adding implicit gemm

[ROCm/composable_kernel commit: dc60d16962]
This commit is contained in:
Chao Liu
2019-01-09 19:12:22 -06:00
parent a943d79f4c
commit 61e180de4a
3 changed files with 416 additions and 0 deletions

View File

@@ -0,0 +1,178 @@
#pragma once
#include "constant_tensor_descriptor.cuh"
#include "blockwise_tensor_op.cuh"
#include "threadwise_tensor_op.cuh"
template <unsigned GridSize,
unsigned BlockSize,
class Float,
class InGlobalDesc,
class WeiGlobalDesc,
class OutGlobalDesc,
unsigned NPerBlock,
unsigned KPerBlock,
unsigned CPerBlock,
unsigned HoPerBlock,
unsigned WoPerBlock,
unsigned KPerThread,
unsigned CPerThread,
unsigned HoPerThread,
unsigned WoPerThread>
__global__ void gridwise_implicit_gemm_convolution_nchw_kcsr(InGlobalDesc,
Float* const __restrict__ p_in_global,
WeiGlobalDesc,
Float* const __restrict__ p_wei_global,
OutGlobalDesc,
Float* __restrict__ p_out_global)
{
// NPerThread == NPerBlock, because the format of input in LDS [C,Hi,Wi,N]
// for GEMM trans([C,K]) * [C,Wo*N], we need a thread to do all the "N"
// if we use [C,Hi,N,Wi,N] in LDS, then NPerThread can be different from NPerBlock
constexpr unsigned NPerThread = NPerBlock;
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto True = Constant<bool, true>;
constexpr auto False = Constant<bool, false>;
constexpr auto in_nchw_global_desc = InGlobalDesc{};
constexpr auto wei_kcsr_global_desc = WeiGlobalDesc{};
constexpr auto out_nkhw_global_desc = OutGlobalDesc{};
constexpr unsigned S = wei_kcsr_global_desc.GetLength(I2);
constexpr unsigned R = wei_kcsr_global_desc.GetLength(I3);
constexpr unsigned HiPerBlock = HoPerBlock + S - 1;
constexpr unsigned WiPerBlock = WoPerBlock + R - 1;
// block
constexpr auto in_chwn_block_desc =
make_ConstantTensorDescriptor(Sequence<CPerBlock, HiPerBlock, WiPerBlock, NPerBlock>{});
constexpr auto wei_srck_block_desc =
make_ConstantTensorDescriptor(Sequence<S, R, CPerBlock, KPerBlock>{});
// LDS
constexpr unsigned in_block_size = in_chwn_block_desc.GetElementSpace();
constexpr unsigned wei_block_size = wei_srck_block_desc.GetElementSpace();
__shared__ Float p_in_block[in_block_size];
__shared__ Float p_wei_block[wei_block_size];
// thread
constexpr auto out_hkwn_thread_desc = xxxxxx();
// register
Float p_out_thread[out_hkwn_thread_desc.GetElementSpace()];
// set threadwise output tensor to 0
threadwise_4d_tensor_set_zero(out_hkwn_thread_desc, p_out_thread);
for(unsigned c_block_data_begin = 0; c_block_data_begin < in_global_desc.GetLength(I1);
c_block_data_begin += CPerBlock, __syncthreads())
{
// input: global mem to LDS,
// convert 4d-tensor in[N,C,Hi,Wi] to matrix in_matrix[C,Hi*Wi*N]
constexpr auto reorder_nchw2chwn = Sequence<3, 0, 1, 2>{};
blockwise_4d_tensor_copy_reorder<BlockSize>(in_nchw_global_desc,
p_in_global,
in_chwn_block_desc,
p_in_block,
in_chwn_block_desc,
reorder_nchw2chwn);
// matrix view of input
constexpr unsigned in_row = in_chwn_block_desc.GetLength(I0);
constexpr unsigned in_col = in_chwn_block_desc.GetLength(I1) *
in_chwn_block_desc.GetLength(I2) *
in_chwn_block_desc.GetLength(I3);
constexpr auto in_cxhwn_block_mtx_desc =
make_ConstantMatrixDescriptor(Number<in_row>, Number<in_col>, Number<in_col>);
// weight: global mem to LDS,
// convert 4d-tensor wei[K,C,S,R] to matrix wei_matrix[S*R*C,K]
constexpr auto reorder_kcsr2srck = Sequence<3, 2, 0, 1>{};
blockwise_4d_tensor_copy_reorder<BlockSize>(wei_csrk_global_desc,
p_wei_global,
wei_csrk_block_desc,
p_wei_block,
wei_csrk_block_desc,
reorder_kcsr2csrk);
// matrix view of wei
constexpr unsigned wei_row = wei_srck_block_desc.GetLength(I0) *
wei_srck_block_desc.GetLength(I1) *
wei_srck_block_desc.GetLength(I2);
constexpr unsigned wei_col = wei_srck_block_desc.GetLength(I3);
constexpr auto wei_srcxk_block_mtx_desc =
make_ConstantMatrixDescriptor(Number<wei_row>, Number<wei_col>, Number<wei_col>);
__syncthreads();
// a series of batched GEMM
// blockwise batched GEMM, C_matrix += transpose(A_matrix) * B_matrix
// A_matrix and B_matrix saved in LDS, c_matrix saved in register
// A_matrix[C,K] is a sub-matrix of wei_matrix[S*R*C,K]
// B_matrix[C,Wo*N] is a sub-matrix of in_matrix[C,Hi*Wi*N]
// C_matrix[K,Wo*N] is a sub-matrix of out_matrix[Ho*K,Wo*N]
constexpr auto a_block_mtx_desc = wei_srcxk_block_mtx_desc.MakeSubMatrixDescriptor(
Number<CPerBlock>{}, Number<KPerBlock>{});
constexpr auto b_block_mtx_desc = in_cxhwn_block_mtx_desc.MakeSubMatrixDescriptor(
Number<CPerBlock>{}, Number<WoPerBlock * NPerBlock>{});
auto f_accum = (auto& c, auto& v) { c += v; };
const auto blockwise_batch_gemm =
blockwise_1d_strided_batched_gemm_block_a_block_b_thread_c<BlockSize,
a_block_mtx_desc,
b_block_mtx_desc,
true,
false,
HoPerBlock,
0,
xxx_b_matrix_stride,
HoPerThread,
KPerThread,
NPerThread * WoPerThread,
CPerTrhead,
decltype(f_accum)>{};
// loop over filter point
for(unsigned s = 0; s < S; ++s)
{
for(unsigned r = 0; r < R; ++r)
{
blockwise_batch_gemm.run(
p_wei_block + wei_srcxk_block_mtx_desc.Get1dIndex(xxxxx, xxxx),
p_in_block + in_cxhwn_block_mtx_desc.Get1dIndex(xxxx, xxxx),
p_out_thread);
}
}
}
const auto matrix_c_index =
blockwise_batch_gemm.CalculateThreadMatrixCIndex(get_thread_local_id());
const unsigned ho_thread_data_begin = matrix_c_index.batch_begin;
const unsigned k_thread_data_begin = matrix_c_index.col_begin;
const unsigned wo_thread_data_begin = matrix_c_index.row_begin / NPerThread;
// output: register to global mem,
// convert matrix out_matrix[Ho*K,Wo*N] to 4d-tensor out[N,K,Ho,Wo]
constexpr auto reorder_hkwn2nkhw = Sequence<2, 1, 3, 0>{};
threadwise_4d_tensor_copy_reorder(
out_hkwn_thread_desc,
p_out_thread,
out_nkhw_global_desc,
p_out_global + out_nkhw_global_desc.GetIndex(n_block_data_begin,
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin),
out_hkwn_thread_desc,
reorder_hkwn2nkhw);
}