mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-11 17:00:18 +00:00
177 lines
7.7 KiB
C++
177 lines
7.7 KiB
C++
// SPDX-License-Identifier: MIT
|
|
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
|
|
|
|
#include <iomanip>
|
|
#include <iostream>
|
|
#include <vector>
|
|
|
|
#include "ck/ck.hpp"
|
|
#include "ck/library/tensor_operation_instance/gpu/convolution_forward.hpp"
|
|
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
|
|
#include "ck/tensor_operation/gpu/device/device_conv_fwd.hpp"
|
|
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
|
|
|
|
using InDataType = ck::half_t;
|
|
using WeiDataType = ck::half_t;
|
|
using OutDataType = ck::half_t;
|
|
|
|
using InLayout = ck::tensor_layout::convolution::NHWC;
|
|
using WeiLayout = ck::tensor_layout::convolution::KYXC;
|
|
using OutLayout = ck::tensor_layout::convolution::NHWK;
|
|
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
|
|
|
static constexpr ck::index_t NumDimSpatial = 2;
|
|
static constexpr ck::index_t N = 16;
|
|
static constexpr ck::index_t K = 32;
|
|
static constexpr ck::index_t C = 3;
|
|
static constexpr ck::index_t Y = 3;
|
|
static constexpr ck::index_t X = 3;
|
|
static constexpr ck::index_t Hi = 224;
|
|
static constexpr ck::index_t Wi = 224;
|
|
static constexpr ck::index_t Ho = 113;
|
|
static constexpr ck::index_t Wo = 113;
|
|
|
|
struct SimpleDeviceMem
|
|
{
|
|
SimpleDeviceMem() = delete;
|
|
|
|
SimpleDeviceMem(std::size_t mem_size) : p_mem_{}
|
|
{
|
|
(void)hipMalloc(static_cast<void**>(&p_mem_), mem_size);
|
|
}
|
|
|
|
void* GetDeviceBuffer() { return p_mem_; }
|
|
|
|
~SimpleDeviceMem() { (void)hipFree(p_mem_); }
|
|
|
|
void* p_mem_;
|
|
};
|
|
|
|
int main(int argc, char* argv[])
|
|
{
|
|
std::vector<ck::index_t> in_spatial_lengths{Hi, Wi};
|
|
std::vector<ck::index_t> filter_spatial_lengths{Y, X};
|
|
std::vector<ck::index_t> out_spatial_lengths{Ho, Wo};
|
|
std::vector<ck::index_t> filter_strides{2, 2};
|
|
std::vector<ck::index_t> filter_dilations{1, 1};
|
|
std::vector<ck::index_t> input_left_pads{2, 2};
|
|
std::vector<ck::index_t> input_right_pads{2, 2};
|
|
|
|
SimpleDeviceMem in(sizeof(InDataType) * N * Hi * Wi * C);
|
|
SimpleDeviceMem wei(sizeof(WeiDataType) * K * Y * X * C);
|
|
SimpleDeviceMem out(sizeof(OutDataType) * N * Ho * Wo * K);
|
|
|
|
using DeviceOp = ck::tensor_operation::device::DeviceConvFwd<NumDimSpatial,
|
|
InLayout,
|
|
WeiLayout,
|
|
OutLayout,
|
|
InDataType,
|
|
WeiDataType,
|
|
OutDataType,
|
|
PassThrough,
|
|
PassThrough,
|
|
PassThrough>;
|
|
// get device op instances
|
|
const auto op_ptrs = ck::tensor_operation::device::instance::DeviceOperationInstanceFactory<
|
|
DeviceOp>::GetInstances();
|
|
|
|
std::cout << "found " << op_ptrs.size() << " instances" << std::endl;
|
|
|
|
std::string best_op_name;
|
|
int best_op_id = -1;
|
|
float best_avg_time = std::numeric_limits<float>::max();
|
|
float best_gb_per_sec = 0;
|
|
float best_tflops = 0;
|
|
|
|
// profile device operation instances
|
|
std::cout << "Run all instances and do timing" << std::endl;
|
|
|
|
for(int i = 0; i < op_ptrs.size(); ++i)
|
|
{
|
|
auto& op_ptr = op_ptrs[i];
|
|
auto argument_ptr = op_ptr->MakeArgumentPointer(in.GetDeviceBuffer(),
|
|
wei.GetDeviceBuffer(),
|
|
out.GetDeviceBuffer(),
|
|
N,
|
|
K,
|
|
C,
|
|
in_spatial_lengths,
|
|
filter_spatial_lengths,
|
|
out_spatial_lengths,
|
|
filter_strides,
|
|
filter_dilations,
|
|
input_left_pads,
|
|
input_right_pads,
|
|
PassThrough{},
|
|
PassThrough{},
|
|
PassThrough{});
|
|
auto invoker_ptr = op_ptr->MakeInvokerPointer();
|
|
std::string op_name = op_ptr->GetTypeString();
|
|
|
|
if(op_ptr->IsSupportedArgument(argument_ptr.get()))
|
|
{
|
|
float avg_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, true});
|
|
|
|
std::size_t flop = 2 * N * K * C * Ho * Wo * Y * X;
|
|
std::size_t num_bytes = sizeof(InDataType) * N * Hi * Wi * C +
|
|
sizeof(WeiDataType) * K * Y * X * C +
|
|
sizeof(OutDataType) * N * Ho * Wo * K;
|
|
|
|
float tflops = static_cast<float>(flop) / 1.E9 / avg_time;
|
|
float gb_per_sec = num_bytes / 1.E6 / avg_time;
|
|
|
|
std::cout << "Perf: " << std::setw(10) << avg_time << " ms, " << tflops << " TFlops, "
|
|
<< gb_per_sec << " GB/s, " << op_name << std::endl;
|
|
|
|
if(tflops > best_tflops)
|
|
{
|
|
best_op_id = i;
|
|
best_op_name = op_name;
|
|
best_avg_time = avg_time;
|
|
best_gb_per_sec = gb_per_sec;
|
|
best_tflops = tflops;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
std::cout << op_name << " does not support this problem" << std::endl;
|
|
}
|
|
}
|
|
|
|
std::cout << "Best Perf: " << std::setw(10) << best_avg_time << " ms, " << best_tflops
|
|
<< " TFlops, " << best_gb_per_sec << " GB/s, " << best_op_name << std::endl;
|
|
|
|
// run the best intance
|
|
{
|
|
auto& op_ptr = op_ptrs[best_op_id];
|
|
std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString()
|
|
<< std::endl;
|
|
auto argument_ptr = op_ptr->MakeArgumentPointer(in.GetDeviceBuffer(),
|
|
wei.GetDeviceBuffer(),
|
|
out.GetDeviceBuffer(),
|
|
N,
|
|
K,
|
|
C,
|
|
in_spatial_lengths,
|
|
filter_spatial_lengths,
|
|
out_spatial_lengths,
|
|
filter_strides,
|
|
filter_dilations,
|
|
input_left_pads,
|
|
input_right_pads,
|
|
PassThrough{},
|
|
PassThrough{},
|
|
PassThrough{});
|
|
|
|
auto invoker_ptr = op_ptr->MakeInvokerPointer();
|
|
|
|
if(op_ptr->IsSupportedArgument(argument_ptr.get()))
|
|
{
|
|
invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, false});
|
|
}
|
|
|
|
std::cout << "Done" << std::endl;
|
|
}
|
|
|
|
return 0;
|
|
} |