,
|
|
#if 0 // we assume page_block_size=1 for now
|
|
args.kv_last_page_lens,
|
|
args.page_block_size,
|
|
#endif
|
|
args.scale_s,
|
|
args.scale_p,
|
|
args.scale_o,
|
|
args.logits_soft_cap,
|
|
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);
|
|
}
|
|
|
|
// 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_,
|
|
bool kHasLogitsSoftCap_,
|
|
typename FmhaMask_,
|
|
ck_tile::BlockAttentionBiasEnum BiasEnum_,
|
|
bool kStoreLse_,
|
|
bool kHasDropout_,
|
|
ck_tile::BlockAttentionQuantScaleEnum QScaleEnum_,
|
|
bool kPadS_,
|
|
bool kPadSK_,
|
|
bool kPadD_,
|
|
bool kPadDv_,
|
|
bool kUseTrLoad_,
|
|
bool kSkipMinSeqlenQ_ = false>
|
|
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_;
|
|
static constexpr bool kHasLogitsSoftCap = kHasLogitsSoftCap_;
|
|
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 auto QScaleEnum = QScaleEnum_;
|
|
static constexpr bool kPadS = kPadS_;
|
|
static constexpr bool kPadSK = kPadSK_;
|
|
static constexpr bool kPadD = kPadD_;
|
|
static constexpr bool kPadDv = kPadDv_;
|
|
static constexpr bool kUseTrLoad = kUseTrLoad_;
|
|
static constexpr bool kSkipMinSeqlenQ = kSkipMinSeqlenQ_;
|
|
};
|
|
|
|
template <typename Traits_, typename Arch = void>
|
|
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_,
|
|
bool kHasLogitsSoftCap_,
|
|
typename FmhaMask_,
|
|
ck_tile::BlockAttentionBiasEnum BiasEnum_,
|
|
bool kStoreLse_,
|
|
bool kIsPagedKV_,
|
|
bool kDoFp8StaticQuant_,
|
|
bool kPadS_,
|
|
bool kPadSK_,
|
|
bool kPadD_,
|
|
bool kPadDv_,
|
|
bool kSkipMinSeqlenQ_ = false>
|
|
struct fmha_fwd_pagedkv_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_;
|
|
static constexpr bool kHasLogitsSoftCap = kHasLogitsSoftCap_;
|
|
using FmhaMask = ck_tile::remove_cvref_t<FmhaMask_>;
|
|
static constexpr auto BiasEnum = BiasEnum_;
|
|
static constexpr bool kStoreLse = kStoreLse_;
|
|
static constexpr bool kIsPagedKV = kIsPagedKV_;
|
|
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 kSkipMinSeqlenQ = kSkipMinSeqlenQ_;
|
|
};
|
|
|
|
template <typename Traits_, typename Arch = void>
|
|
float fmha_fwd_pagedkv_(const ck_tile::stream_config&, fmha_fwd_pagedkv_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_,
|
|
bool kHasLogitsSoftCap_,
|
|
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_;
|
|
static constexpr bool kHasLogitsSoftCap = kHasLogitsSoftCap_;
|
|
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_, typename Arch = void>
|
|
void fmha_fwd_splitkv_oneshot_(const ck_tile::stream_config&, fmha_fwd_splitkv_args);
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template <typename Traits_, typename Arch = void>
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std::string fmha_fwd_splitkv_get_name_();
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template <ck_tile::index_t HDim_,
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typename DataType_,
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bool kIsGroupMode_,
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ck_tile::index_t kN1_,
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bool kStoreLse_,
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bool kDoFp8StaticQuant_,
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bool kPadS_,
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bool kPadDv_>
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struct fmha_fwd_splitkv_combine_traits_
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{
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static constexpr ck_tile::index_t HDim = HDim_;
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using DataType = ck_tile::remove_cvref_t<DataType_>;
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static constexpr bool kIsGroupMode = kIsGroupMode_;
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static constexpr ck_tile::index_t kN1 = kN1_;
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static constexpr bool kStoreLse = kStoreLse_;
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static constexpr bool kDoFp8StaticQuant = kDoFp8StaticQuant_;
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static constexpr bool kPadS = kPadS_;
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static constexpr bool kPadDv = kPadDv_;
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};
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template <typename Traits_, typename Arch = void>
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void fmha_fwd_splitkv_combine_oneshot_(const ck_tile::stream_config&, fmha_fwd_splitkv_args);
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template <typename Traits_, typename Arch = void>
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std::string fmha_fwd_splitkv_combine_get_name_();
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// this is used to pattern-match internl kernel implementation, not to instantiate kernel
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template <ck_tile::index_t HDim_,
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typename DataType_,
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ck_tile::index_t kTileSizeS_,
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ck_tile::index_t kTileSizeSk_,
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ck_tile::index_t kTileSizeD_,
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ck_tile::index_t kTileSizeDv_,
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bool kIsVLayoutRowMajor_,
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bool kPadS_,
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bool kPadSk_,
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bool kPadD_,
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bool kPadDv_,
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ck_tile::RotaryEmbeddingEnum RotaryEnum_,
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bool kIsPagedKV_>
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struct fmha_fwd_appendkv_traits_
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{
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static constexpr ck_tile::index_t HDim = HDim_;
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using DataType = ck_tile::remove_cvref_t<DataType_>;
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static constexpr ck_tile::index_t kTileSizeS = kTileSizeS_;
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static constexpr ck_tile::index_t kTileSizeSk = kTileSizeSk_;
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static constexpr ck_tile::index_t kTileSizeD = kTileSizeD_;
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static constexpr ck_tile::index_t kTileSizeDv = kTileSizeDv_;
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static constexpr bool kIsVLayoutRowMajor = kIsVLayoutRowMajor_;
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static constexpr bool kPadS = kPadS_;
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static constexpr bool kPadSk = kPadSk_;
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static constexpr bool kPadD = kPadD_;
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static constexpr bool kPadDv = kPadDv_;
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static constexpr auto RotaryEnum = RotaryEnum_;
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static constexpr bool kIsPagedKV = kIsPagedKV_;
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};
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template <typename Traits_, typename Arch = void>
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float fmha_fwd_appendkv_(const ck_tile::stream_config&, fmha_fwd_appendkv_args);
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template <typename Traits_, typename Arch = void>
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float fmha_batch_prefill_(const ck_tile::stream_config&, fmha_batch_prefill_args);
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// This is the public API, will be generated by script
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struct fmha_fwd_traits
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{
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int hdim_q;
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int hdim_v;
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std::string data_type;
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bool is_group_mode;
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bool is_v_rowmajor;
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bool has_logits_soft_cap;
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mask_enum mask_type;
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bias_enum bias_type; // 0:no bias, 1:elementwise bias, 2:alibi. sync with BlockAttentionBiasEnum
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bool has_lse;
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bool has_dropout;
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quant_scale_enum qscale_type;
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bool skip_min_seqlen_q = false;
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// TODO: padding check is inside this api
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};
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float fmha_fwd(fmha_fwd_traits, fmha_fwd_args, const ck_tile::stream_config&);
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struct fmha_fwd_pagedkv_traits
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{
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int hdim_q;
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int hdim_v;
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std::string data_type;
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bool is_group_mode;
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bool is_v_rowmajor;
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bool has_logits_soft_cap;
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mask_enum mask_type;
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bias_enum bias_type; // 0:no bias, 1:elementwise bias, 2:alibi. sync with BlockAttentionBiasEnum
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bool has_lse = false;
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bool use_pagedkv = true;
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bool do_fp8_static_quant = false;
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bool skip_min_seqlen_q = false;
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// TODO: padding check is inside this api
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};
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float fmha_fwd_pagedkv(fmha_fwd_pagedkv_traits&,
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fmha_fwd_pagedkv_args&,
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const ck_tile::stream_config&);
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struct fmha_fwd_splitkv_traits
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{
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int hdim_q;
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int hdim_v;
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std::string data_type;
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bool is_group_mode;
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bool is_v_rowmajor;
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bool has_logits_soft_cap;
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mask_enum mask_type;
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bias_enum bias_type; // 0:no bias, 1:elementwise bias, 2:alibi. sync with BlockAttentionBiasEnum
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bool has_lse;
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bool do_fp8_static_quant;
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// TODO: padding check is inside this api
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};
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float fmha_fwd_splitkv(fmha_fwd_splitkv_traits,
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fmha_fwd_splitkv_args,
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const ck_tile::stream_config&);
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struct fmha_fwd_appendkv_traits
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{
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int hdim_q;
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int hdim_v;
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std::string data_type;
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bool is_v_rowmajor;
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rope_enum rope_type;
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};
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float fmha_fwd_appendkv(fmha_fwd_appendkv_traits,
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fmha_fwd_appendkv_args,
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const ck_tile::stream_config&);
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using fmha_batch_prefill_traits = fmha_fwd_traits;
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float fmha_batch_prefill(fmha_batch_prefill_traits,
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fmha_batch_prefill_args,
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const ck_tile::stream_config&);
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