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kc3-lang/angle/scripts/perf_test_runner.py

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  • Author : Jamie Madill
    Date : 2018-10-30 15:14:52
    Hash : 3402d523
    Message : Try to reduce variance in angle_perftests. This change does a few things: - make perf test runner script print % variation instead of stddev This makes it a bit more clear how much variance there is. - stabilize CPU in the render perf tests Setting a thread affinity and priority should stop from switching cores during the run. Hopefully can prevent background noise from changing the test results. - warm up the benchmark with a few iterations This should hopefully make the test results a bit more stable. - output a new normalized perf result value The new result is normalized against the number of iterations. So it should hopefully be stable even if the number of iterations is changed. - increases the iteration count in the draw call perf tests. These tests were completely dominated by SwapBuffers time. Increasing the iterations per step means we actually are bottlenecked on CPU time instead. Bug: angleproject:2923 Change-Id: I5ee347cf93df239ac33b83dc5effe4c21e066736 Reviewed-on: https://chromium-review.googlesource.com/c/1303679 Commit-Queue: Jamie Madill <jmadill@chromium.org> Reviewed-by: Shahbaz Youssefi <syoussefi@chromium.org> Reviewed-by: Yuly Novikov <ynovikov@chromium.org>

  • scripts/perf_test_runner.py
  • #!/usr/bin/python2
    #
    # Copyright 2015 The ANGLE Project Authors. All rights reserved.
    # Use of this source code is governed by a BSD-style license that can be
    # found in the LICENSE file.
    #
    # perf_test_runner.py:
    #   Helper script for running and analyzing perftest results. Runs the
    #   tests in an infinite batch, printing out the mean and coefficient of
    #   variation of the population continuously.
    #
    
    import glob
    import subprocess
    import sys
    import os
    import re
    
    base_path = os.path.abspath(os.path.join(os.path.dirname(os.path.abspath(__file__)), '..'))
    
    # Might have to add lower case "release" in some configurations.
    perftests_paths = glob.glob('out/*Release*')
    metric = 'score'
    
    binary_name = 'angle_perftests'
    if sys.platform == 'win32':
        binary_name += '.exe'
    
    scores = []
    
    # Danke to http://stackoverflow.com/a/27758326
    def mean(data):
        """Return the sample arithmetic mean of data."""
        n = len(data)
        if n < 1:
            raise ValueError('mean requires at least one data point')
        return float(sum(data))/float(n) # in Python 2 use sum(data)/float(n)
    
    def sum_of_square_deviations(data, c):
        """Return sum of square deviations of sequence data."""
        ss = sum((float(x)-c)**2 for x in data)
        return ss
    
    def coefficient_of_variation(data):
        """Calculates the population coefficient of variation."""
        n = len(data)
        if n < 2:
            raise ValueError('variance requires at least two data points')
        c = mean(data)
        ss = sum_of_square_deviations(data, c)
        pvar = ss/n # the population variance
        stddev = (pvar**0.5) # population standard deviation
        return stddev / c
    
    def truncated_list(data, n):
        """Compute a truncated list, n is truncation size"""
        if len(data) < n * 2:
            raise ValueError('list not large enough to truncate')
        return sorted(data)[n:-n]
    
    def truncated_mean(data, n):
        """Compute a truncated mean, n is truncation size"""
        return mean(truncated_list(data, n))
    
    def truncated_cov(data, n):
        """Compute a truncated coefficient of variation, n is truncation size"""
        return coefficient_of_variation(truncated_list(data, n))
    
    # Find most recent binary
    newest_binary = None
    newest_mtime = None
    
    for path in perftests_paths:
        binary_path = os.path.join(base_path, path, binary_name)
        if os.path.exists(binary_path):
            binary_mtime = os.path.getmtime(binary_path)
            if (newest_binary is None) or (binary_mtime > newest_mtime):
                newest_binary = binary_path
                newest_mtime = binary_mtime
    
    perftests_path = newest_binary
    
    if perftests_path == None or not os.path.exists(perftests_path):
        print('Cannot find Release %s!' % binary_name)
        sys.exit(1)
    
    if sys.platform == 'win32':
        test_name = 'DrawCallPerfBenchmark.Run/d3d11_null'
    else:
        test_name = 'DrawCallPerfBenchmark.Run/gl'
    
    if len(sys.argv) >= 2:
        test_name = sys.argv[1]
    
    print('Using test executable: ' + perftests_path)
    print('Test name: ' + test_name)
    
    # Infinite loop of running the tests.
    while True:
        process = subprocess.Popen([perftests_path, '--gtest_filter=' + test_name], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
        output, err = process.communicate()
    
        start_index = output.find(metric + "=")
        if start_index == -1:
            print("Did not find the score of the specified test in output:")
            print(output)
            sys.exit(1)
    
        start_index += len(metric) + 2
    
        end_index = output[start_index:].find(" ")
        if end_index == -1:
            print("Error parsing output:")
            print(output)
            sys.exit(2)
    
        m = re.search('Running (\d+) tests', output)
        if m and int(m.group(1)) > 1:
            print("Found more than one test result in output:")
            print(output)
            sys.exit(3)
    
        end_index += start_index
    
        score = int(output[start_index:end_index])
        sys.stdout.write("score: " + str(score))
    
        scores.append(score)
        sys.stdout.write(", mean: %.2f" % mean(scores))
    
        if (len(scores) > 1):
            sys.stdout.write(", variation: %.2f%%" % (coefficient_of_variation(scores) * 100.0))
    
        if (len(scores) > 7):
            trucation_n = len(scores) >> 3
            sys.stdout.write(", truncated mean: %.2f" % truncated_mean(scores, trucation_n))
            sys.stdout.write(", variation: %.2f%%" % (truncated_cov(scores, trucation_n) * 100.0))
    
        print("")