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Unverified Commit 88833bd9 authored by Chao Liu's avatar Chao Liu Committed by GitHub
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Merge pull request #32 from ROCmSoftwarePlatform/develop 

Merge develop into master
parents 31b40352 f3acd251
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host/driver_offline/src/gemm_driver_offline.cpp 0 → 100644
View file @ 88833bd9
#include <iostream>
#include <numeric>
#include <initializer_list>
#include <cstdlib>
#include <stdlib.h>
#include <half.hpp>
#include "config.hpp"
#include "print.hpp"
#include "device.hpp"
#include "host_tensor.hpp"
#include "host_tensor_generator.hpp"
#include "gemm_common.hpp"
#include "host_gemm.hpp"
#include "device_tensor.hpp"
#include "device_gemm_xdlops_mk_kn_mn.hpp"
#include "device_gemm_xdlops_mk_nk_mn.hpp"
#include "device_gemm_xdlops_km_kn_mn.hpp"
#include "device_gemm_xdlops_km_nk_mn.hpp"
#define USE_GEMM_XDL_MK_KN_MN 1
#define USE_GEMM_XDL_MK_NK_MN 1
#define USE_GEMM_XDL_KM_KN_MN 1
#define USE_GEMM_XDL_KM_NK_MN 1
enum GemmAlgo
{
Xdl_MK_KN_MN, // 0
Xdl_MK_NK_MN, // 1
Xdl_KM_KN_MN, // 2
Xdl_KM_NK_MN, // 3
};
int main(int argc, char* argv[])
{
using namespace ck;
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
// dynamic mode
if(argc != 10)
{
printf("arg1 to 6: layout, algo, do_verification, init_method, do_log, nrepeat\n");
printf("rest: M, N, K\n");
exit(1);
}
const auto layout = static_cast<GemmMatrixLayout>(std::stoi(argv[1]));
const auto algo = static_cast<GemmAlgo>(std::stoi(argv[2]));
const bool do_verification = std::stoi(argv[3]);
const int init_method = std::stoi(argv[4]);
const bool do_log = std::stoi(argv[5]);
const int nrepeat = std::stoi(argv[6]);
const index_t M = std::stoi(argv[7]);
const index_t N = std::stoi(argv[8]);
const index_t K = std::stoi(argv[9]);
#if 0
using ab_data_t = float;
using acc_data_t = float;
using c_data_t = float;
#elif 1
using ab_data_t = half_t;
using acc_data_t = float;
using c_data_t = half_t;
#elif 1
using ab_data_t = int8_t;
using acc_data_t = int32_t;
using c_data_t = int8_t;
#endif
std::vector<std::size_t> a_lengths_host(2), b_lengths_host(2), c_lengths_host(2);
std::vector<std::size_t> a_strides_host(2), b_strides_host(2), c_strides_host(2);
if(layout == GemmMatrixLayout::MK_KN_MN)
{
a_lengths_host[0] = static_cast<std::size_t>(M);
a_lengths_host[1] = static_cast<std::size_t>(K);
a_strides_host[0] = static_cast<std::size_t>(K);
a_strides_host[1] = static_cast<std::size_t>(1);
b_lengths_host[0] = static_cast<std::size_t>(K);
b_lengths_host[1] = static_cast<std::size_t>(N);
b_strides_host[0] = static_cast<std::size_t>(N);
b_strides_host[1] = static_cast<std::size_t>(1);
c_lengths_host[0] = static_cast<std::size_t>(M);
c_lengths_host[1] = static_cast<std::size_t>(N);
c_strides_host[0] = static_cast<std::size_t>(N);
c_strides_host[1] = static_cast<std::size_t>(1);
}
else if(layout == GemmMatrixLayout::MK_NK_MN)
{
a_lengths_host[0] = static_cast<std::size_t>(M);
a_lengths_host[1] = static_cast<std::size_t>(K);
a_strides_host[0] = static_cast<std::size_t>(K);
a_strides_host[1] = static_cast<std::size_t>(1);
b_lengths_host[0] = static_cast<std::size_t>(N);
b_lengths_host[1] = static_cast<std::size_t>(K);
b_strides_host[0] = static_cast<std::size_t>(K);
b_strides_host[1] = static_cast<std::size_t>(1);
c_lengths_host[0] = static_cast<std::size_t>(M);
c_lengths_host[1] = static_cast<std::size_t>(N);
c_strides_host[0] = static_cast<std::size_t>(N);
c_strides_host[1] = static_cast<std::size_t>(1);
}
else if(layout == GemmMatrixLayout::KM_KN_MN)
{
a_lengths_host[0] = static_cast<std::size_t>(K);
a_lengths_host[1] = static_cast<std::size_t>(M);
a_strides_host[0] = static_cast<std::size_t>(M);
a_strides_host[1] = static_cast<std::size_t>(1);
b_lengths_host[0] = static_cast<std::size_t>(K);
b_lengths_host[1] = static_cast<std::size_t>(N);
b_strides_host[0] = static_cast<std::size_t>(N);
b_strides_host[1] = static_cast<std::size_t>(1);
c_lengths_host[0] = static_cast<std::size_t>(M);
c_lengths_host[1] = static_cast<std::size_t>(N);
c_strides_host[0] = static_cast<std::size_t>(N);
c_strides_host[1] = static_cast<std::size_t>(1);
}
else if(layout == GemmMatrixLayout::KM_NK_MN)
{
a_lengths_host[0] = static_cast<std::size_t>(K);
a_lengths_host[1] = static_cast<std::size_t>(M);
a_strides_host[0] = static_cast<std::size_t>(M);
a_strides_host[1] = static_cast<std::size_t>(1);
b_lengths_host[0] = static_cast<std::size_t>(N);
b_lengths_host[1] = static_cast<std::size_t>(K);
b_strides_host[0] = static_cast<std::size_t>(K);
b_strides_host[1] = static_cast<std::size_t>(1);
c_lengths_host[0] = static_cast<std::size_t>(M);
c_lengths_host[1] = static_cast<std::size_t>(N);
c_strides_host[0] = static_cast<std::size_t>(N);
c_strides_host[1] = static_cast<std::size_t>(1);
}
else
{
std::runtime_error("wrong! not implemented");
}
Tensor<ab_data_t> a(a_lengths_host, a_strides_host);
Tensor<ab_data_t> b(b_lengths_host, b_strides_host);
Tensor<c_data_t> c_host(c_lengths_host, c_strides_host);
Tensor<c_data_t> c_device(c_lengths_host, c_strides_host);
std::cout << "layout: " << layout << std::endl;
ostream_HostTensorDescriptor(a.mDesc, std::cout << "a: ");
ostream_HostTensorDescriptor(b.mDesc, std::cout << "b: ");
ostream_HostTensorDescriptor(c_host.mDesc, std::cout << "c: ");
std::size_t num_thread = std::thread::hardware_concurrency();
switch(init_method)
{
case 0:
// no initialization
break;
case 1:
a.GenerateTensorValue(GeneratorTensor_1{}, num_thread);
b.GenerateTensorValue(GeneratorTensor_1{}, num_thread);
break;
case 2:
a.GenerateTensorValue(GeneratorTensor_1{}, num_thread);
b.GenerateTensorValue(GeneratorTensor_2{-5, 5}, num_thread);
break;
case 3:
a.GenerateTensorValue(GeneratorTensor_2{-5, 5}, num_thread);
b.GenerateTensorValue(GeneratorTensor_1{}, num_thread);
break;
case 4:
a.GenerateTensorValue(GeneratorTensor_2{-5, 5}, num_thread);
b.GenerateTensorValue(GeneratorTensor_2{-5, 5}, num_thread);
break;
default:
a.GenerateTensorValue(GeneratorTensor_3<float>{0.0, 1.0}, num_thread);
b.GenerateTensorValue(GeneratorTensor_3<float>{-0.5, 0.5}, num_thread);
}
auto f_make_for_device_mk_kn_mn = [&]() {
const auto a_desc = make_naive_tensor_descriptor(make_tuple(M, K), make_tuple(K, I1));
const auto b_desc = make_naive_tensor_descriptor(make_tuple(K, N), make_tuple(N, I1));
const auto c_desc = make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(N, I1));
return make_tuple(a_desc, b_desc, c_desc);
};
auto f_make_for_device_mk_nk_mn = [&]() {
const auto a_desc = make_naive_tensor_descriptor(make_tuple(M, K), make_tuple(K, I1));
const auto b_desc = make_naive_tensor_descriptor(make_tuple(N, K), make_tuple(K, I1));
const auto c_desc = make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(N, I1));
return make_tuple(a_desc, b_desc, c_desc);
};
auto f_make_for_device_km_kn_mn = [&]() {
const auto a_desc = make_naive_tensor_descriptor(make_tuple(K, M), make_tuple(M, I1));
const auto b_desc = make_naive_tensor_descriptor(make_tuple(K, N), make_tuple(N, I1));
const auto c_desc = make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(N, I1));
return make_tuple(a_desc, b_desc, c_desc);
};
auto f_make_for_device_km_nk_mn = [&]() {
const auto a_desc = make_naive_tensor_descriptor(make_tuple(K, M), make_tuple(M, I1));
const auto b_desc = make_naive_tensor_descriptor(make_tuple(N, K), make_tuple(K, I1));
const auto c_desc = make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(N, I1));
return make_tuple(a_desc, b_desc, c_desc);
};
#if USE_GEMM_XDL_MK_KN_MN
if(algo == GemmAlgo::Xdl_MK_KN_MN)
{
if(layout != GemmMatrixLayout::MK_KN_MN)
{
throw std::runtime_error("wrong! layout");
}
const auto descs = f_make_for_device_mk_kn_mn();
device_gemm_xdlops_mk_kn_mn<ab_data_t, acc_data_t, c_data_t>(
descs[I0], descs[I1], descs[I2], a, b, c_device, nrepeat);
}
#endif
#if USE_GEMM_XDL_MK_NK_MN
if(algo == GemmAlgo::Xdl_MK_NK_MN)
{
if(layout != GemmMatrixLayout::MK_NK_MN)
{
throw std::runtime_error("wrong! layout");
}
const auto descs = f_make_for_device_mk_nk_mn();
device_gemm_xdlops_mk_nk_mn<ab_data_t, acc_data_t, c_data_t>(
descs[I0], descs[I1], descs[I2], a, b, c_device, nrepeat);
}
#endif
#if USE_GEMM_XDL_KM_KN_MN
if(algo == GemmAlgo::Xdl_KM_KN_MN)
{
if(layout != GemmMatrixLayout::KM_KN_MN)
{
throw std::runtime_error("wrong! layout");
}
const auto descs = f_make_for_device_km_kn_mn();
device_gemm_xdlops_km_kn_mn<ab_data_t, acc_data_t, c_data_t>(
descs[I0], descs[I1], descs[I2], a, b, c_device, nrepeat);
}
#endif
#if USE_GEMM_XDL_KM_NK_MN
if(algo == GemmAlgo::Xdl_KM_NK_MN)
{
if(layout != GemmMatrixLayout::KM_NK_MN)
{
throw std::runtime_error("wrong! layout");
}
const auto descs = f_make_for_device_km_nk_mn();
device_gemm_xdlops_km_nk_mn<ab_data_t, acc_data_t, c_data_t>(
descs[I0], descs[I1], descs[I2], a, b, c_device, nrepeat);
}
#endif
if(do_verification)
{
host_gemm(a, b, c_host, layout);
check_error(c_host, c_device);
if(do_log)
{
LogRangeAsType<float>(std::cout << "a : ", a.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "b: ", b.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "c_host : ", c_host.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "c_device: ", c_device.mData, ",") << std::endl;
}
}
}
host/host_tensor/include/gemm_common.hpp 0 → 100644
View file @ 88833bd9
#ifndef GEMM_COMMON_HPP
#define GEMM_COMMON_HPP
enum GemmMatrixLayout
{
MK_KN_MN, // 0
MK_NK_MN, // 1
KM_KN_MN, // 2
KM_NK_MN, // 3
};
#endif
host/host_tensor/include/host_conv_bwd_weight.hpp 0 → 100644
View file @ 88833bd9
#pragma once
#include "host_tensor.hpp"
template <typename TOut,
typename TIn,
typename TWei,
typename ConvStrides,
typename ConvDilations,
typename InLeftPads,
typename InRightPads>
void host_direct_convolution_backward_weights(
const Tensor<TOut>& out,
const Tensor<TIn>& in,
Tensor<TWei>& wei,
const ConvStrides& conv_strides,
const ConvDilations& conv_dilations,
const InLeftPads& in_left_pads,
const InRightPads&,
const ConvTensorLayout layout = ConvTensorLayout::NCHW)
{
using namespace ck;
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
auto f_kcyx = [&](auto k, auto c, auto y, auto x) {
double v = 0;
for(int n = 0; n < out.mDesc.GetLengths()[0]; ++n)
{
for(int ho = 0; ho < out.mDesc.GetLengths()[2]; ++ho)
{
int hi = ho * conv_strides[I0] + y * conv_dilations[I0] - in_left_pads[I0];
for(int wo = 0; wo < out.mDesc.GetLengths()[3]; ++wo)
{
int wi = wo * conv_strides[I1] + x * conv_dilations[I1] - in_left_pads[I1];
if(hi >= 0 && hi < in.mDesc.GetLengths()[2] && wi >= 0 &&
wi < in.mDesc.GetLengths()[3])
{
v += static_cast<const double>(in(n, c, hi, wi)) *
static_cast<const double>(out(n, k, ho, wo));
}
}
}
}
wei(k, c, y, x) = v;
};
auto f_kyxc = [&](auto k, auto y, auto x, auto c) {
double v = 0;
for(int n = 0; n < out.mDesc.GetLengths()[0]; ++n)
{
for(int ho = 0; ho < out.mDesc.GetLengths()[1]; ++ho)
{
int hi = ho * conv_strides[I0] + y * conv_dilations[I0] - in_left_pads[I0];
for(int wo = 0; wo < out.mDesc.GetLengths()[2]; ++wo)
{
int wi = wo * conv_strides[I1] + x * conv_dilations[I1] - in_left_pads[I1];
if(hi >= 0 && hi < in.mDesc.GetLengths()[1] && wi >= 0 &&
wi < in.mDesc.GetLengths()[2])
{
v += static_cast<const double>(in(n, hi, wi, c)) *
static_cast<const double>(out(n, ho, wo, k));
}
}
}
}
wei(k, y, x, c) = v;
};
if(layout == ConvTensorLayout::NCHW)
{
make_ParallelTensorFunctor(f_kcyx,
wei.mDesc.GetLengths()[0],
wei.mDesc.GetLengths()[1],
wei.mDesc.GetLengths()[2],
wei.mDesc.GetLengths()[3])(std::thread::hardware_concurrency());
}
else if(layout == ConvTensorLayout::NHWC)
{
make_ParallelTensorFunctor(f_kyxc,
wei.mDesc.GetLengths()[0],
wei.mDesc.GetLengths()[1],
wei.mDesc.GetLengths()[2],
wei.mDesc.GetLengths()[3])(std::thread::hardware_concurrency());
}
else
{
throw std::runtime_error("wrong! not supported layout");
}
}
host/host_tensor/include/host_gemm.hpp 0 → 100644
View file @ 88833bd9
#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
{
throw std::runtime_error("wrong! not supported layout");
}
}
host/solver/include/conv_tunable_fwd_v4r4_xdlops_nchw_kcyx_nkhw.hpp
View file @ 88833bd9
...@@ -9,8 +9,8 @@ struct tunable_dyn_conv_fwd_v4r4_xdlops_nchw_kcyx_nkhw ...@@ -9,8 +9,8 @@ struct tunable_dyn_conv_fwd_v4r4_xdlops_nchw_kcyx_nkhw
int NPerBlock; int NPerBlock;
int KPerBlock; int KPerBlock;
int MPerWave; int MPerXDL;
int NPerWave; int NPerXDL;
int K1; int K1;
int MRepeat; int MRepeat;
...@@ -45,8 +45,8 @@ static tunable_dyn_conv_fwd_v4r4_xdlops_nchw_kcyx_nkhw ...@@ -45,8 +45,8 @@ static tunable_dyn_conv_fwd_v4r4_xdlops_nchw_kcyx_nkhw
128, // MPerBlock, 128, // MPerBlock,
128, // NPerBlock, 128, // NPerBlock,
4, // KPerBlock, 4, // KPerBlock,
32, // MPerWave, 32, // MPerXDL,
32, // NPerWave, 32, // NPerXDL,
4, // K1, 4, // K1,
2, // MRepeat, 2, // MRepeat,
2, // NRepeat, 2, // NRepeat,
......
script/run.sh
View file @ 88833bd9
...@@ -12,13 +12,16 @@ ...@@ -12,13 +12,16 @@
#export OLC_DEBUG_HIP_DUMP=1 #export OLC_DEBUG_HIP_DUMP=1
#export OLC_DEBUG_SAVE_TEMP_DIR=1 #export OLC_DEBUG_SAVE_TEMP_DIR=1
make -j conv_fwd_driver_offline
make -j conv_bwd_driver_offline
make -j conv_fwd_driver_online
#rm -rf /root/_hip_binary_kernels_/ #rm -rf /root/_hip_binary_kernels_/
#rm -rf /tmp/olCompile* #rm -rf /tmp/olCompile*
#make -j conv_fwd_driver_offline
#make -j conv_bwd_driver_offline
#make -j conv_wrw_driver_offline
#make -j conv_fwd_driver_online
make -j gemm_driver_offline
LAYOUT=$1 LAYOUT=$1
ALGO=$2 ALGO=$2
VERIFY=$3 VERIFY=$3
...@@ -30,7 +33,7 @@ REPEAT=$6 ...@@ -30,7 +33,7 @@ REPEAT=$6
#./host/driver_offline/conv_fwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 128 128 192 3 3 71 71 2 2 1 1 1 1 1 1 #./host/driver_offline/conv_fwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 128 128 192 3 3 71 71 2 2 1 1 1 1 1 1
#./host/driver_offline/conv_fwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 128 256 192 3 3 71 71 2 2 1 1 1 1 1 1 #./host/driver_offline/conv_fwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 128 256 192 3 3 71 71 2 2 1 1 1 1 1 1
#./host/driver_offline/conv_fwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 128 256 1024 1 7 17 17 1 1 1 1 0 3 0 3 #./host/driver_offline/conv_fwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 128 256 1024 1 7 17 17 1 1 1 1 0 3 0 3
./host/driver_offline/conv_fwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 256 256 256 3 3 14 14 1 1 1 1 1 1 1 1 #./host/driver_offline/conv_fwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 256 256 256 3 3 14 14 1 1 1 1 1 1 1 1
#./host/driver_offline/conv_fwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 128 128 128 3 3 14 14 1 1 1 1 1 1 1 1 #./host/driver_offline/conv_fwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 128 128 128 3 3 14 14 1 1 1 1 1 1 1 1
#./host/driver_offline/conv_fwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 256 512 512 3 3 7 7 1 1 1 1 1 1 1 1 #./host/driver_offline/conv_fwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 256 512 512 3 3 7 7 1 1 1 1 1 1 1 1
...@@ -44,4 +47,12 @@ REPEAT=$6 ...@@ -44,4 +47,12 @@ REPEAT=$6
#./host/driver_offline/conv_bwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 256 256 256 3 3 14 14 1 1 1 1 1 1 1 1 #./host/driver_offline/conv_bwd_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 256 256 256 3 3 14 14 1 1 1 1 1 1 1 1
#./host/driver_online/conv_fwd_driver_online $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 128 256 192 3 3 71 71 2 2 1 1 1 1 1 1 #./host/driver_offline/conv_wrw_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 128 256 128 3 3 14 14 1 1 1 1 1 1 1 1
#./host/driver_online/conv_fwd_driver_online $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 128 128 192 3 3 71 71 2 2 1 1 1 1 1 1
################################################ layout algo verify init log repeat M___ N___ K___
#./host/driver_offline/gemm_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 960 1024 1024
#./host/driver_offline/gemm_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 1920 2048 2048
./host/driver_offline/gemm_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 3840 4096 4096
#./host/driver_offline/gemm_driver_offline $LAYOUT $ALGO $VERIFY $INIT $LOG $REPEAT 7680 8192 8192
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