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Commit b7c1259f authored by ltqin's avatar ltqin
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init ok

parent 0acd3ebe
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Showing with 80 additions and 70 deletions
composable_kernel/include/tensor_operation/gridwise_gemm_xdlops_v2r4.hpp
View file @ b7c1259f
......@@ -366,18 +366,20 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r4
const auto M = a_b_k0_m_k1_grid_desc.GetLength(I2);
const auto N = b_b_k0_n_k1_grid_desc.GetLength(I2);
const auto b_grid_size = CalculateGridSize(M, N);
const auto nBatch = get_block_1d_id() / b_grid_size;
const auto blockid_in_batch = get_block_1d_id() % b_grid_size;
const auto k_batch_id = get_block_1d_id() / b_grid_size;
const auto block_id_in_batch = get_block_1d_id() % b_grid_size;
if(get_block_1d_id() == 2000)
printf("grid size: %d, Batch: %d block_id: %d k0: %d\n",
printf("grid size: %d, k0: %d, blockid: %d, threadid %d, Batch: %d block_id: %d \n",
b_grid_size,
nBatch,
blockid_in_batch,
K0);
K0,
get_block_1d_id(),
get_thread_local_1d_id(),
k_batch_id,
block_id_in_batch);
// divide block work by [M, N]
const auto block_work_idx =
c_block_cluster_adaptor.CalculateBottomIndex(make_multi_index(blockid_in_batch));
c_block_cluster_adaptor.CalculateBottomIndex(make_multi_index(block_id_in_batch));
// HACK: this force m/n_block_data_idx_on_grid into SGPR
const index_t m_block_data_idx_on_grid =
......@@ -391,65 +393,69 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r4
// A matrix in LDS memory, dst of blockwise copy
// be careful of LDS alignment
constexpr auto a_b_k0_m_k1_block_desc = make_naive_tensor_descriptor_aligned(
make_tuple(1, Number<KPerBlock>{}, Number<MPerBlock>{}, K1), max_lds_align);
constexpr auto a_k0_m_k1_block_desc = make_naive_tensor_descriptor_aligned(
make_tuple(Number<KPerBlock>{}, Number<MPerBlock>{}, K1), max_lds_align);
// B matrix in LDS memory, dst of blockwise copy
// be careful of LDS alignment
constexpr auto b_b_k0_n_k1_block_desc = make_naive_tensor_descriptor_aligned(
make_tuple(1, Number<KPerBlock>{}, Number<NPerBlock>{}, K1), max_lds_align);
constexpr auto b_k0_n_k1_block_desc = make_naive_tensor_descriptor_aligned(
make_tuple(Number<KPerBlock>{}, Number<NPerBlock>{}, K1), max_lds_align);
// A matrix blockwise copy
auto a_blockwise_copy =
BlockwiseTensorSliceTransfer_v4<BlockSize,
InMemoryDataOperationEnum_t::Set,
Sequence<KPerBlock, MPerBlock, K1>,
Sequence<1, KPerBlock, MPerBlock, K1>,
ABlockTransferThreadSliceLengths_K0_M_K1,
ABlockTransferThreadClusterLengths_K0_M_K1,
ABlockTransferThreadClusterArrangeOrder,
FloatAB,
FloatAB,
decltype(a_k0_m_k1_grid_desc),
decltype(a_k0_m_k1_block_desc),
decltype(a_b_k0_m_k1_grid_desc),
decltype(a_b_k0_m_k1_block_desc),
ABlockTransferSrcAccessOrder,
Sequence<1, 0, 2>,
Sequence<0, 2, 1, 3>,
ABlockTransferSrcVectorDim,
2,
3,
ABlockTransferSrcScalarPerVector,
ABlockTransferDstScalarPerVector_K1,
1,
1,
AThreadTransferSrcResetCoordinateAfterRun,
true>(a_k0_m_k1_grid_desc,
make_multi_index(0, m_block_data_idx_on_grid, 0),
a_k0_m_k1_block_desc,
make_multi_index(0, 0, 0));
true>(a_b_k0_m_k1_grid_desc,
make_multi_index(k_batch_id, 0, m_block_data_idx_on_grid, 0),
a_b_k0_m_k1_block_desc,
make_multi_index(0, 0, 0, 0));
// B matrix blockwise copy
auto b_blockwise_copy =
BlockwiseTensorSliceTransfer_v4<BlockSize,
InMemoryDataOperationEnum_t::Set,
Sequence<KPerBlock, NPerBlock, K1>,
Sequence<1, KPerBlock, NPerBlock, K1>,
BBlockTransferThreadSliceLengths_K0_N_K1,
BBlockTransferThreadClusterLengths_K0_N_K1,
BBlockTransferThreadClusterArrangeOrder,
FloatAB,
FloatAB,
decltype(b_k0_n_k1_grid_desc),
decltype(b_k0_n_k1_block_desc),
decltype(b_b_k0_n_k1_grid_desc),
decltype(b_b_k0_n_k1_block_desc),
BBlockTransferSrcAccessOrder,
Sequence<1, 0, 2>,
Sequence<0, 2, 1, 3>,
BBlockTransferSrcVectorDim,
2,
3,
BBlockTransferSrcScalarPerVector,
BBlockTransferDstScalarPerVector_K1,
1,
1,
BThreadTransferSrcResetCoordinateAfterRun,
true>(b_k0_n_k1_grid_desc,
make_multi_index(0, n_block_data_idx_on_grid, 0),
b_k0_n_k1_block_desc,
make_multi_index(0, 0, 0));
true>(b_b_k0_n_k1_grid_desc,
make_multi_index(k_batch_id, 0, n_block_data_idx_on_grid, 0),
b_b_k0_n_k1_block_desc,
make_multi_index(0, 0, 0, 0));
// GEMM definition
// c_mtx += transpose(a_mtx) * b_mtx
......@@ -490,8 +496,8 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r4
FloatAB* p_a_block = p_shared_block;
FloatAB* p_b_block = p_shared_block + a_block_space_size;
constexpr auto a_block_slice_copy_step = make_multi_index(KPerBlock, 0, 0);
constexpr auto b_block_slice_copy_step = make_multi_index(KPerBlock, 0, 0);
constexpr auto a_block_slice_copy_step = make_multi_index(0, KPerBlock, 0, 0);
constexpr auto b_block_slice_copy_step = make_multi_index(0, KPerBlock, 0, 0);
// hack to control index calculation when iterating over A and B matrix for threadwise copy
constexpr auto a_k0_m_k1_grid_step_hacks = AGridStepHacks{};
......@@ -509,11 +515,11 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r4
// preload data into LDS
{
a_blockwise_copy.RunRead(a_k0_m_k1_grid_desc, a_grid_buf, a_k0_m_k1_grid_step_hacks);
b_blockwise_copy.RunRead(b_k0_n_k1_grid_desc, b_grid_buf, b_k0_n_k1_grid_step_hacks);
a_blockwise_copy.RunRead(a_b_k0_m_k1_grid_desc, a_grid_buf, a_k0_m_k1_grid_step_hacks);
b_blockwise_copy.RunRead(b_b_k0_n_k1_grid_desc, b_grid_buf, b_k0_n_k1_grid_step_hacks);
a_blockwise_copy.RunWrite(a_k0_m_k1_block_desc, a_block_buf);
b_blockwise_copy.RunWrite(b_k0_n_k1_block_desc, b_block_buf);
a_blockwise_copy.RunWrite(a_b_k0_m_k1_block_desc, a_block_buf);
b_blockwise_copy.RunWrite(b_b_k0_n_k1_block_desc, b_block_buf);
}
// main body
......@@ -521,25 +527,25 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r4
do
{
a_blockwise_copy.MoveSrcSliceWindow(a_k0_m_k1_grid_desc,
a_blockwise_copy.MoveSrcSliceWindow(a_b_k0_m_k1_grid_desc,
a_block_slice_copy_step,
a_k0_m_k1_grid_move_slice_window_step_hack);
b_blockwise_copy.MoveSrcSliceWindow(b_k0_n_k1_grid_desc,
b_blockwise_copy.MoveSrcSliceWindow(b_b_k0_n_k1_grid_desc,
b_block_slice_copy_step,
b_k0_n_k1_grid_move_slice_window_step_hack);
a_blockwise_copy.RunRead(a_k0_m_k1_grid_desc, a_grid_buf, a_k0_m_k1_grid_step_hacks);
a_blockwise_copy.RunRead(a_b_k0_m_k1_grid_desc, a_grid_buf, a_k0_m_k1_grid_step_hacks);
block_sync_lds();
b_blockwise_copy.RunRead(b_k0_n_k1_grid_desc, b_grid_buf, b_k0_n_k1_grid_step_hacks);
b_blockwise_copy.RunRead(b_b_k0_n_k1_grid_desc, b_grid_buf, b_k0_n_k1_grid_step_hacks);
blockwise_gemm.Run(a_block_buf, b_block_buf, c_thread_buf);
block_sync_lds();
a_blockwise_copy.RunWrite(a_k0_m_k1_block_desc, a_block_buf);
b_blockwise_copy.RunWrite(b_k0_n_k1_block_desc, b_block_buf);
a_blockwise_copy.RunWrite(a_b_k0_m_k1_block_desc, a_block_buf);
b_blockwise_copy.RunWrite(b_b_k0_n_k1_block_desc, b_block_buf);
k_block_data_begin += KPerBlock;
} while(k_block_data_begin < (K0 - KPerBlock));
......
host/driver_offline/include/device_convolution_backward_weight_implicit_gemm_v4r4r3_xdlops_nchw_kcyx_nkhw.hpp
View file @ b7c1259f
......@@ -62,21 +62,21 @@ void device_convolution_backward_weight_implicit_gemm_v4r4r3_xdlops_nchw_kcyx_nk
constexpr index_t MRepeat = 2;
constexpr index_t NRepeat = 2;
using GemmABlockTransferThreadSliceLengths_GemmK0_GemmM_GemmK1 = Sequence<1, 2, 8>;
using GemmABlockTransferThreadClusterLengths_GemmK0_GemmM_GemmK1 = Sequence<4, 64, 1>;
using GemmABlockTransferThreadSliceLengths_GemmB_GemmK0_GemmM_GemmK1 = Sequence<1, 1, 2, 8>;
using GemmABlockTransferThreadClusterLengths_GemmB_GemmK0_GemmM_GemmK1 = Sequence<1, 4, 64, 1>;
// using vector load 4, so config's wo*ho must be a multiple of 4
constexpr index_t GemmABlockTransferSrcScalarPerVector_GemmK1 = 4;
constexpr index_t GemmABlockTransferDstScalarPerVector_GemmK1 = 4;
using GemmBBlockTransferThreadSliceLengths_GemmK0_GemmN_GemmK1 = Sequence<1, 2, 8>;
using GemmBBlockTransferThreadClusterLengths_GemmK0_GemmN_GemmK1 = Sequence<4, 64, 1>;
using GemmBBlockTransferThreadSliceLengths_GemmB_GemmK0_GemmN_GemmK1 = Sequence<1, 1, 2, 8>;
using GemmBBlockTransferThreadClusterLengths_GemmB_GemmK0_GemmN_GemmK1 = Sequence<1, 4, 64, 1>;
constexpr index_t GemmBBlockTransferSrcScalarPerVector_GemmN = 1;
constexpr index_t GemmBBlockTransferDstScalarPerVector_GemmK1 = 8;
constexpr index_t GemmCThreadTransferDstScalarPerVector = 1;
constexpr index_t KBatch = 96;
constexpr index_t KBatch = 2;
#elif 1
// [M, N, K0, K1] = [128, 128, 4, 8] for fp16
constexpr index_t BlockSize = 256;
......@@ -123,20 +123,24 @@ void device_convolution_backward_weight_implicit_gemm_v4r4r3_xdlops_nchw_kcyx_nk
// HACK: hacks that control index calculation when iterating over A, B, C matrix
constexpr auto out_gemmk0_gemmm_gemmk1_grid_step_hacks =
make_tuple(make_tuple(Sequence<0, 0, 1, 0, 0>{}, // 0+: GemmK0
Sequence<0, 0, 0, 0, 0>{}, // 1+: GemmM
Sequence<0, 0, 1, 0, 0>{}), // 2+: GemmK1
make_tuple(Sequence<0, 0, 2, 0, 0>{}, // 0-: GemmK0
Sequence<0, 0, 0, 0, 0>{}, // 1-: GemmM
Sequence<0, 0, 2, 0, 0>{})); // 2-: GemmK1
make_tuple(make_tuple(Sequence<0, 0, 0, 0, 0, 0, 0, 0>{}, // 0+: GemmB
Sequence<0, 0, 0, 0, 0, 0, 0, 0>{}, // 1+: GemmK0
Sequence<0, 0, 0, 0, 0, 0, 0, 0>{}, // 2+: GemmM
Sequence<0, 0, 0, 0, 0, 0, 0, 0>{}), // 3+: GemmK1
make_tuple(Sequence<0, 0, 0, 0, 0, 0, 0, 0>{}, // 0-: GemB
Sequence<0, 0, 0, 0, 0, 0, 0, 0>{}, // 1-: GemmK0
Sequence<0, 0, 0, 0, 0, 0, 0, 0>{}, // 2-: GemmM
Sequence<0, 0, 0, 0, 0, 0, 0, 0>{})); // 3-: GemmK1
constexpr auto in_gemmk0_gemmn_gemmk1_grid_step_hacks =
make_tuple(make_tuple(Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0>{}, // 0+: GemmK0
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0>{}, // 1+: GemmN
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0>{}), // 2+: GemmK1
make_tuple(Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0>{}, // 0-: GemmK0
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0>{}, // 1-: GemmN
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0>{})); // 2-: GemmK1
make_tuple(make_tuple(Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{}, // 0+: GemmB
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{}, // 1+: GemmK0
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{}, // 2+: GemmN
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{}), // 3+: GemmK1
make_tuple(Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{}, // 0-: GemmB
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{}, // 1-: GemmK0
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{}, // 2-: GemmN
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{})); // 3-: GemmK1
constexpr auto wei_m0_n0_m1_n1_m2_m3_m4_n2_grid_step_hacks =
make_tuple(make_tuple(Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{}, // 0+: M0
......@@ -157,10 +161,10 @@ void device_convolution_backward_weight_implicit_gemm_v4r4r3_xdlops_nchw_kcyx_nk
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{})); // 7-: N2
constexpr auto out_gemmk0_gemmm_gemmk1_grid_move_slice_window_step_hacks =
Sequence<0, 0, 1, 0, 0>{};
Sequence<0, 0, 0, 0, 0, 0, 0, 0>{};
constexpr auto in_gemmk0_gemmn_gemmk1_grid_move_slice_window_step_hacks =
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0>{};
Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{};
for(index_t i = 0; i < 5; ++i)
{
......@@ -181,19 +185,19 @@ void device_convolution_backward_weight_implicit_gemm_v4r4r3_xdlops_nchw_kcyx_nk
GemmK1,
MRepeat,
NRepeat,
GemmABlockTransferThreadSliceLengths_GemmK0_GemmM_GemmK1,
GemmABlockTransferThreadClusterLengths_GemmK0_GemmM_GemmK1,
Sequence<1, 0, 2>,
Sequence<1, 0, 2>,
2,
GemmABlockTransferThreadSliceLengths_GemmB_GemmK0_GemmM_GemmK1,
GemmABlockTransferThreadClusterLengths_GemmB_GemmK0_GemmM_GemmK1,
Sequence<0, 2, 1, 3>,
Sequence<0, 2, 1, 3>,
3,
GemmABlockTransferSrcScalarPerVector_GemmK1,
GemmABlockTransferDstScalarPerVector_GemmK1,
false, // don't move back src coordinate after threadwise copy
GemmBBlockTransferThreadSliceLengths_GemmK0_GemmN_GemmK1,
GemmBBlockTransferThreadClusterLengths_GemmK0_GemmN_GemmK1,
Sequence<1, 0, 2>,
Sequence<1, 0, 2>,
2,
GemmBBlockTransferThreadSliceLengths_GemmB_GemmK0_GemmN_GemmK1,
GemmBBlockTransferThreadClusterLengths_GemmB_GemmK0_GemmN_GemmK1,
Sequence<0, 2, 1, 3>,
Sequence<0, 2, 1, 3>,
3,
GemmBBlockTransferSrcScalarPerVector_GemmN,
GemmBBlockTransferDstScalarPerVector_GemmK1,
false, // don't move back src coordinate after threadwise copy
......
host/driver_offline/src/conv_wrw_driver_offline.cpp
View file @ b7c1259f
......@@ -233,6 +233,8 @@ int main(int argc, char* argv[])
in_right_pads_dev);
};
// set zero to wei_device
wei_device.GenerateTensorValue(GeneratorTensor_0{}, num_thread);
#if USE_CONV_WRW_V4R4R2_XDL_NCHW
if(algo == ConvBackwardWeightAlgo::V4R4R2XDLNCHW)
{
......@@ -267,8 +269,6 @@ int main(int argc, char* argv[])
{
throw std::runtime_error("wrong! layout");
}
// set zero to wei_device
wei_device.GenerateTensorValue(GeneratorTensor_0{}, num_thread);
const auto tmp = f_make_for_device_nchw();
......
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