Files
composable_kernel/host/host_tensor/include/host_gemm.hpp
Chao Liu b3e8d57d51 Tweak GEMM kernel (#38)
* add parameters

* tweak gemm

* tweak

* update conv

* update script

* adding bwd 1x1

* update script

* adding 1x1 bwd

* debugging bwd 1x1 failure

* update script

* update script

* test

* test v100

* clean up
2021-10-06 11:12:36 -05:00

160 lines
4.5 KiB
C++

#pragma once
#include "host_tensor.hpp"
#include "gemm_common.hpp"
template <typename AType, typename BType, typename CType>
void host_gemm(const Tensor<AType>& a,
const Tensor<BType>& b,
Tensor<CType>& c,
const GemmMatrixLayout layout)
{
if(layout == GemmMatrixLayout::MK_KN_MN)
{
auto f_mk_kn_mn = [&](auto m, auto n) {
const int K = a.mDesc.GetLengths()[1];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(m, k)) * static_cast<const double>(b(k, n));
}
c(m, n) = v;
};
make_ParallelTensorFunctor(f_mk_kn_mn, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::MK_NK_MN)
{
auto f_mk_nk_mn = [&](auto m, auto n) {
const int K = a.mDesc.GetLengths()[1];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(m, k)) * static_cast<const double>(b(n, k));
}
c(m, n) = v;
};
make_ParallelTensorFunctor(f_mk_nk_mn, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::KM_KN_MN)
{
auto f_km_kn_mn = [&](auto m, auto n) {
const int K = a.mDesc.GetLengths()[0];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(k, m)) * static_cast<const double>(b(k, n));
}
c(m, n) = v;
};
make_ParallelTensorFunctor(f_km_kn_mn, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::KM_NK_MN)
{
auto f_km_nk_mn = [&](auto m, auto n) {
const int K = a.mDesc.GetLengths()[0];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(k, m)) * static_cast<const double>(b(n, k));
}
c(m, n) = v;
};
make_ParallelTensorFunctor(f_km_nk_mn, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::MK_KN_NM)
{
auto f_mk_kn_nm = [&](auto n, auto m) {
const int K = a.mDesc.GetLengths()[1];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(m, k)) * static_cast<const double>(b(k, n));
}
c(n, m) = v;
};
make_ParallelTensorFunctor(f_mk_kn_nm, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::MK_NK_NM)
{
auto f_mk_nk_nm = [&](auto n, auto m) {
const int K = a.mDesc.GetLengths()[1];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(m, k)) * static_cast<const double>(b(n, k));
}
c(n, m) = v;
};
make_ParallelTensorFunctor(f_mk_nk_nm, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::KM_KN_NM)
{
auto f_km_kn_nm = [&](auto n, auto m) {
const int K = a.mDesc.GetLengths()[0];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(k, m)) * static_cast<const double>(b(k, n));
}
c(n, m) = v;
};
make_ParallelTensorFunctor(f_km_kn_nm, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::KM_NK_NM)
{
auto f_km_nk_nm = [&](auto n, auto m) {
const int K = a.mDesc.GetLengths()[0];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(k, m)) * static_cast<const double>(b(n, k));
}
c(n, m) = v;
};
make_ParallelTensorFunctor(f_km_nk_nm, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else
{
throw std::runtime_error("wrong! not supported layout");
}
}