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GNU C Library master sources branch siddhesh/benchmarks created. glibc-2.21-321-g7ea649c
- From: siddhesh at sourceware dot org
- To: glibc-cvs at sourceware dot org
- Date: 7 May 2015 06:23:31 -0000
- Subject: GNU C Library master sources branch siddhesh/benchmarks created. glibc-2.21-321-g7ea649c
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http://sourceware.org/git/gitweb.cgi?p=glibc.git;a=commitdiff;h=7ea649ca8e5fef748b6c2c48d298d82cd57b7a8c
commit 7ea649ca8e5fef748b6c2c48d298d82cd57b7a8c
Author: Siddhesh Poyarekar <siddhesh@redhat.com>
Date: Thu May 7 11:31:28 2015 +0530
Fix up timing_type key and remove the machine key
diff --git a/benchtests/scripts/compare_bench.py b/benchtests/scripts/compare_bench.py
index 45840ff..1aa2ee1 100755
--- a/benchtests/scripts/compare_bench.py
+++ b/benchtests/scripts/compare_bench.py
@@ -54,21 +54,10 @@ def do_compare(func, var, tl1, tl2, par, threshold):
def compare_runs(pts1, pts2, threshold):
"""Compare two benchmark runs
- For now, assume that machine1 and machine2 are the same. In future, we may
- have to add an additional condition to ensure that we are comparing apples
- to apples.
-
Args:
- machine1: Machine info from the first machine
- machine2: machine info from the second machine
pts1: Timing data from first machine
pts2: Timing data from second machine
"""
- # Just print the machines for now. We would want to do something more
- # interesting with this in future.
- print 'Machine 1:', pts1['machine']
- print 'Machine 2:', pts2['machine']
- print
# XXX We assume that the two benchmarks have identical functions and
# variants. We cannot compare two benchmarks that may have different
@@ -179,7 +168,7 @@ def main(args):
else:
threshold = 10.0
- if (bench1['timing-type'] != bench2['timing-type']):
+ if (bench1['timing_type'] != bench2['timing_type']):
print('Cannot compare benchmark outputs: timing types are different')
return
http://sourceware.org/git/gitweb.cgi?p=glibc.git;a=commitdiff;h=b9df7564cbcc2712f93efaf29eba3417649d5c85
commit b9df7564cbcc2712f93efaf29eba3417649d5c85
Author: Siddhesh Poyarekar <siddhesh@redhat.com>
Date: Wed Sep 24 14:25:34 2014 +0530
benchtest: script to compare two benchmarks
This script is a sample implementation that uses import_bench to
construct two benchmark objects and compare them. If detailed timing
information is available (when one does `make DETAILED=1 bench`), it
writes out graphs for all functions it benchmarks and prints
significant differences in timings of the two benchmark runs. If
detailed timing information is not available, it points out
significant differences in aggregate times.
Call this script as follows:
compare_bench.py schema_file.json bench1.out bench2.out
Alternatively, if one wants to set a different threshold for warnings
(default is a 10% difference):
compare_bench.py schema_file.json bench1.out bench2.out 25
The threshold in the example above is 25%. schema_file.json is the
JSON schema (which is $srcdir/benchtests/scripts/benchout.schema.json
for the benchmark output file) and bench1.out and bench2.out are the
two benchmark output files to compare.
* benchtests/scripts/compare_bench.py: New file.
* benchtests/scripts/import_bench.py (mean): New function.
(split_list): Likewise.
(do_for_all_timings): Likewise.
(compress_timings): Likewise.
diff --git a/benchtests/scripts/compare_bench.py b/benchtests/scripts/compare_bench.py
new file mode 100755
index 0000000..45840ff
--- /dev/null
+++ b/benchtests/scripts/compare_bench.py
@@ -0,0 +1,195 @@
+#!/usr/bin/python
+# Copyright (C) 2014 Free Software Foundation, Inc.
+# This file is part of the GNU C Library.
+#
+# The GNU C Library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# The GNU C Library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with the GNU C Library; if not, see
+# <http://www.gnu.org/licenses/>.
+"""Compare two benchmark results
+
+Given two benchmark result files and a threshold, this script compares the
+benchmark results and flags differences in performance beyond a given
+threshold.
+"""
+import sys
+import os
+import pylab
+import import_bench as bench
+
+def do_compare(func, var, tl1, tl2, par, threshold):
+ """Compare one of the aggregate measurements
+
+ Helper function to compare one of the aggregate measurements of a function
+ variant.
+
+ Args:
+ func: Function name
+ var: Function variant name
+ tl1: The first timings list
+ tl2: The second timings list
+ par: The aggregate to measure
+ threshold: The threshold for differences, beyond which the script should
+ print a warning.
+ """
+ d = abs(tl2[par] - tl1[par]) * 100 / tl1[str(par)]
+ if d > threshold:
+ if tl1[par] > tl2[par]:
+ ind = '+++'
+ else:
+ ind = '---'
+ print('%s %s(%s)[%s]: (%.2lf%%) from %g to %g' %
+ (ind, func, var, par, d, tl1[par], tl2[par]))
+
+
+def compare_runs(pts1, pts2, threshold):
+ """Compare two benchmark runs
+
+ For now, assume that machine1 and machine2 are the same. In future, we may
+ have to add an additional condition to ensure that we are comparing apples
+ to apples.
+
+ Args:
+ machine1: Machine info from the first machine
+ machine2: machine info from the second machine
+ pts1: Timing data from first machine
+ pts2: Timing data from second machine
+ """
+ # Just print the machines for now. We would want to do something more
+ # interesting with this in future.
+ print 'Machine 1:', pts1['machine']
+ print 'Machine 2:', pts2['machine']
+ print
+
+ # XXX We assume that the two benchmarks have identical functions and
+ # variants. We cannot compare two benchmarks that may have different
+ # functions or variants. Maybe that is something for the future.
+ for func in pts1['functions'].keys():
+ for var in pts1['functions'][func].keys():
+ tl1 = pts1['functions'][func][var]
+ tl2 = pts2['functions'][func][var]
+
+ # Compare the consolidated numbers
+ # do_compare(func, var, tl1, tl2, 'max', threshold)
+ do_compare(func, var, tl1, tl2, 'min', threshold)
+ do_compare(func, var, tl1, tl2, 'mean', threshold)
+
+ # Skip over to the next variant or function if there is no detailed
+ # timing info for the function variant.
+ if 'timings' not in pts1['functions'][func][var].keys() or \
+ 'timings' not in pts2['functions'][func][var].keys():
+ return
+
+ # If two lists do not have the same length then it is likely that
+ # the performance characteristics of the function have changed.
+ # XXX: It is also likely that there was some measurement that
+ # strayed outside the usual range. Such ouiers should not
+ # happen on an idle machine with identical hardware and
+ # configuration, but ideal environments are hard to come by.
+ if len(tl1['timings']) != len(tl2['timings']):
+ print('* %s(%s): Timing characteristics changed' %
+ (func, var))
+ print('\tBefore: [%s]' %
+ ', '.join([str(x) for x in tl1['timings']]))
+ print('\tAfter: [%s]' %
+ ', '.join([str(x) for x in tl2['timings']]))
+ continue
+
+ # Collect numbers whose differences cross the threshold we have
+ # set.
+ issues = [(x, y) for x, y in zip(tl1['timings'], tl2['timings']) \
+ if abs(y - x) * 100 / x > threshold]
+
+ # Now print them.
+ for t1, t2 in issues:
+ d = abs(t2 - t1) * 100 / t1
+ if t2 > t1:
+ ind = '-'
+ else:
+ ind = '+'
+
+ print("%s %s(%s): (%.2lf%%) from %g to %g" %
+ (ind, func, var, d, t1, t2))
+
+
+def plot_graphs(bench1, bench2):
+ """Plot graphs for functions
+
+ Make scatter plots for the functions and their variants.
+
+ Args:
+ bench1: Set of points from the first machine
+ bench2: Set of points from the second machine.
+ """
+ for func in bench1['functions'].keys():
+ for var in bench1['functions'][func].keys():
+ # No point trying to print a graph if there are no detailed
+ # timings.
+ if u'timings' not in bench1['functions'][func][var].keys():
+ print('Skipping graph for %s(%s)' % (func, var))
+ continue
+
+ pylab.clf()
+ pylab.ylabel('Time (cycles)')
+
+ # First set of points
+ length = len(bench1['functions'][func][var]['timings'])
+ X = [float(x) for x in range(length)]
+ lines = pylab.scatter(X, bench1['functions'][func][var]['timings'],
+ 1.5 + 100 / length)
+ pylab.setp(lines, 'color', 'r')
+
+ # Second set of points
+ length = len(bench2['functions'][func][var]['timings'])
+ X = [float(x) for x in range(length)]
+ lines = pylab.scatter(X, bench2['functions'][func][var]['timings'],
+ 1.5 + 100 / length)
+ pylab.setp(lines, 'color', 'g')
+
+ if var:
+ filename = "%s-%s.png" % (func, var)
+ else:
+ filename = "%s.png" % func
+ print('Writing out %s' % filename)
+ pylab.savefig(filename)
+
+
+def main(args):
+ """Program Entry Point
+
+ Take two benchmark output files and compare their timings.
+ """
+ if len(args) > 4 or len(args) < 3:
+ print('Usage: %s <schema> <file1> <file2> [threshold in %%]' % sys.argv[0])
+ sys.exit(os.EX_USAGE)
+
+ bench1 = bench.parse_bench(args[1], args[0])
+ bench2 = bench.parse_bench(args[2], args[0])
+ if len(args) == 4:
+ threshold = float(args[3])
+ else:
+ threshold = 10.0
+
+ if (bench1['timing-type'] != bench2['timing-type']):
+ print('Cannot compare benchmark outputs: timing types are different')
+ return
+
+ plot_graphs(bench1, bench2)
+
+ bench.compress_timings(bench1)
+ bench.compress_timings(bench2)
+
+ compare_runs(bench1, bench2, threshold)
+
+
+if __name__ == '__main__':
+ main(sys.argv[1:])
diff --git a/benchtests/scripts/import_bench.py b/benchtests/scripts/import_bench.py
index c147df7..d0d9f4b 100644
--- a/benchtests/scripts/import_bench.py
+++ b/benchtests/scripts/import_bench.py
@@ -25,6 +25,102 @@ except ImportError:
raise
+def mean(lst):
+ """Compute and return mean of numbers in a list
+
+ The numpy average function has horrible performance, so implement our
+ own mean function.
+
+ Args:
+ lst: The list of numbers to average.
+ Return:
+ The mean of members in the list.
+ """
+ return sum(lst) / len(lst)
+
+
+def split_list(bench, func, var):
+ """ Split the list into a smaller set of more distinct points
+
+ Group together points such that the difference between the smallest
+ point and the mean is less than 1/3rd of the mean. This means that
+ the mean is at most 1.5x the smallest member of that group.
+
+ mean - xmin < mean / 3
+ i.e. 2 * mean / 3 < xmin
+ i.e. mean < 3 * xmin / 2
+
+ For an evenly distributed group, the largest member will be less than
+ twice the smallest member of the group.
+ Derivation:
+
+ An evenly distributed series would be xmin, xmin + d, xmin + 2d...
+
+ mean = (2 * n * xmin + n * (n - 1) * d) / 2 * n
+ and max element is xmin + (n - 1) * d
+
+ Now, mean < 3 * xmin / 2
+
+ 3 * xmin > 2 * mean
+ 3 * xmin > (2 * n * xmin + n * (n - 1) * d) / n
+ 3 * n * xmin > 2 * n * xmin + n * (n - 1) * d
+ n * xmin > n * (n - 1) * d
+ xmin > (n - 1) * d
+ 2 * xmin > xmin + (n-1) * d
+ 2 * xmin > xmax
+
+ Hence, proved.
+
+ Similarly, it is trivial to prove that for a similar aggregation by using
+ the maximum element, the maximum element in the group must be at most 4/3
+ times the mean.
+
+ Args:
+ bench: The benchmark object
+ func: The function name
+ var: The function variant name
+ """
+ means = []
+ lst = bench['functions'][func][var]['timings']
+ last = len(lst) - 1
+ while lst:
+ for i in range(last + 1):
+ avg = mean(lst[i:])
+ if avg > 0.75 * lst[last]:
+ means.insert(0, avg)
+ lst = lst[:i]
+ last = i - 1
+ break
+ bench['functions'][func][var]['timings'] = means
+
+
+def do_for_all_timings(bench, callback):
+ """Call a function for all timing objects for each function and its
+ variants.
+
+ Args:
+ bench: The benchmark object
+ callback: The callback function
+ """
+ for func in bench['functions'].keys():
+ for k in bench['functions'][func].keys():
+ if 'timings' not in bench['functions'][func][k].keys():
+ continue
+
+ callback(bench, func, k)
+
+
+def compress_timings(points):
+ """Club points with close enough values into a single mean value
+
+ See split_list for details on how the clubbing is done.
+
+ Args:
+ points: The set of points.
+ """
+ do_for_all_timings(points, split_list)
+
+
def parse_bench(filename, schema_filename):
"""Parse the input file
http://sourceware.org/git/gitweb.cgi?p=glibc.git;a=commitdiff;h=e060c353b8a01d04549d7333ee6e4af9154f7d43
commit e060c353b8a01d04549d7333ee6e4af9154f7d43
Author: Siddhesh Poyarekar <siddhesh@redhat.com>
Date: Mon Feb 24 23:11:28 2014 +0530
New module to import and process benchmark output
This is the beginning of a module to import and process benchmark
outputs. Currently this is tied to the bench.out format, but in
future this needs to be generalized.
The module currently supports importing of a bench.out and validating
it against a schema file. I have also added a function that
compresses detailed timings by grouping them into their means based on
how close they are to each other.
The idea here is to have a set of routines that benchmark consumers
may find useful to build their own analysis tools. I have altered
validate_bench to use this module too.
* benchtests/scripts/import_bench.py: New file.
* benchtests/scripts/validate_benchout.py: Import import_bench
instead of jsonschema.
(validate_bench): Remove function.
(main): Use import_bench.
diff --git a/benchtests/scripts/import_bench.py b/benchtests/scripts/import_bench.py
new file mode 100644
index 0000000..c147df7
--- /dev/null
+++ b/benchtests/scripts/import_bench.py
@@ -0,0 +1,45 @@
+#!/usr/bin/python
+# Copyright (C) 2014 Free Software Foundation, Inc.
+# This file is part of the GNU C Library.
+#
+# The GNU C Library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# The GNU C Library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with the GNU C Library; if not, see
+# <http://www.gnu.org/licenses/>.
+"""Functions to import benchmark data and process it"""
+
+import json
+try:
+ import jsonschema as validator
+except ImportError:
+ print('Could not find jsonschema module.')
+ raise
+
+
+def parse_bench(filename, schema_filename):
+ """Parse the input file
+
+ Parse and validate the json file containing the benchmark outputs. Return
+ the resulting object.
+ Args:
+ filename: Name of the benchmark output file.
+ Return:
+ The bench dictionary.
+ """
+ with open(schema_filename, 'r') as schemafile:
+ schema = json.load(schemafile)
+ with open(filename, 'r') as benchfile:
+ bench = json.load(benchfile)
+ validator.validate(bench, schema)
+ do_for_all_timings(bench, lambda b, f, v:
+ b['functions'][f][v]['timings'].sort())
+ return bench
diff --git a/benchtests/scripts/validate_benchout.py b/benchtests/scripts/validate_benchout.py
index d1cd719..28fd023 100755
--- a/benchtests/scripts/validate_benchout.py
+++ b/benchtests/scripts/validate_benchout.py
@@ -27,37 +27,26 @@ import sys
import os
try:
- import jsonschema
+ import import_bench as bench
except ImportError:
- print('Could not find jsonschema module. Output not validated.')
+ print('Import Error: Output will not be validated.')
# Return success because we don't want the bench target to fail just
# because the jsonschema module was not found.
sys.exit(os.EX_OK)
-def validate_bench(benchfile, schemafile):
- """Validate benchmark file
-
- Validate a benchmark output file against a JSON schema.
+def print_and_exit(message, exitcode):
+ """Prints message to stderr and returns the exit code.
Args:
- benchfile: The file name of the bench.out file.
- schemafile: The file name of the JSON schema file to validate
- bench.out against.
+ message: The message to print
+ exitcode: The exit code to return
- Exceptions:
- jsonschema.ValidationError: When bench.out is not valid
- jsonschema.SchemaError: When the JSON schema is not valid
- IOError: If any of the files are not found.
+ Returns:
+ The passed exit code
"""
- with open(benchfile, 'r') as bfile:
- with open(schemafile, 'r') as sfile:
- bench = json.load(bfile)
- schema = json.load(sfile)
- jsonschema.validate(bench, schema)
-
- # If we reach here, we're all good.
- print("Benchmark output in %s is valid." % benchfile)
+ print(message, file=sys.stderr)
+ return exitcode
def main(args):
@@ -73,11 +62,23 @@ def main(args):
Exceptions thrown by validate_bench
"""
if len(args) != 2:
- print("Usage: %s <bench.out file> <bench.out schema>" % sys.argv[0],
- file=sys.stderr)
- return os.EX_USAGE
+ return print_and_exit("Usage: %s <bench.out file> <bench.out schema>"
+ % sys.argv[0], os.EX_USAGE)
+
+ try:
+ bench.parse_bench(args[0], args[1])
+ except IOError as e:
+ return print_and_exit("IOError(%d): %s" % (e.errno, e.strerror),
+ os.EX_OSFILE)
+
+ except bench.validator.ValidationError as e:
+ return print_and_exit("Invalid benchmark output: %s" % e.message,
+ os.EX_DATAERR)
+
+ except bench.validator.SchemaError as e:
+ return print_and_exit("Invalid schema: %s" % e.message, os.EX_DATAERR)
- validate_bench(args[0], args[1])
+ print("Benchmark output in %s is valid." % args[0])
return os.EX_OK
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