Profiling

Profiling is a way to measure the performance of a program and to identify bottlenecks in your MatX application. Since the method for profiling depends on the executor, each executor implements its own profiling mechanism. For example, the CUDA executor can use events encapsulating the kernels it’s profiling. The profiling is done through the executor object rather than the run statement so that multiple runs can be profiled together.

Profiling is done by calling the start_timer() method of the executor:

exec.start_timer();

To stop the profiler, stop_timer() is called:

exec.stop_timer();

Depending on the executor, stop_timer() may need to block for the operation to conplete on an asynchronous executor.

Once stop_timer() returns, the execution time between the timers can be retrieved by calling get_time_ms():

auto time = exec.get_time_ms();

In the above example time contains the runtime of everything executed between the start_timer() and stop_timer() calls. For a CUDA executor this is the time between the beginning of the first kernel and the end of the last. For a CPU executor this is the CPU time between the two calls.

Note

Profiling does not work a multi-threaded host executor currently

For a full example of profiling, see the spectrogram example.