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PROJECT(cppuprofile)

CMAKE_MINIMUM_REQUIRED(VERSION 2.8.12)

OPTION(PROFILE_ENABLED "Whether library performs profiling operations or does nothing" ON)

OPTION(SAMPLE_ENABLED "Whether sample binary is built or not" OFF)

OPTION(BUILD_SHARED_LIBS "Build shared libraries" OFF)

OPTION(GPU_MONITOR_NVIDIA "Whether NVidiaMonitor class for monitoring NVidia GPUs is compiled and embedded to the library" OFF)

ADD_SUBDIRECTORY(lib)

IF(SAMPLE_ENABLED)

  ADD_SUBDIRECTORY(sample)

ENDIF()

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# cppuprofile

![GitHub tag](https://img.shields.io/github/v/tag/orange-opensource/cppuprofile)

![Licensing](https://img.shields.io/github/license/Orange-OpenSource/cppuprofile)

[![Documentation](https://img.shields.io/badge/documentation-ok-green)](https://orange-opensource.github.io/cppuprofile/)

![Linux](https://img.shields.io/badge/Linux-full_support-green?logo=linux&logoColor=white)

![Windows](https://img.shields.io/badge/Windows-partial_support-orange?&logo=windows&logoColor=white)

![MacOS](https://img.shields.io/badge/MacOS-not_tested-orange?&logo=apple&logoColor=white)

This project provides a tiny C++ profiling library for monitoring:

* execution time

* CPU usage

* memory usage

* GPU usage and memory

This library aims at collecting metrics on embedded devices to monitor device

performance while operating heavy tasks or booting for example. Those metrics can

be useful to check that load is properly spread onto all CPU cores or

that memory is not starved.

This library can also run on non-embedded devices like servers or desktop PCs. It is

compatible with Linux and Windows.

Metrics are stored in a CSV file (the path is configurable).

## Usage

The library is lightweight, simple and easy to use. It can be easily used from an existing application or integrated in a dedicated monitoring application.

Full API documentation is available [here](https://orange-opensource.github.io/cppuprofile/).

### System memory and CPU usage monitoring

```cpp

#include <uprofile/uprofile.h>

...

uprofile::start("uprofile.log");

uprofile::startSystemMemoryMonitoring(200);

uprofile::startCPUUsageMonitoring(200);

...

uprofile::stop();

```

### Record time execution

```cpp

uprofile::timeBegin("my_custom_function");

...

uprofile::timeEnd("my_custom_function");

```

### GPU monitoring

The library also supports GPU metrics monitoring like usage and memory. Since GPU monitoring is specific to each vendor, an interface `IGPUMonitor` is available to abstract each vendor monitor system.

To monitor a specific GPU, you must subclass `IGPUMonitor`:

```cpp

#include <uprofile/igpumonitor.h>

class MyGPUMonitor: public uprofile::IGPUMonitor {

public:

    float getUsage() override;

    void getMemory(int& usedMem, int& totalMem) override;

}

```

And then inject it at runtime to the `uprofile` monitoring system:

```cpp

uprofile::addGPUMonitor(new MyGPUMonitor);

uprofile::start("uprofile.log");

uprofile::startGPUMemoryMonitoring(200);

uprofile::startGPUUsageMonitoring(200);

```

#### Supported GPU monitoring

Here is the list of GPUs supported by `cppuprofile`

* NVidia Graphics Cards (through `nvidia-smi`). Pass `-DGPU_MONITOR_NVIDIA=ON` as compile option and inject `uprofile::NvidiaMonitor` from `monitors/nvidiamonitor.h` as `GPUMonitor`. The `nvidia-smi` tool should be installed into `/usr/bin` directory.

## Build

The build process is based on CMake. Minimum version is 2.8.

```commandline

$ cmake --configure . -B ../build-cppuprofile

$ cmake --build ../build-cppuprofile

```

### Shared/dynamic library

By default, it generates a shared library on Linux and a dynamic library (DLL) on Windows. To link with this library on Windows, you must

pass `-DUPROFILE_DLL` definition to CMake.

### Static library

If you want to generate a static library, you must use `-DBUILD_SHARED_LIBS=OFF` CMake option.

### Disable profiling in Release mode

If you want to disable profiling in Release mode or if you want to only enable profiling in particular cases, you can use the `PROFILE_ENABLED` option (set to `ON` by default).

To disable the profiling:

```commandline

$ cmake --configure . -B ../build-cppuprofile -DPROFILE_ENABLED=OFF

```

## Tools

The project also brings a tool for displaying the different metrics in

a single view:

![ScreenshotShowGraph](doc/show-graph-screenshot.png)

This tool is written in Python3. It requires a set of dependency packages. To install them:

```commandline

$ pip3 install -r requirements.txt

```

Then

```commandline

$ ./tools/show-graph uprofile.log

```

Note that you can filter the metrics to display with `--metric` argument.

## Sample

The project provides a C++ sample application called `uprof-sample`

that shows how to use the `cppuprofile` library. You can build it with `SAMPLE_ENABLED` option:

```commandline

$ cmake --configure . -B ../build-cppuprofile -DSAMPLE_ENABLED=ON

$ cmake --build ../build-cppuprofile

$ ../build-cppuprofile/sample/uprof-sample

```

## Windows support limitations

The library compiles on Windows but only time execution is supported so far. Monitoring metrics like CPU Usage and system, process and nvidia GPU memory are not supported.

Contributions are welcomed.

## License

This project is licensed under BSD-3-Clause license. See LICENSE file for any further information.