2016-05-24 19:00:51 +00:00
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#!/usr/bin/env python
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# Copyright (C) 2011, 2012 Purdue University
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# Written by Gregor Richards
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# All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# 1. Redistributions of source code must retain the above copyright notice,
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# this list of conditions and the following disclaimer.
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# 2. Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
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# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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# POSSIBILITY OF SUCH DAMAGE.
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import math
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import os
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import re
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import sys
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benchmarks = ["amazon/chrome", "amazon/firefox", "amazon/safari",
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"facebook/chrome", "facebook/firefox", "facebook/safari",
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"google/chrome", "google/firefox", "google/safari",
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"twitter/chrome", "twitter/firefox", "twitter/safari",
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"yahoo/chrome", "yahoo/firefox", "yahoo/safari"]
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modes = {
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"*": ["urem"],
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"amazon/firefox": ["urm"],
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"google/firefox": ["uem"]
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}
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runcount = 25
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keepruns = 20
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keepfrom = runcount - keepruns
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if len(sys.argv) != 2:
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2017-12-08 21:56:09 +00:00
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print("Use: python harness.py <JS executable>")
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2016-05-24 19:00:51 +00:00
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exit(1)
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js = sys.argv[1]
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# standard t-distribution for normally distributed samples
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tDistribution = [0, 0, 12.71, 4.30, 3.18, 2.78, 2.57, 2.45, 2.36, 2.31, 2.26,
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2.23, 2.20, 2.18, 2.16, 2.14, 2.13, 2.12, 2.11, 2.10, 2.09, 2.09, 2.08, 2.07,
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2.07, 2.06, 2.06, 2.06, 2.05, 2.05, 2.05, 2.04, 2.04, 2.04, 2.03, 2.03, 2.03,
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2.03, 2.03, 2.02, 2.02, 2.02, 2.02, 2.02, 2.02, 2.02, 2.01, 2.01, 2.01, 2.01,
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2.01, 2.01, 2.01, 2.01, 2.01, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00,
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2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99,
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1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99,
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1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.98, 1.98, 1.98, 1.98, 1.98,
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1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98,
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1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98,
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1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98,
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1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98,
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1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97,
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1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.96]
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def tDist(n):
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if (n >= len(tDistribution)):
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return tDistribution[-1]
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return tDistribution[n]
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results = {}
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for benchmark in benchmarks:
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results[benchmark] = {}
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bmodes = modes["*"]
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if benchmark in modes:
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bmodes = modes[benchmark]
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for mode in bmodes:
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results[benchmark][mode] = []
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for runno in range(runcount):
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# Now run it and get the results
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print(benchmark + " " + mode + " " + str(runno))
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res = os.popen(js + " " + benchmark + "/" + mode + ".js").read()
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time = float(re.match("Time: ([0-9]*)ms", res).group(1))
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if runno >= keepfrom:
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results[benchmark][mode].append(time)
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# Collect the totals
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sresults = {}
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totals = {
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"mean": 1,
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"stddev": 1,
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"sem": 1,
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"ci": 1,
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"runs": 0
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}
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for benchmark in benchmarks:
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sresults[benchmark] = {}
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bmodes = modes["*"]
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if benchmark in modes:
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bmodes = modes[benchmark]
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for mode in bmodes:
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sresults[benchmark][mode] = sresult = {}
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result = results[benchmark][mode]
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totals["runs"] = totals["runs"] + 1
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sresult["mode"] = mode
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mean = sresult["mean"] = sum(result) / len(result)
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stddev = sresult["stddev"] = math.sqrt(
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sum(
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map(lambda e: math.pow(e - mean, 2), result)
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) / (len(result) - 1)
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)
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sm = sresult["sm"] = stddev / mean
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sem = sresult["sem"] = stddev / math.sqrt(len(result))
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semm = sresult["semm"] = sem / mean
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ci = sresult["ci"] = tDist(len(result)) * sem
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cim = sresult["cim"] = ci / mean
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totals["mean"] *= mean
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totals["stddev"] *= stddev
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totals["sem"] *= sem
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totals["ci"] *= ci
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power = 1 / totals["runs"]
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totals["mean"] = math.pow(totals["mean"], power)
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totals["stddev"] = math.pow(totals["stddev"], power)
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totals["sm"] = totals["stddev"] / totals["mean"]
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totals["sem"] = math.pow(totals["sem"], power)
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totals["semm"] = totals["sem"] / totals["mean"]
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totals["ci"] = math.pow(totals["ci"], power)
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totals["cim"] = totals["ci"] / totals["mean"]
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totals["sm"] *= 100
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totals["semm"] *= 100
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totals["cim"] *= 100
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2017-12-08 21:56:09 +00:00
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print("Final results:")
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print(u" %(mean)fms \u00b1 %(cim)f%% (lower is better)" % totals)
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print(" Standard deviation = %(sm)f%% of mean" % totals)
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print(" Standard error = %(semm)f%% of mean" % totals)
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print(" %(runs)d runs" % {"runs": runcount})
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print("")
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2016-05-24 19:00:51 +00:00
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2017-12-08 21:56:09 +00:00
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print("Result breakdown:")
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2016-05-24 19:00:51 +00:00
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for benchmark in benchmarks:
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2017-12-08 21:56:09 +00:00
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print(" %(benchmark)s:" % {"benchmark": benchmark})
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2016-05-24 19:00:51 +00:00
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bmodes = modes["*"]
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if benchmark in modes:
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bmodes = modes[benchmark]
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for mode in bmodes:
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2017-12-08 21:56:09 +00:00
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print(u" %(mode)s: %(mean)fms \u00b1 %(cim)f%% (stddev=%(sm)f%%, stderr=%(semm)f%%)" % sresults[benchmark][mode])
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print("")
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2016-05-24 19:00:51 +00:00
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2017-12-08 21:56:09 +00:00
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print("Raw results:")
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2016-05-24 19:00:51 +00:00
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for benchmark in benchmarks:
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2017-12-08 21:56:09 +00:00
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print(" %(benchmark)s:" % {"benchmark": benchmark})
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2016-05-24 19:00:51 +00:00
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bmodes = modes["*"]
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if benchmark in modes:
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bmodes = modes[benchmark]
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for mode in bmodes:
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2017-12-08 21:56:09 +00:00
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print(" %(mode)s: %(results)s" % {
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2016-05-24 19:00:51 +00:00
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"mode": mode,
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"results": results[benchmark][mode]
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2017-12-08 21:56:09 +00:00
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})
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