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Merge branch 'mtgu/dev/ck_moe_gemm2_int4_merge' into dev/ck_moe_gemm2_merge

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coderfeli
2025-02-21 08:52:43 +00:00
parent d5b2c900b9 1d46f8f63d
commit 751ddf8648
4 changed files with 569 additions and 100 deletions
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4
example/65_gemm_multiply_multiply/moe_pk_i4_gemm1.cpp
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@@ -167,14 +167,14 @@ using DeviceOpInstance = ck::tensor_operation::device::DeviceMoeGemm<
Row, Col, DsLayout, ELayout,
A0DataType, B0DataType, DsDataType, EDataType, AccDataType, CShuffleDataType,
AElementOp, BElementOp, CDEElementOp, GemmSpec,
256, 128, 128, 64,
256, MPerBlock, 128, 64,
16, 32,
32, 32,
4, 1,
S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0,
S<2, 128, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 32, 32, 0,
4, 1, S<1, 32, 1, 8>, S<4, 1, 1>,
ck::BlockGemmPipelineScheduler::Intrawave, ck::BlockGemmPipelineVersion::v1, Nswizzle, true, A0DataType>;
ck::BlockGemmPipelineScheduler::Intrawave, ck::BlockGemmPipelineVersion::v3, Nswizzle, true, A0DataType>;
// clang-format on
#endif

14
include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_b_preshuffle_dequant_v3.hpp
View File

@@ -194,17 +194,17 @@ struct BlockwiseGemmXdlops_pipeline_bpreshuffle_bdequant_v3<BlockGemmPipelineSch
constexpr auto num_mfma = HotLoopInstList::C_MFMA_Inst_Num;
constexpr auto staged_num_ds_read_inst_a = num_ds_read_inst_a / MRepeat;
constexpr auto staged_num_mfma = num_mfma / MRepeat;
constexpr auto staged_num_ds_read_inst_a = ck::math::integer_divide_ceil(num_ds_read_inst_a,MRepeat);
constexpr auto staged_num_mfma = ck::math::integer_divide_ceil(num_mfma , MRepeat);
constexpr auto staged_num_mfma_per_ds_read_a = staged_num_mfma / staged_num_ds_read_inst_a;
constexpr auto staged_num_mfma_per_ds_read_a = ck::math::integer_divide_ceil(staged_num_mfma , staged_num_ds_read_inst_a);
if constexpr(stage.value == 0)
{
constexpr auto staged_num_buffer_load_b_per_ds_read_a =
num_buffer_load_inst_b / staged_num_ds_read_inst_a;
constexpr auto staged_num_mfma_per_buffer_load_b =
staged_num_mfma / num_buffer_load_inst_b;
constexpr auto staged_num_buffer_load_b_per_ds_read_a = ck::math::integer_divide_ceil(
num_buffer_load_inst_b , staged_num_ds_read_inst_a);
constexpr auto staged_num_mfma_per_buffer_load_b =ck::math::integer_divide_ceil(
staged_num_mfma , num_buffer_load_inst_b);
// B global
static_for<0, staged_num_ds_read_inst_a, 1>{}([&](auto i_inst) {
ignore = i_inst;

55
include/ck/tensor_operation/gpu/device/impl/device_moe_gemm.hpp
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@@ -247,6 +247,7 @@ struct DeviceMoeGemm
// static_assert(BlkGemmPipelineVer == BlockGemmPipelineVersion::v3 &&
// has_main_k_block_loop, "only impl BlockGemmPipelineVersion::v3 and has mainloop right
// now");
constexpr auto MemoryDataOp = IsInputGemm ? InMemoryDataOperationEnum::Set : InMemoryDataOperationEnum::AtomicAdd;
if(has_main_k_block_loop)
{
// Tail number always full
@@ -279,7 +280,6 @@ struct DeviceMoeGemm
// }
// else
{
constexpr auto MemoryDataOp = IsInputGemm ? InMemoryDataOperationEnum::Set : InMemoryDataOperationEnum::AtomicAdd;
// if(GridwiseGemm::CalculateKBlockLoopTailNum(K_split) == TailNumber::Odd)
// {
// const auto kernel = kernel_moe_gemm<
@@ -304,8 +304,9 @@ struct DeviceMoeGemm
}
}
}
// else if constexpr(BlkGemmPipelineVer == BlockGemmPipelineVersion::v2)
// {
else if constexpr(BlkGemmPipelineVer == BlockGemmPipelineVersion::v2 ||
BlkGemmPipelineVer == BlockGemmPipelineVersion::v3)
{
// if(arg.KBatch > 1)
// {
// if(GridwiseGemm::CalculateKBlockLoopTailNum(K_split) == TailNumber::Odd)
@@ -332,31 +333,29 @@ struct DeviceMoeGemm
// }
// }
// else
// {
// if(GridwiseGemm::CalculateKBlockLoopTailNum(K_split) == TailNumber::Odd)
// {
// const auto kernel =
// kernel_moe_gemm_gather_2lds<
// GridwiseGemm,
// true,
// IsInputGemm? InMemoryDataOperationEnum::Set : InMemoryDataOperationEnum::AtomicAdd,
// minimum_occupancy,
// TailNumber::Odd>;
// RunKernel(kernel);
// }
// else
// {
// const auto kernel =
// kernel_moe_gemm_gather_2lds<
// GridwiseGemm,
// true,
// IsInputGemm? InMemoryDataOperationEnum::Set : InMemoryDataOperationEnum::AtomicAdd,
// minimum_occupancy,
// TailNumber::Even>;
// RunKernel(kernel);
// }
// }
// }
{
if(GridwiseGemm::CalculateKBlockLoopTailNum(K_split) == TailNumber::Odd)
{
const auto kernel = kernel_moe_gemm_2lds<GridwiseGemm,
true,
MemoryDataOp,
minimum_occupancy,
IsInputGemm,
TailNumber::Odd>;
RunKernel(kernel);
}
else
{
const auto kernel = kernel_moe_gemm_2lds<GridwiseGemm,
true,
MemoryDataOp,
minimum_occupancy,
IsInputGemm,
TailNumber::Even>;
RunKernel(kernel);
}
}
}
else
{
throw std::runtime_error("todo: only v1 & v2 support now");

596
include/ck/tensor_operation/gpu/grid/gridwise_moe_gemm.hpp
View File

@@ -62,39 +62,43 @@ __global__ void
#endif // end of if (defined(__gfx9__))
}
// template <typename GridwiseGemm,
// bool HasMainKBlockLoop,
// InMemoryDataOperationEnum CGlobalMemoryDataOperation,
// index_t MinimumOccupancy = 1,
// TailNumber TailNum = TailNumber::Even>
// __global__ void
// #if CK_USE_LAUNCH_BOUNDS
// __launch_bounds__(CK_MAX_THREAD_PER_BLOCK, MinimumOccupancy)
// #endif
// // __attribute__((amdgpu_waves_per_eu(1, 1)))
// kernel_moe_gemm_gather_2lds(typename GridwiseGemm::Argument karg)
// {
// #if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx9__))
// __shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
// __shared__ char p_shared1[GridwiseGemm::GetSharedMemoryNumberOfByte()];
template <typename GridwiseGemm,
bool HasMainKBlockLoop,
InMemoryDataOperationEnum CGlobalMemoryDataOperation,
index_t MinimumOccupancy = 1,
bool IsInputGemm = false,
TailNumber TailNum = TailNumber::Even>
__global__ void
#if CK_USE_LAUNCH_BOUNDS
__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, MinimumOccupancy)
#endif
// __attribute__((amdgpu_waves_per_eu(1, 1)))
kernel_moe_gemm_2lds(typename GridwiseGemm::Argument karg)
{
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx9__))
__shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
__shared__ char p_shared1[GridwiseGemm::GetSharedMemoryNumberOfByte()];
// auto splitk_batch_offset = typename GridwiseGemm::SplitKBatchOffset(karg, blockIdx.z);
auto splitk_batch_offset = typename GridwiseGemm::SplitKBatchOffset(karg, blockIdx.z);
// GridwiseGemm::template Run_2Lds<HasMainKBlockLoop, CGlobalMemoryDataOperation, TailNum>(
// karg.p_a_grid + splitk_batch_offset.a_k_split_offset,
// karg.p_b_grid + splitk_batch_offset.b_k_split_offset,
// karg.p_ds_grid,
// karg.p_c_grid,
// p_shared,
// p_shared1,
// karg,
// karg.a_element_op,
// karg.b_element_op,
// karg.c_element_op);
// #else
// ignore = karg;
// #endif // end of if (defined(__gfx9__))
// }
GridwiseGemm::template Run_2Lds<HasMainKBlockLoop, CGlobalMemoryDataOperation, IsInputGemm, TailNum>(
karg.p_sorted_token_ids,
karg.p_sorted_expert_ids,
karg.p_max_token_id,
karg.p_a_grid + splitk_batch_offset.a_k_split_offset,
karg.p_b_grid + splitk_batch_offset.b_k_split_offset,
karg.p_ds_grid,
karg.p_c_grid,
p_shared,
p_shared1,
karg,
karg.a_element_op,
karg.b_element_op,
karg.c_element_op);
#else
ignore = karg;
#endif // end of if (defined(__gfx9__))
}
template <typename ALayout,
typename BLayout,
@@ -929,7 +933,7 @@ struct GridwiseMoeGemm
GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock();
constexpr auto c_block_size =
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize();
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize() / 2;
return math::max(a_block_space_size_aligned * sizeof(LDSTypeA) / APackedSize,
c_block_size * sizeof(CShuffleDataType));
@@ -1642,10 +1646,506 @@ struct GridwiseMoeGemm
}
}
template <bool HasMainKBlockLoop,
InMemoryDataOperationEnum CGlobalMemoryDataOperation,
bool IsInputGemm = true,
TailNumber TailNum = TailNumber::Odd>
__device__ static void Run_2Lds(const index_t* p_sorted_token_ids,
const index_t* p_sorted_expert_ids,
const index_t* p_max_token_id,
const ADataType* p_a_grid,
const BDataType* p_b_grid,
DsGridPointer& p_ds_grid,
CDataType* p_c_grid,
void* p_shared,
void* p_shared1,
const Problem& problem,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
CElementwiseOperation c_element_op)
{
ignore = b_element_op;
const auto a_grid_desc_ak0_m_ak1 = MakeAGridDescriptor_AK0_M_AK1(
IsInputGemm? problem.NumTokens : problem.NumTokens * problem.TopK, problem.MPadded, problem.K, problem.KPadded, problem.StrideA, problem.AK0);
const auto b_grid_desc_bpreshuffled =
MakeBGridDescriptor_Preshuffled(problem.BN0Shuffled, problem.BK0Shuffled);
const auto c_grid_desc_m_n = MakeCGridDescriptor_M_N<CLayout>(
IsInputGemm? problem.NumTokens * problem.TopK : problem.NumTokens , problem.MPadded, problem.N, problem.NPadded, problem.StrideC);
// printf("tido %d size %d %d MNBLOCK %d %d %d %d\n", threadIdx.x, problem.StrideC, c_grid_desc_m_n.GetElementSpaceSize(),
// problem.MBlock, problem.NBlock, MPerBlock, NPerBlock);
const auto c_grid_desc_mblock_mperblock_nblock_nperblock =
MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
c_grid_desc_m_n, problem.MBlock, problem.NBlock);
const index_t max_token_id = __builtin_amdgcn_readfirstlane(p_max_token_id[0]);
// constexpr int expert_tile_cnt[8] = {2, 1, 1, 2, 2, 2, 1, 2};
// const index_t b_block_id = blockIdx.x % problem.NBlock;
const auto block_mn = [&]() -> std::pair<int, int> {
if constexpr (NSwizzle)
{
const index_t expert_block_id = blockIdx.x / problem.NBlock;
const index_t es = __builtin_amdgcn_readfirstlane(p_max_token_id[expert_block_id + 1]);
const index_t expert_swizzle = es > 0 ? es : 1; //p_max_token_id[expert_id + 1];
const index_t expert_block_swizzle = expert_block_id / expert_swizzle;
const index_t b_block_id_swizzle = blockIdx.x % (problem.NBlock * expert_swizzle);
const index_t nid = __builtin_amdgcn_readfirstlane(b_block_id_swizzle % 8 + b_block_id_swizzle / (8 * expert_swizzle) * 8);
const index_t mid = __builtin_amdgcn_readfirstlane(expert_block_swizzle * expert_swizzle + b_block_id_swizzle / 8 % expert_swizzle);
return {nid, mid};
} else {
return {blockIdx.x, blockIdx.y};
}
}();
const index_t block_n_id = block_mn.first;
const index_t block_m_id = block_mn.second;
const index_t expert_id = __builtin_amdgcn_readfirstlane(p_sorted_expert_ids[block_m_id]);
// if (threadIdx.x==0) {
// printf("bid %d, eid %d, es %d, esi %d, bsi %d, m %d, n %d\n", blockIdx.x, expert_id, expert_swizzle, expert_block_swizzle, b_block_id_swizzle, block_m_id, block_n_id);
// }
const index_t token0 = __builtin_amdgcn_readfirstlane(p_sorted_token_ids[block_m_id * MPerBlock] & 0xffffff);
// constexpr auto M0 = ABlockTransferThreadClusterLengths_AK0_M_AK1{}.At(I1);
constexpr auto AMThreads = ABlockTransferThreadClusterLengths_AK0_M_AK1{}.At(I1);
constexpr auto AK0Threads = ABlockTransferThreadClusterLengths_AK0_M_AK1{}.At(I0);
constexpr auto AK1Threads = ABlockTransferThreadClusterLengths_AK0_M_AK1{}.At(I2);
constexpr auto AKThreads = AK0Threads * AK1Threads;
constexpr auto AMRepeats = MPerBlock / AMThreads;
const index_t token_pos = block_m_id * MPerBlock + threadIdx.x / AKThreads * AMRepeats;
if(token_pos >= max_token_id || token0 >= problem.NumTokens)
return;
StaticallyIndexedArray<index_t, AMRepeats> gather_offsets; //= p_sorted_token_ids[token_pos];
static_for<0, AMRepeats, 1>{}([&](auto m0) {
const index_t fused_token = p_sorted_token_ids[token_pos + m0];
index_t token_offset = fused_token & 0xffffff;
if constexpr (!IsInputGemm)
{
token_offset = token_offset * problem.TopK + (fused_token >> 24);
}
gather_offsets(m0) = token_offset * problem.K;
// printf("init off tid %d m %d off %d\n", threadIdx.x, m0(), gather_offsets(m0));
});
const index_t expert_stride = __builtin_amdgcn_readfirstlane(problem.N * problem.K);
// N0, K0, Blocksize*KPack
const index_t n_block_data_idx_on_grid =
__builtin_amdgcn_readfirstlane(block_n_id * NXdlPerWave);
const auto a_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
p_a_grid, a_grid_desc_ak0_m_ak1.GetElementSpaceSize());
const auto b_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
p_b_grid + expert_id * expert_stride / BPackedSize, b_grid_desc_bpreshuffled.GetElementSpaceSize());
// if(threadIdx.x==0)
// printf("tid %d eid %d expert_stride %d bufsize %d\n",
// threadIdx.x, expert_id, expert_stride, a_grid_desc_ak0_m_ak1.GetElementSpaceSize());
// A matrix in LDS memory, dst of blockwise copy
constexpr auto a_block_desc_ak0_m_ak1 = GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1();
// B matrix in LDS memory, dst of blockwise copy
// dummy
constexpr auto b_block_desc_bk0_n_bk1 = GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1();
// A matrix blockwise copy
auto a_blockwise_copy =
ThreadGroupTensorSliceTransfer_v4r1_mod8<ThisThreadBlock,
AElementwiseOperation,
ck::tensor_operation::element_wise::PassThrough,
InMemoryDataOperationEnum::Set,
Sequence<AK0Number, MPerBlock, AK1Number>,
ABlockTransferThreadClusterLengths_AK0_M_AK1,
ABlockTransferThreadClusterArrangeOrder,
ADataType,
LDSTypeA,
decltype(a_grid_desc_ak0_m_ak1),
decltype(a_block_desc_ak0_m_ak1),
ABlockTransferSrcAccessOrder,
Sequence<0, 1, 2>,
ABlockTransferSrcVectorDim,
2,
ABlockTransferSrcScalarPerVector,
ABlockTransferDstScalarPerVector_AK1,
1,
1,
AThreadTransferSrcResetCoordinateAfterRun,
true,
1,
2>(
a_grid_desc_ak0_m_ak1,
make_multi_index(0, 0, 0),
a_element_op,
a_block_desc_ak0_m_ak1,
make_multi_index(0, 0, 0),
ck::tensor_operation::element_wise::PassThrough{},
gather_offsets);
// Thread-wise copy
// K0 -> N0/NWave -> NWave -> KLane -> NLane -> KPack
auto b_block_buf_ping = make_static_buffer<AddressSpaceEnum::Vgpr, BDataType>(
b_block_desc_bk0_n_bk1.GetElementSpaceSize());
auto b_block_buf_pong = make_static_buffer<AddressSpaceEnum::Vgpr, BDataType>(
b_block_desc_bk0_n_bk1.GetElementSpaceSize());
auto b_block_bufs = make_tuple(b_block_buf_ping, b_block_buf_pong);
auto b_blockwise_copy = ThreadwiseTensorSliceTransfer_v2<
BDataType,
BDataType,
decltype(b_grid_desc_bpreshuffled),
decltype(b_block_desc_bk0_n_bk1),
Sequence<Number<NXdlPerWave>{}, I1, Number<KRepeat>{}, Number<BK1Value>{}>,
Sequence<1, 2, 0, 3>,
3,
BBlockTransferSrcScalarPerVector,
BThreadTransferSrcResetCoordinateAfterRun,
true>(b_grid_desc_bpreshuffled,
make_multi_index(n_block_data_idx_on_grid,
get_warp_local_1d_id() % NWave,
0,
KPack * (get_thread_local_1d_id() % warpSize)));
// LDS allocation for A and B: be careful of alignment
// Cast after lds
auto a_block_buf_ping = make_dynamic_buffer<AddressSpaceEnum::Lds>(
static_cast<ADataType*>(p_shared), a_block_desc_ak0_m_ak1.GetElementSpaceSize());
auto a_block_buf_pong = make_dynamic_buffer<AddressSpaceEnum::Lds>(
static_cast<ADataType*>(p_shared1), a_block_desc_ak0_m_ak1.GetElementSpaceSize());
auto a_block_bufs = make_tuple(a_block_buf_ping, a_block_buf_pong);
constexpr auto a_block_slice_copy_step = make_multi_index(KPerBlock / AK1Number, 0, 0);
constexpr auto b_block_slice_copy_step = make_multi_index(0, 0, KRepeat, 0);
// Blockwise GEMM pipeline
static_assert(std::is_default_constructible_v<BlockwiseGemmPipe>);
auto blockwise_gemm_pipeline = BlockwiseGemmPipe{};
auto c_thread_buf = blockwise_gemm_pipeline.GetCThreadBuffer();
const index_t num_k_block_main_loop = __builtin_amdgcn_readfirstlane(
(a_grid_desc_ak0_m_ak1.GetLength(I0) * a_grid_desc_ak0_m_ak1.GetLength(I2)) /
KPerBlock);
blockwise_gemm_pipeline.template Run<HasMainKBlockLoop, TailNum>(a_grid_desc_ak0_m_ak1,
a_block_desc_ak0_m_ak1,
a_blockwise_copy,
a_grid_buf,
a_block_bufs,
a_block_slice_copy_step,
b_grid_desc_bpreshuffled,
b_blockwise_copy,
b_grid_buf,
b_block_bufs,
b_block_slice_copy_step,
c_thread_buf,
num_k_block_main_loop);
// shuffle C and write out
{
static_assert(MXdlPerWave % CShuffleMXdlPerWavePerShuffle == 0 &&
NXdlPerWave % CShuffleNXdlPerWavePerShuffle == 0,
"wrong!");
constexpr index_t MWave = MPerBlock / (MXdlPerWave * MPerXdl);
// TODO: hacky, fix it!
constexpr auto c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2 =
blockwise_gemm_pipeline.GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
// TODO: hacky, fix it!
// c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp is only used to get lengths
constexpr auto c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp =
blockwise_gemm_pipeline.GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
constexpr auto M0 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I0);
constexpr auto N0 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I1);
constexpr auto M1 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I2);
constexpr auto N1 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I3);
constexpr auto M2 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I4);
constexpr auto M3 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I5);
constexpr auto M4 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I6);
constexpr auto N2 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I7);
constexpr auto c_shuffle_block_desc_mblock_mperblock_nblock_nperblock =
GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock();
auto c_shuffle_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
static_cast<CShuffleDataType*>(p_shared),
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
constexpr auto c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2 = transform_tensor_descriptor(
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock,
make_tuple(
make_freeze_transform(I0),
make_unmerge_transform(make_tuple(
Number<CShuffleMXdlPerWavePerShuffle>{}, // M0 (MXdlPerWave) per shuffle
M1, // M1 = MWave
M2, // M2 * M3 * M4 = MPerXdl
M3,
M4)),
make_freeze_transform(I0),
make_unmerge_transform(make_tuple(
Number<CShuffleNXdlPerWavePerShuffle>{}, // N0 (NXdlPerWave) per shuffle
N1, // N1 = NWave
N2))), // N2 = NPerXdl
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
make_tuple(
Sequence<>{}, Sequence<0, 2, 4, 5, 6>{}, Sequence<>{}, Sequence<1, 3, 7>{}));
// calculate origin of thread output tensor on global memory
// blockwise GEMM c matrix starting index
const auto c_thread_mtx_on_block =
blockwise_gemm_pipeline.CalculateCThreadOriginDataIndex(I0, I0, I0, I0);
const index_t m_thread_data_on_block = c_thread_mtx_on_block[I0];
const index_t n_thread_data_on_block = c_thread_mtx_on_block[I1];
const auto m_thread_data_on_block_to_m0_m1_m2_m3_m4_adaptor =
make_single_stage_tensor_adaptor(
make_tuple(make_merge_transform(make_tuple(M0, M1, M2, M3, M4))),
make_tuple(Sequence<0, 1, 2, 3, 4>{}),
make_tuple(Sequence<0>{}));
const auto m_thread_data_on_block_idx =
m_thread_data_on_block_to_m0_m1_m2_m3_m4_adaptor.CalculateBottomIndex(
make_multi_index(m_thread_data_on_block));
const auto n_thread_data_on_block_to_n0_n1_n2_adaptor =
make_single_stage_tensor_adaptor(
make_tuple(make_merge_transform(make_tuple(N0, N1, N2))),
make_tuple(Sequence<0, 1, 2>{}),
make_tuple(Sequence<0>{}));
const auto n_thread_data_on_block_idx =
n_thread_data_on_block_to_n0_n1_n2_adaptor.CalculateBottomIndex(
make_multi_index(n_thread_data_on_block));
// shuffle: threadwise copy C from VGPR to LDS
auto c_thread_copy_vgpr_to_lds =
ThreadwiseTensorSliceTransfer_v1r3<AccDataType,
CShuffleDataType,
decltype(c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2),
decltype(c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2),
ck::tensor_operation::element_wise::PassThrough,
Sequence<CShuffleMXdlPerWavePerShuffle,
CShuffleNXdlPerWavePerShuffle,
I1,
I1,
M2,
I1,
M4,
I1>,
Sequence<0, 1, 2, 3, 4, 5, 6, 7>,
7,
1,
InMemoryDataOperationEnum::Set,
1,
true>{
c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2,
make_multi_index(0,
0,
m_thread_data_on_block_idx[I1],
n_thread_data_on_block_idx[I1],
m_thread_data_on_block_idx[I2],
m_thread_data_on_block_idx[I3],
m_thread_data_on_block_idx[I4],
n_thread_data_on_block_idx[I2]),
ck::tensor_operation::element_wise::PassThrough{}};
using EDataType = CDataType;
const auto ds_grid_desc_m_n = MakeDsGridDescriptor_M_N(
problem.M, problem.MPadded, problem.N, problem.NPadded, problem.StrideDs);
const auto ds_grid_desc_mblock_mperblock_nblock_nperblock =
MakeDsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
ds_grid_desc_m_n, problem.MBlock, problem.NBlock);
const auto ds_grid_buf = generate_tuple(
[&](auto i) {
using DDataType = remove_cvref_t<tuple_element_t<i.value, DsDataType>>;
const DDataType *ptr_ = p_ds_grid[i];
// hack logic here to support different kind of strides. todo fix it.
// ascale t, 1; bscale E, N, 1, move ptr to E
if (i.value == 1)
{
ptr_ += expert_id * (problem.StrideDs[1]? problem.StrideDs[1] * problem.N : 1);
// if ( threadIdx.x % 16 ==0)
// printf("bid %d eid %d b eoff %d %f\n", blockIdx.y, expert_id, expert_id * (problem.StrideDs[1]? problem.StrideDs[1] * problem.N : 1), ptr_[0]);
}
return make_dynamic_buffer<AddressSpaceEnum::Global>(
ptr_, ds_grid_desc_m_n[i].GetElementSpaceSize());
},
Number<NumDTensor>{});
// tuple of reference to C/Ds tensor descriptors
const auto c_ds_desc_refs = concat_tuple_of_reference(
tie(c_shuffle_block_desc_mblock_mperblock_nblock_nperblock),
generate_tie(
[&](auto i) -> const auto& // return type should be reference
{ return ds_grid_desc_mblock_mperblock_nblock_nperblock[i]; },
Number<NumDTensor>{}));
// tuple of reference to C/Ds tensor descriptors
const auto c_ds_buf_refs = concat_tuple_of_reference(
tie(c_shuffle_block_buf),
generate_tie(
[&](auto i) -> const auto& // return type should be reference
{ return ds_grid_buf[i]; },
Number<NumDTensor>{}));
// tuple of starting index of C/Ds blockwise copy
const auto idx_c_ds_block_begin = container_concat(
make_tuple(make_multi_index(0, 0, 0, 0)),
generate_tuple(
[&](auto) {
return make_multi_index(block_m_id, 0, block_n_id, 0);
// return make_multi_index(block_work_idx[I0], 0, block_work_idx[I1], 0);
},
Number<NumDTensor>{}));
const auto e_grid_desc_mblock_mperblock_nblock_nperblock =
c_grid_desc_mblock_mperblock_nblock_nperblock;
using CDEBlockTransferCluster =
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock;
const auto EGlobalMemoryDataOperation = CGlobalMemoryDataOperation;
constexpr auto EMThreads = CDEBlockTransferCluster{}.At(I0) * CDEBlockTransferCluster{}.At(I1);
constexpr auto EMRepeats = MPerBlock / EMThreads;
constexpr auto ENThreads = CDEBlockTransferCluster{}.At(I2) * CDEBlockTransferCluster{}.At(I3);
const index_t c_token_pos = block_m_id * MPerBlock + threadIdx.x / ENThreads * EMRepeats;
StaticallyIndexedArray<index_t, EMRepeats> scatter_offsets; //= p_sorted_token_ids[c_token_pos];
StaticallyIndexedArray<float, EMRepeats> scatter_weights; //= for topk
// too hack here, 2 specific for topk weights, fixme
const float *p_sorted_weights_0 = p_ds_grid[I0];
// const index_t topk_id[EMRepeats];// = (p_sorted_token_ids[block_m_id * MPerBlock] & 0xff000000) >> 24;
static_for<0, EMRepeats, 1>{}([&](auto m0) {
const index_t fused_token = p_sorted_token_ids[c_token_pos + m0];
index_t token_offset = fused_token & 0xffffff;
float weight = p_sorted_weights_0[(c_token_pos + m0) * problem.StrideDs[0]];
if constexpr (IsInputGemm)
{
token_offset = token_offset * problem.TopK + (fused_token >> 24);
} else {
const float *p_sorted_weights_2 = p_ds_grid[I2];
weight = weight * p_sorted_weights_2[c_token_pos + m0];
}
scatter_offsets(m0) = token_offset * problem.N;
scatter_weights(m0) = weight;
// if(threadIdx.x % 16 == 0)
// printf("init off bid %d tid %d m %d off %d\n", blockIdx.y, threadIdx.x, m0(), scatter_offsets(m0));
});
constexpr index_t scatter_weight_idx = IsInputGemm ? 1 : 3; //hack fix felix
auto cde_block_copy_lds_and_global = ThreadGroupTensorSliceTransfer_v7r3_scatter<
ThisThreadBlock,
decltype(container_concat(make_tuple(CShuffleDataType{}), DsDataType{})),
Tuple<EDataType>,
decltype(c_ds_desc_refs),
decltype(tie(e_grid_desc_mblock_mperblock_nblock_nperblock)),
CElementwiseOperation,
Sequence<static_cast<index_t>(EGlobalMemoryDataOperation)>, // FIXME: make Sequence
// support arbitray type
Sequence<1,
CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl,
1,
CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl>, // BlockSliceLengths,
CDEBlockTransferCluster,
Sequence<0, 1, 2, 3>, // typename ThreadClusterArrangeOrder,
Sequence<0, 1, 2, 3>, // typename SrcDimAccessOrder,
Sequence<0, 1, 2, 3>, // typename DstDimAccessOrder,
3, // index_t SrcVectorDim,
3, // index_t DstVectorDim,
CDEShuffleBlockTransferScalarPerVectors,
CShuffleBlockTransferScalarPerVector_NPerBlock,
sequence_merge_t<
Sequence<true>,
uniform_sequence_gen_t<NumDTensor,
false>>, // ThreadTransferSrcResetCoordinateAfterRunFlags
Sequence<false>, // ThreadTransferDstResetCoordinateAfterRunFlags
1, //ScatterDim
true, //OutputScatter: false, only use scatter weights
scatter_weight_idx // ScatterWeightIdx: ascale
>
{c_ds_desc_refs,
idx_c_ds_block_begin,
tie(e_grid_desc_mblock_mperblock_nblock_nperblock),
make_tuple(make_multi_index(0, 0, block_n_id, 0)),
c_element_op,
scatter_offsets,
scatter_weights};
auto c_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
p_c_grid, c_grid_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
// space filling curve for threadwise C in VGPR
constexpr auto sfc_c_vgpr =
SpaceFillingCurve<Sequence<MXdlPerWave, NXdlPerWave, 1, 1, M2, 1, M4, 1>,
Sequence<0, 1, 2, 3, 4, 5, 6, 7>,
Sequence<CShuffleMXdlPerWavePerShuffle,
CShuffleNXdlPerWavePerShuffle,
1,
1,
M2,
1,
M4,
1>>{};
constexpr index_t num_access = sfc_c_vgpr.GetNumOfAccess();
// space filling curve for shuffled blockwise C/D/E
constexpr auto sfc_cde_block =
SpaceFillingCurve<Sequence<1, MPerBlock, 1, NPerBlock>,
Sequence<0, 2, 1, 3>,
Sequence<1,
CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl,
1,
CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl>>{};
static_assert(num_access == sfc_cde_block.GetNumOfAccess(), "wrong!");
static_for<0, num_access, 1>{}([&](auto access_id) {
// make sure it's safe to write to LDS
block_sync_lds();
// each thread write its data from VGPR to LDS
c_thread_copy_vgpr_to_lds.Run(c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2,
sfc_c_vgpr.GetIndexTupleOfNumber(access_id),
c_thread_buf,
c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2,
c_shuffle_block_buf);
// make sure it's safe to read from LDS
block_sync_lds();
// each block copy its data from LDS to global
cde_block_copy_lds_and_global.Run(
c_ds_desc_refs,
c_ds_buf_refs,
tie(e_grid_desc_mblock_mperblock_nblock_nperblock),
tie(c_grid_buf));
if constexpr(access_id < num_access - 1)
{
constexpr auto cde_lds_and_global_step =
sfc_cde_block.GetForwardStep(access_id);
// move on Ds
static_for<0, NumDTensor, 1>{}([&](auto i) {
cde_block_copy_lds_and_global.MoveSrcSliceWindow(
c_ds_desc_refs, i + I1, cde_lds_and_global_step);
});
// move on E
cde_block_copy_lds_and_global.MoveDstSliceWindow(
tie(e_grid_desc_mblock_mperblock_nblock_nperblock),
I0,
cde_lds_and_global_step);
}
});
}
}
// template <bool HasMainKBlockLoop,
// InMemoryDataOperationEnum CGlobalMemoryDataOperation,
// bool IsInputGemm = true,
// TailNumber TailNum = TailNumber::Odd>
// __device__ static void Run_2Lds(const ADataType* p_a_grid,
// __device__ static void Run_2Lds(const index_t* p_sorted_token_ids,
// const index_t* p_sorted_expert_ids,
// const index_t* p_max_token_id,
// const ADataType* p_a_grid,
// const BDataType* p_b_grid,
// DsGridPointer& p_ds_grid,
// CDataType* p_c_grid,
@@ -1656,37 +2156,7 @@ struct GridwiseMoeGemm
// BElementwiseOperation b_element_op,
// CElementwiseOperation c_element_op)
// {
// // const auto block_2_ctile_map = Block2CTileMapDefault{problem.M, problem.N, 4};
// // Run_2Lds<Block2CTileMapDefault, HasMainKBlockLoop, CGlobalMemoryDataOperation, TailNum>(
// // p_a_grid,
// // p_b_grid,
// // p_ds_grid,
// // p_c_grid,
// // p_shared,
// // p_shared1,
// // problem,
// // a_element_op,
// // b_element_op,
// // c_element_op,
// // block_2_ctile_map);
// }
// template <typename Block2CTileMap,
// bool HasMainKBlockLoop,
// InMemoryDataOperationEnum CGlobalMemoryDataOperation,
// TailNumber TailNum = TailNumber::Odd>
// __device__ static void Run_2Lds(const ADataType* p_a_grid,
// const BDataType* p_b_grid,
// DsGridPointer& p_ds_grid,
// CDataType* p_c_grid,
// void* p_shared,
// void* p_shared1,
// const Problem& problem,
// AElementwiseOperation a_element_op,
// BElementwiseOperation b_element_op,
// CElementwiseOperation c_element_op,
// const Block2CTileMap& block_2_ctile_map)
// {
// }
};