Files
cutlass/examples/77_blackwell_fmha/kernel/fmha_kernel_bwd_convert.hpp
Richard Cai 56f0718a97 ex77 backwards GQA (#2556)
* bwd GQA init

* Update examples/77_blackwell_fmha/77_blackwell_fmha_bwd.cu

* ref kernel type conversion fix

---------

Co-authored-by: Haicheng Wu <57973641+hwu36@users.noreply.github.com>
2025-09-09 12:53:28 -04:00

154 lines
6.4 KiB
C++

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#pragma once
#include "cutlass/cutlass.h"
#include "cute/layout.hpp"
namespace cutlass::fmha::kernel {
using namespace cute;
template<class ProblemShape, class Element, class ElementAcc>
struct FmhaKernelBwdConvert {
struct Arguments {
ProblemShape problem_shape;
const ElementAcc* ptr_src_dQ;
tuple<int, _1, tuple<tuple<int, int>, int>> stride_src_dQ;
const ElementAcc* ptr_src_dK;
tuple<int, _1, tuple<tuple<_0, int>, int>> stride_src_dK;
const ElementAcc* ptr_src_dV;
tuple<int, _1, tuple<tuple<_0, int>, int>> stride_src_dV;
Element* ptr_dest_dQ;
tuple<int, _1, tuple<tuple<int, int>, int>> stride_dest_dQ;
Element* ptr_dest_dK;
tuple<int, _1, tuple<tuple<_0, int>, int>> stride_dest_dK;
Element* ptr_dest_dV;
tuple<int, _1, tuple<tuple<_0, int>, int>> stride_dest_dV;
ElementAcc scale = 1.0;
};
using Params = Arguments;
using ClusterShape = Shape<_1, _1, _1>;
static constexpr int SharedStorageSize = 0;
static const int MinBlocksPerMultiprocessor = 1;
static const int MaxThreadsPerBlock = 128;
using ArchTag = cutlass::arch::Sm90;
static const int kBlockSeq = 8;
static size_t get_workspace_size(Arguments const& args) { return 0; }
static cutlass::Status initialize_workspace(Arguments const&, void*, cudaStream_t) {
return cutlass::Status::kSuccess;
}
static const int kNumThreadsD = 16;
static const int kNumThreadsSeq = MaxThreadsPerBlock / kNumThreadsD;
static const int kElementsPerLoad = 4;
static const int kIterationsSeq = kBlockSeq / kNumThreadsSeq;
static bool can_implement(Arguments const& args) {
return get<2>(args.problem_shape) % kElementsPerLoad == 0 && get<3>(args.problem_shape) % kElementsPerLoad == 0;
}
static dim3 get_grid_shape(Params const& params) {
dim3 grid(size<4,0>(params.problem_shape), size<4,1>(params.problem_shape), ceil_div(std::max(size<0>(params.problem_shape), size<1>(params.problem_shape)), kBlockSeq));
return grid;
}
static dim3 get_block_shape() {
dim3 block(kNumThreadsD, kNumThreadsSeq, 1);
return block;
}
static Params to_underlying_arguments(Arguments const& args, void* workspace) {
return args;
}
template<class StrideSrc, class StrideDest, class Count>
CUTLASS_DEVICE void copy(Params const& params, const ElementAcc* ptr_src, StrideSrc const& stride_src, Element* ptr_dest, StrideDest const& stride_dest, Count const& count, int d_dim) {
auto ptr_src_bh = ptr_src + get<2,0,0>(stride_src) * blockIdx.x + get<2,1>(stride_src) * blockIdx.y;
auto ptr_dest_bh = ptr_dest + get<2,0,0>(stride_dest) * blockIdx.x + get<2,1>(stride_dest) * blockIdx.y;
int seqlen = count;
if constexpr (is_variable_length_v<decltype(count)>) {
int offset = count.cumulative_length[blockIdx.y];
ptr_dest_bh += offset * get<0>(stride_dest);
seqlen = count.cumulative_length[blockIdx.y + 1] - offset;
}
for (int idx_s_t = threadIdx.y; idx_s_t < kBlockSeq; idx_s_t += kNumThreadsSeq) {
int idx_s = idx_s_t + kBlockSeq * blockIdx.z;
if (idx_s >= seqlen) continue;
auto ptr_src_bhs = ptr_src_bh + idx_s * get<0>(stride_src);
auto ptr_dest_bhs = ptr_dest_bh + idx_s * get<0>(stride_dest);
for (int idx_d = threadIdx.x * kElementsPerLoad; idx_d < d_dim; idx_d += kElementsPerLoad * kNumThreadsD) {
ElementAcc value_src[kElementsPerLoad];
Element value_dest[kElementsPerLoad];
using VecSrc = uint_bit_t<sizeof_bits_v<ElementAcc> * kElementsPerLoad>;
using VecDest = uint_bit_t<sizeof_bits_v<Element> * kElementsPerLoad>;
*reinterpret_cast<VecSrc*>(value_src) = *reinterpret_cast<const VecSrc*>(&ptr_src_bhs[idx_d]);
for (int v = 0; v < kElementsPerLoad; v++) {
value_dest[v] = static_cast<Element>(params.scale * value_src[v]);
}
*reinterpret_cast<VecDest*>(&ptr_dest_bhs[idx_d]) = *reinterpret_cast<const VecDest*>(value_dest);
}
}
}
CUTLASS_DEVICE void operator()(const Params &params, char* smem) {
if (params.ptr_src_dQ != nullptr) {
copy(params, params.ptr_src_dQ, params.stride_src_dQ, params.ptr_dest_dQ, params.stride_dest_dQ, get<0>(params.problem_shape), get<2>(params.problem_shape));
}
if (params.ptr_src_dK != nullptr) {
copy(params, params.ptr_src_dK, params.stride_src_dK, params.ptr_dest_dK, params.stride_dest_dK, get<1>(params.problem_shape), get<2>(params.problem_shape));
}
if (params.ptr_src_dV != nullptr) {
copy(params, params.ptr_src_dV, params.stride_src_dV, params.ptr_dest_dV, params.stride_dest_dV, get<1>(params.problem_shape), get<3>(params.problem_shape));
}
}
};
} // namespace cutlass::fmha::kernel