cupyx.profiler.benchmark(func, args=(), kwargs={}, n_repeat=10000, *, name=None, n_warmup=10, max_duration=inf, devices=None)[source]#

Timing utility for measuring time spent by both CPU and GPU.

This function is a very convenient helper for setting up a timing test. The GPU time is properly recorded by synchronizing internal streams. As a result, to time a multi-GPU function all participating devices must be passed as the devices argument so that this helper knows which devices to record. A simple example is given as follows:

import cupy as cp
from cupyx.profiler import benchmark

def f(a, b):
    return 3 * cp.sin(-a) * b

a = 0.5 - cp.random.random((100,))
b = cp.random.random((100,))
print(benchmark(f, (a, b), n_repeat=1000))
  • func (callable) – a callable object to be timed.

  • args (tuple) – positional arguments to be passed to the callable.

  • kwargs (dict) – keyword arguments to be passed to the callable.

  • n_repeat (int) – number of times the callable is called. Increasing this value would improve the collected statistics at the cost of longer test time.

  • name (str) – the function name to be reported. If not given, the callable’s __name__ attribute is used.

  • n_warmup (int) – number of times the callable is called. The warm-up runs are not timed.

  • max_duration (float) – the maximum time (in seconds) that the entire test can use. If the taken time is longer than this limit, the test is stopped and the statistics collected up to the breakpoint is reported.

  • devices (tuple) – a tuple of device IDs (int) that will be timed during the timing test. If not given, the current device is used.


an object collecting all test results.

Return type: