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cuda: drop performance sample

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Regular OpenCV perf tests should be used instead
pull/11244/head
Alexander Alekhin 7 years ago
parent f93c1b942a
commit dd243067e5
5 changed files with 0 additions and 1753 deletions
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  1. 1
      samples/gpu/CMakeLists.txt
  2. 37
      samples/gpu/performance/CMakeLists.txt
  3. 227
      samples/gpu/performance/performance.cpp
  4. 188
      samples/gpu/performance/performance.h
  5. 1300
      samples/gpu/performance/tests.cpp

1
samples/gpu/CMakeLists.txt
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@ -60,4 +60,3 @@ foreach(sample_filename ${all_samples})
ocv_target_link_libraries(${tgt} opencv_cudacodec)
endif()
endforeach()
include("performance/CMakeLists.txt" OPTIONAL)

37
samples/gpu/performance/CMakeLists.txt
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@ -1,37 +0,0 @@
set(the_target "example_gpu_performance")
file(GLOB sources "performance/*.cpp")
file(GLOB headers "performance/*.h")
if(HAVE_opencv_xfeatures2d)
ocv_include_modules_recurse(opencv_xfeatures2d)
endif()
if(HAVE_opencv_bgsegm)
ocv_include_modules_recurse(opencv_bgsegm)
endif()
add_executable(${the_target} ${sources} ${headers})
ocv_target_link_libraries(${the_target} ${OPENCV_LINKER_LIBS} ${OPENCV_CUDA_SAMPLES_REQUIRED_DEPS})
if(HAVE_opencv_xfeatures2d)
ocv_target_link_libraries(${the_target} opencv_xfeatures2d)
endif()
if(HAVE_opencv_bgsegm)
ocv_target_link_libraries(${the_target} opencv_bgsegm)
endif()
set_target_properties(${the_target} PROPERTIES
OUTPUT_NAME "performance_gpu"
PROJECT_LABEL "(EXAMPLE_CUDA) performance")
if(ENABLE_SOLUTION_FOLDERS)
set_target_properties(${the_target} PROPERTIES FOLDER "samples//gpu")
endif()
if(WIN32)
install(TARGETS ${the_target} RUNTIME DESTINATION "${OPENCV_SAMPLES_BIN_INSTALL_PATH}/gpu" COMPONENT samples)
endif()
ocv_install_example_src("gpu/performance" performance/*.cpp performance/*.h)

227
samples/gpu/performance/performance.cpp
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@ -1,227 +0,0 @@
#include <iomanip>
#include <stdexcept>
#include <string>
#include "performance.h"
#include "opencv2/core/cuda.hpp"
using namespace std;
using namespace cv;
using namespace cv::cuda;
void TestSystem::run()
{
if (is_list_mode_)
{
for (vector<Runnable*>::iterator it = tests_.begin(); it != tests_.end(); ++it)
cout << (*it)->name() << endl;
return;
}
// Run test initializers
for (vector<Runnable*>::iterator it = inits_.begin(); it != inits_.end(); ++it)
{
if ((*it)->name().find(test_filter_, 0) != string::npos)
(*it)->run();
}
printHeading();
// Run tests
for (vector<Runnable*>::iterator it = tests_.begin(); it != tests_.end(); ++it)
{
try
{
if ((*it)->name().find(test_filter_, 0) != string::npos)
{
cout << endl << (*it)->name() << ":\n";
(*it)->run();
finishCurrentSubtest();
}
}
catch (const Exception&)
{
// Message is printed via callback
resetCurrentSubtest();
}
catch (const runtime_error& e)
{
printError(e.what());
resetCurrentSubtest();
}
}
printSummary();
}
void TestSystem::finishCurrentSubtest()
{
if (cur_subtest_is_empty_)
// There is no need to print subtest statistics
return;
double cpu_time = cpu_elapsed_ / getTickFrequency() * 1000.0;
double gpu_time = gpu_elapsed_ / getTickFrequency() * 1000.0;
double speedup = static_cast<double>(cpu_elapsed_) / std::max(1.0, gpu_elapsed_);
speedup_total_ += speedup;
printMetrics(cpu_time, gpu_time, speedup);
num_subtests_called_++;
resetCurrentSubtest();
}
double TestSystem::meanTime(const vector<int64> &samples)
{
double sum = accumulate(samples.begin(), samples.end(), 0.);
if (samples.size() > 1)
return (sum - samples[0]) / (samples.size() - 1);
return sum;
}
void TestSystem::printHeading()
{
cout << endl;
cout << setiosflags(ios_base::left);
cout << TAB << setw(10) << "CPU, ms" << setw(10) << "GPU, ms"
<< setw(14) << "SPEEDUP"
<< "DESCRIPTION\n";
cout << resetiosflags(ios_base::left);
}
void TestSystem::printSummary()
{
cout << setiosflags(ios_base::fixed);
cout << "\naverage GPU speedup: x"
<< setprecision(3) << speedup_total_ / std::max(1, num_subtests_called_)
<< endl;
cout << resetiosflags(ios_base::fixed);
}
void TestSystem::printMetrics(double cpu_time, double gpu_time, double speedup)
{
cout << TAB << setiosflags(ios_base::left);
stringstream stream;
stream << cpu_time;
cout << setw(10) << stream.str();
stream.str("");
stream << gpu_time;
cout << setw(10) << stream.str();
stream.str("");
stream << "x" << setprecision(3) << speedup;
cout << setw(14) << stream.str();
cout << cur_subtest_description_.str();
cout << resetiosflags(ios_base::left) << endl;
}
void TestSystem::printError(const std::string& msg)
{
cout << TAB << "[error: " << msg << "] " << cur_subtest_description_.str() << endl;
}
void gen(Mat& mat, int rows, int cols, int type, Scalar low, Scalar high)
{
mat.create(rows, cols, type);
RNG rng(0);
rng.fill(mat, RNG::UNIFORM, low, high);
}
string abspath(const string& relpath)
{
return TestSystem::instance().workingDir() + relpath;
}
static int cvErrorCallback(int /*status*/, const char* /*func_name*/,
const char* err_msg, const char* /*file_name*/,
int /*line*/, void* /*userdata*/)
{
TestSystem::instance().printError(err_msg);
return 0;
}
int main(int argc, const char* argv[])
{
int num_devices = getCudaEnabledDeviceCount();
if (num_devices == 0)
{
cerr << "No GPU found or the library was compiled without CUDA support";
return -1;
}
redirectError(cvErrorCallback);
const char* keys =
"{ h help | | print help message }"
"{ f filter | | filter for test }"
"{ w workdir | | set working directory }"
"{ l list | | show all tests }"
"{ d device | 0 | device id }"
"{ i iters | 10 | iteration count }";
CommandLineParser cmd(argc, argv, keys);
if (cmd.has("help") || !cmd.check())
{
cmd.printMessage();
cmd.printErrors();
return 0;
}
int device = cmd.get<int>("device");
if (device < 0 || device >= num_devices)
{
cerr << "Invalid device ID" << endl;
return -1;
}
DeviceInfo dev_info(device);
if (!dev_info.isCompatible())
{
cerr << "CUDA module isn't built for GPU #" << device << " " << dev_info.name() << ", CC " << dev_info.majorVersion() << '.' << dev_info.minorVersion() << endl;
return -1;
}
setDevice(device);
printShortCudaDeviceInfo(device);
string filter = cmd.get<string>("filter");
string workdir = cmd.get<string>("workdir");
bool list = cmd.has("list");
int iters = cmd.get<int>("iters");
if (!filter.empty())
TestSystem::instance().setTestFilter(filter);
if (!workdir.empty())
{
if (workdir[workdir.size() - 1] != '/' && workdir[workdir.size() - 1] != '\\')
workdir += '/';
TestSystem::instance().setWorkingDir(workdir);
}
if (list)
TestSystem::instance().setListMode(true);
TestSystem::instance().setNumIters(iters);
cout << "\nNote: the timings for GPU don't include data transfer" << endl;
TestSystem::instance().run();
return 0;
}

188
samples/gpu/performance/performance.h
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@ -1,188 +0,0 @@
#ifndef OPENCV_CUDA_SAMPLE_PERFORMANCE_H_
#define OPENCV_CUDA_SAMPLE_PERFORMANCE_H_
#include <iostream>
#include <cstdio>
#include <vector>
#include <numeric>
#include <string>
#include <opencv2/core/utility.hpp>
#define TAB " "
class Runnable
{
public:
explicit Runnable(const std::string& nameStr): name_(nameStr) {}
virtual ~Runnable() {}
const std::string& name() const { return name_; }
virtual void run() = 0;
private:
std::string name_;
};
class TestSystem
{
public:
static TestSystem& instance()
{
static TestSystem me;
return me;
}
void setWorkingDir(const std::string& val) { working_dir_ = val; }
const std::string& workingDir() const { return working_dir_; }
void setTestFilter(const std::string& val) { test_filter_ = val; }
const std::string& testFilter() const { return test_filter_; }
void setNumIters(int num_iters) { num_iters_ = num_iters; }
void addInit(Runnable* init) { inits_.push_back(init); }
void addTest(Runnable* test) { tests_.push_back(test); }
void run();
// It's public because OpenCV callback uses it
void printError(const std::string& msg);
std::stringstream& startNewSubtest()
{
finishCurrentSubtest();
return cur_subtest_description_;
}
bool stop() const { return cur_iter_idx_ >= num_iters_; }
void cpuOn() { cpu_started_ = cv::getTickCount(); }
void cpuOff()
{
int64 delta = cv::getTickCount() - cpu_started_;
cpu_times_.push_back(delta);
++cur_iter_idx_;
}
void cpuComplete()
{
cpu_elapsed_ += meanTime(cpu_times_);
cur_subtest_is_empty_ = false;
cur_iter_idx_ = 0;
}
void gpuOn() { gpu_started_ = cv::getTickCount(); }
void gpuOff()
{
int64 delta = cv::getTickCount() - gpu_started_;
gpu_times_.push_back(delta);
++cur_iter_idx_;
}
void gpuComplete()
{
gpu_elapsed_ += meanTime(gpu_times_);
cur_subtest_is_empty_ = false;
cur_iter_idx_ = 0;
}
bool isListMode() const { return is_list_mode_; }
void setListMode(bool value) { is_list_mode_ = value; }
private:
TestSystem():
cur_subtest_is_empty_(true), cpu_elapsed_(0),
gpu_elapsed_(0), speedup_total_(0.0),
num_subtests_called_(0), is_list_mode_(false),
num_iters_(10), cur_iter_idx_(0)
{
cpu_times_.reserve(num_iters_);
gpu_times_.reserve(num_iters_);
}
void finishCurrentSubtest();
void resetCurrentSubtest()
{
cpu_elapsed_ = 0;
gpu_elapsed_ = 0;
cur_subtest_description_.str("");
cur_subtest_is_empty_ = true;
cur_iter_idx_ = 0;
cpu_times_.clear();
gpu_times_.clear();
}
double meanTime(const std::vector<int64> &samples);
void printHeading();
void printSummary();
void printMetrics(double cpu_time, double gpu_time, double speedup);
std::string working_dir_;
std::string test_filter_;
std::vector<Runnable*> inits_;
std::vector<Runnable*> tests_;
std::stringstream cur_subtest_description_;
bool cur_subtest_is_empty_;
int64 cpu_started_;
int64 gpu_started_;
double cpu_elapsed_;
double gpu_elapsed_;
double speedup_total_;
int num_subtests_called_;
bool is_list_mode_;
int num_iters_;
int cur_iter_idx_;
std::vector<int64> cpu_times_;
std::vector<int64> gpu_times_;
};
#define GLOBAL_INIT(name) \
struct name##_init: Runnable { \
name##_init(): Runnable(#name) { \
TestSystem::instance().addInit(this); \
} \
void run(); \
} name##_init_instance; \
void name##_init::run()
#define TEST(name) \
struct name##_test: Runnable { \
name##_test(): Runnable(#name) { \
TestSystem::instance().addTest(this); \
} \
void run(); \
} name##_test_instance; \
void name##_test::run()
#define SUBTEST TestSystem::instance().startNewSubtest()
#define CPU_ON \
while (!TestSystem::instance().stop()) { \
TestSystem::instance().cpuOn()
#define CPU_OFF \
TestSystem::instance().cpuOff(); \
} TestSystem::instance().cpuComplete()
#define CUDA_ON \
while (!TestSystem::instance().stop()) { \
TestSystem::instance().gpuOn()
#define CUDA_OFF \
TestSystem::instance().gpuOff(); \
} TestSystem::instance().gpuComplete()
// Generates a matrix
void gen(cv::Mat& mat, int rows, int cols, int type, cv::Scalar low,
cv::Scalar high);
// Returns abs path taking into account test system working dir
std::string abspath(const std::string& relpath);
#endif // OPENCV_CUDA_SAMPLE_PERFORMANCE_H_

1300
samples/gpu/performance/tests.cpp
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