From 4877829bff4a8655ff3882986e6c7a20e5c3a9b6 Mon Sep 17 00:00:00 2001 From: Martin Liska Date: Thu, 28 Apr 2016 14:02:37 +0200 Subject: [PATCH] Replace AWK script with the python script. * analyze_brprob: Remove. * analyze_brprob.py: New file. From-SVN: r235560 --- contrib/ChangeLog | 5 ++ contrib/analyze_brprob | 147 -------------------------------------- contrib/analyze_brprob.py | 136 +++++++++++++++++++++++++++++++++++ 3 files changed, 141 insertions(+), 147 deletions(-) delete mode 100755 contrib/analyze_brprob create mode 100644 contrib/analyze_brprob.py diff --git a/contrib/ChangeLog b/contrib/ChangeLog index 44e62e86940..7e5ac53039f 100644 --- a/contrib/ChangeLog +++ b/contrib/ChangeLog @@ -1,3 +1,8 @@ +2016-04-28 Martin Liska + + * analyze_brprob: Remove. + * analyze_brprob.py: New file. + 2016-04-27 Jakub Jelinek * gennews (files): Add files for GCC 6. diff --git a/contrib/analyze_brprob b/contrib/analyze_brprob deleted file mode 100755 index 57028346200..00000000000 --- a/contrib/analyze_brprob +++ /dev/null @@ -1,147 +0,0 @@ -#!/usr/bin/awk -f -# Script to analyze experimental results of our branch prediction heuristics -# Contributed by Jan Hubicka, SuSE Inc. -# Copyright (C) 2001, 2003 Free Software Foundation, Inc. -# -# This file is part of GCC. -# -# GCC is free software; you can redistribute it and/or modify -# it under the terms of the GNU General Public License as published by -# the Free Software Foundation; either version 3, or (at your option) -# any later version. -# -# GCC 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 General Public License for more details. -# -# You should have received a copy of the GNU General Public License -# along with GCC; see the file COPYING. If not, write to -# the Free Software Foundation, 51 Franklin Street, Fifth Floor, -# Boston, MA 02110-1301, USA. -# -# -# This script is used to calculate two basic properties of the branch prediction -# heuristics - coverage and hitrate. Coverage is number of executions of a given -# branch matched by the heuristics and hitrate is probability that once branch is -# predicted as taken it is really taken. -# -# These values are useful to determine the quality of given heuristics. Hitrate -# may be directly used in predict.c. -# -# Usage: -# Step 1: Compile and profile your program. You need to use -fprofile-arcs -# flag to get the profiles -# Step 2: Generate log files. The information about given heuristics are -# saved into ipa-profile dumps. You need to pass the -fdimp-ipa-profile switch -# to the compiler as well -# as -fbranch-probabilities to get the results of profiling noted in the dumps. -# Ensure that there are no "Arc profiling: some edge counts were bad." warnings. -# Step 3: Run this script to concatenate all *.profile files: -# analyze_brprob `find . -name *.profile` -# the information is collected and print once all files are parsed. This -# may take a while. -# Note that the script does use bc to perform long arithmetic. -# Step 4: Read the results. Basically the following table is printed: -# (this is just an example from a very early stage of branch prediction pass -# development, so please don't take these numbers seriously) -# -#HEURISTICS BRANCHES (REL) HITRATE COVERAGE (REL) -#opcode 2889 83.7% 94.96%/ 97.62% 7516383 75.3% -#pointer 246 7.1% 99.69%/ 99.86% 118791 1.2% -#loop header 449 13.0% 98.32%/ 99.07% 43553 0.4% -#first match 3450 100.0% 89.92%/ 97.27% 9979782 100.0% -#loop exit 924 26.8% 88.95%/ 95.58% 9026266 90.4% -#error return 150 4.3% 64.48%/ 86.81% 453542 4.5% -#call 803 23.3% 51.66%/ 98.61% 3614037 36.2% -#loop branch 51 1.5% 99.26%/ 99.27% 26854 0.3% -#noreturn call 951 27.6% 100.00%/100.00% 1759809 17.6% -# -# The heuristic called "first match" is a heuristic used by GCC branch -# prediction pass and it predicts 89.92% branches correctly. -# -# The quality of heuristics can be rated using both, coverage and hitrate -# parameters. For example "loop branch" heuristics (predicting loopback edge -# as taken) have both very high hitrate and coverage, so it is very useful. -# On the other hand, "exit block" heuristics (predicting exit edges as not -# taken) have good hitrate, but poor coverage, so only 3 branches have been -# predicted. The "loop header" heuristic has problems, since it tends to -# misspredict. -# -# The implementation of this script is somewhat brute force. My awk skills -# are limited. - -function longeval(e) -{ - e = "echo \"scale = 2 ;"e"\" | bc" - e | getline res - close (e) - return res -} - -BEGIN {nnames = 0} - -/^ .* heuristics: .*.$/ { - name=$0 - sub (/^ /,"",name) - sub (/ heuristics: .*.$/,"",name) - if (!(name in branches)) - { - names[nnames] = name - branches[name]=0 - counts[name]=0 - hits[name]=0 - phits[name]=0 - nnames++ - } - branches[name]+=1 - } - -/^ .* heuristics: .*. exec [0-9]* hit [0-9]* (.*.)$/ { - name=$0 - sub (/^ /,"",name) - sub (/ heuristics: .*. exec [0-9]* hit [0-9]* (.*.)$/,"",name) - pred=$0 - sub (/^ .* heuristics: /,"",pred) - sub (/. exec [0-9]* hit [0-9]* (.*.)$/,"",pred) - count=$0 - sub (/^ .* heuristics: .*. exec /,"",count) - sub (/ hit [0-9]* (.*.)$/,"",count) - hit=$0 - sub (/^ .* heuristics: .*. exec [0-9]* hit /,"",hit) - sub (/ (.*.)$/,"",hit) - - if (int(pred) < 50.0) - { - hit = count"-"hit; - } - counts[name]=counts[name] "+" count - hits[name]=hits[name] "+" hit - phits[name]=phits[name] "+(("hit")<"count"/2)*("count"-("hit"))+(("hit")>="count"/2)*("hit")" - - #BC crashes on long strings. Irritating. - if (length(counts[name]) > 2000) - counts[name] = longeval(counts[name]) - if (length(hits[name]) > 2000) - hits[name] = longeval(hits[name]) - if (length(phits[name]) > 2000) - phits[name] = longeval(phits[name]) - } -END { - # Heuristics called combined predicts just everything. - maxcounts = longeval(counts["combined"]) - maxbranches = branches["combined"] - max = names["combined"] - printf("HEURISTICS BRANCHES (REL) HITRATE COVERAGE (REL)\n") - for (i = 0; i < nnames ; i++) - { - name = names[i] - counts[name] = longeval(counts[name]) - printf ("%-26s %8i %5.1f%% %6s%% / %6s%% %12s %5.1f%%\n", - name, - branches[name], branches[name] * 100 / maxbranches, - longeval("("hits[name]") * 100 /(" counts[name]"-0.00001)"), - longeval("("phits[name]") * 100 /(" counts[name]"-0.00001)"), - counts[name], longeval(counts[name]" * 100 / ("maxcounts"-0.00001)")) - } -} diff --git a/contrib/analyze_brprob.py b/contrib/analyze_brprob.py new file mode 100644 index 00000000000..36371ff26ff --- /dev/null +++ b/contrib/analyze_brprob.py @@ -0,0 +1,136 @@ +#!/usr/bin/env python3 +# +# Script to analyze results of our branch prediction heuristics +# +# This file is part of GCC. +# +# GCC is free software; you can redistribute it and/or modify it under +# the terms of the GNU General Public License as published by the Free +# Software Foundation; either version 3, or (at your option) any later +# version. +# +# GCC 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 General Public License +# for more details. +# +# You should have received a copy of the GNU General Public License +# along with GCC; see the file COPYING3. If not see +# . */ +# +# +# +# This script is used to calculate two basic properties of the branch prediction +# heuristics - coverage and hitrate. Coverage is number of executions +# of a given branch matched by the heuristics and hitrate is probability +# that once branch is predicted as taken it is really taken. +# +# These values are useful to determine the quality of given heuristics. +# Hitrate may be directly used in predict.def. +# +# Usage: +# Step 1: Compile and profile your program. You need to use -fprofile-generate +# flag to get the profiles. +# Step 2: Make a reference run of the intrumented application. +# Step 3: Compile the program with collected profile and dump IPA profiles +# (-fprofile-use -fdump-ipa-profile-details) +# Step 4: Collect all generated dump files: +# find . -name '*.profile' | xargs cat > dump_file +# Step 5: Run the script: +# ./analyze_brprob.py dump_file +# and read results. Basically the following table is printed: +# +# HEURISTICS BRANCHES (REL) HITRATE COVERAGE (REL) +# early return (on trees) 3 0.2% 35.83% / 93.64% 66360 0.0% +# guess loop iv compare 8 0.6% 53.35% / 53.73% 11183344 0.0% +# call 18 1.4% 31.95% / 69.95% 51880179 0.2% +# loop guard 23 1.8% 84.13% / 84.85% 13749065956 42.2% +# opcode values positive (on trees) 42 3.3% 15.71% / 84.81% 6771097902 20.8% +# opcode values nonequal (on trees) 226 17.6% 72.48% / 72.84% 844753864 2.6% +# loop exit 231 18.0% 86.97% / 86.98% 8952666897 27.5% +# loop iterations 239 18.6% 91.10% / 91.10% 3062707264 9.4% +# DS theory 281 21.9% 82.08% / 83.39% 7787264075 23.9% +# no prediction 293 22.9% 46.92% / 70.70% 2293267840 7.0% +# guessed loop iterations 313 24.4% 76.41% / 76.41% 10782750177 33.1% +# first match 708 55.2% 82.30% / 82.31% 22489588691 69.0% +# combined 1282 100.0% 79.76% / 81.75% 32570120606 100.0% +# +# +# The heuristics called "first match" is a heuristics used by GCC branch +# prediction pass and it predicts 55.2% branches correctly. As you can, +# the heuristics has very good covertage (69.05%). On the other hand, +# "opcode values nonequal (on trees)" heuristics has good hirate, but poor +# coverage. + +import sys +import os +import re + +def percentage(a, b): + return 100.0 * a / b + +class Summary: + def __init__(self, name): + self.name = name + self.branches = 0 + self.count = 0 + self.hits = 0 + self.fits = 0 + + def count_formatted(self): + v = self.count + for unit in ['','K','M','G','T','P','E','Z']: + if v < 1000: + return "%3.2f%s" % (v, unit) + v /= 1000.0 + return "%.1f%s" % (v, 'Y') + +class Profile: + def __init__(self, filename): + self.filename = filename + self.heuristics = {} + + def add(self, name, prediction, count, hits): + if not name in self.heuristics: + self.heuristics[name] = Summary(name) + + s = self.heuristics[name] + s.branches += 1 + s.count += count + if prediction < 50: + hits = count - hits + s.hits += hits + s.fits += max(hits, count - hits) + + def branches_max(self): + return max([v.branches for k, v in self.heuristics.items()]) + + def count_max(self): + return max([v.count for k, v in self.heuristics.items()]) + + def dump(self): + print('%-36s %8s %6s %-16s %14s %8s %6s' % ('HEURISTICS', 'BRANCHES', '(REL)', + 'HITRATE', 'COVERAGE', 'COVERAGE', '(REL)')) + for (k, v) in sorted(self.heuristics.items(), key = lambda x: x[1].branches): + print('%-36s %8i %5.1f%% %6.2f%% / %6.2f%% %14i %8s %5.1f%%' % + (k, v.branches, percentage(v.branches, self.branches_max ()), + percentage(v.hits, v.count), percentage(v.fits, v.count), + v.count, v.count_formatted(), percentage(v.count, self.count_max()) )) + +if len(sys.argv) != 2: + print('Usage: ./analyze_brprob.py dump_file') + exit(1) + +profile = Profile(sys.argv[1]) +r = re.compile(' (.*) heuristics: (.*)%.*exec ([0-9]*) hit ([0-9]*)') +for l in open(profile.filename).readlines(): + m = r.match(l) + if m != None: + name = m.group(1) + prediction = float(m.group(2)) + count = int(m.group(3)) + hits = int(m.group(4)) + + profile.add(name, prediction, count, hits) + +profile.dump()