[B! profiling] dannã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

dann id:dann

profilingã«é–¢ã™ã‚‹dannã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (19)

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ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒ©ã‚’ä½¿ç”¨ã—ãŸ TensorFlow ã®ãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹æœ€é©åŒ– Â |Â TensorFlow Core
ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒ©ã‚’ä½¿ç”¨ã—ãŸ TensorFlow ã®ãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹æœ€é©åŒ– ã‚³ãƒ¬ã‚¯ã‚·ãƒ§ãƒ³ã§ã‚³ãƒ³ãƒ†ãƒ³ãƒ„ã‚’æ•´ç† å¿…è¦ã«å¿œã˜ã¦ã€ã‚³ãƒ³ãƒ†ãƒ³ãƒ„ã®ä¿å˜ã¨åˆ†é¡žã‚’è¡Œã„ã¾ã™ã€‚ ã“ã®ã‚¬ã‚¤ãƒ‰ã§ã¯ã€TensorFlow Profiler ã§æä¾›ã•ã‚Œã¦ã„ã‚‹ãƒ„ãƒ¼ãƒ«ã‚’ä½¿ç”¨ã—ã¦ã€TensorFlow ãƒ¢ãƒ‡ãƒ«ã®ãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹ã‚’è¿½è·¡ã™ã‚‹æ–¹æ³•ã‚’èª¬æ˜Žã—ã¾ã™ã€‚ã¾ãŸã€ãƒ›ã‚¹ãƒˆï¼ˆCPUï¼‰ã€ãƒ‡ãƒã‚¤ã‚¹ï¼ˆGPUï¼‰ã€ã¾ãŸã¯ãƒ›ã‚¹ãƒˆã¨ãƒ‡ãƒã‚¤ã‚¹ã®ä¸¡æ–¹ã®çµ„ã¿åˆã‚ã›ã§ãƒ¢ãƒ‡ãƒ«ãŒã©ã®ã‚ˆã†ã«æ©Ÿèƒ½ã™ã‚‹ã‹ã‚’ç¢ºèªã—ã¾ã™ã€‚ ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒªãƒ³ã‚°ã¯ã€ãƒ¢ãƒ‡ãƒ«å†…ã®ã•ã¾ã–ã¾ãª TensorFlow æ¼”ç®—ï¼ˆopï¼‰ã«ã‚ˆã‚‹ãƒãƒ¼ãƒ‰ã‚¦ã‚§ã‚¢ãƒªã‚½ãƒ¼ã‚¹æ¶ˆè²»ï¼ˆæ™‚é–“ã¨ãƒ¡ãƒ¢ãƒªï¼‰ã‚’æŠŠæ¡ã—ã€ãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹ã®ãƒœãƒˆãƒ«ãƒãƒƒã‚¯ã‚’è§£æ¶ˆã—ã¦æœ€çµ‚çš„ã«ãƒ¢ãƒ‡ãƒ«ã®å®Ÿè¡Œã‚’é«˜é€ŸåŒ–ã™ã‚‹ã®ã«å½¹ç«‹ã¡ã¾ã™ã€‚ ã“ã®ã‚¬ã‚¤ãƒ‰ã§ã¯ã€ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒ©ã®ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«æ–¹æ³•ã€åˆ©ç”¨å¯èƒ½ãªã•ã¾ã–ã¾ãªãƒ„ãƒ¼ãƒ«ã€ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒ©ã®ã•ã¾ã–ã¾ãªãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹ãƒ‡ãƒ¼ã‚¿åŽé›†ãƒ¢ãƒ¼ãƒ‰ã€ãŠã‚ˆ
dann 2024/02/01
tensorflow

profiling

performance
ãƒªãƒ³ã‚¯
GitHub - gaogaotiantian/viztracer: VizTracer is a low-overhead logging/debugging/profiling tool that can trace and visualize your python code execution.
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dann 2023/05/03
python

profiling

performance
ãƒªãƒ³ã‚¯
GitHub - grafana/pyroscope: Continuous Profiling Platform. Debug performance issues down to a single line of code
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dann 2021/02/21
python

profiling

performance
ãƒªãƒ³ã‚¯
.NET Memory Profiler - Find Memory Leaks and Optimize Memory Usage in Programs Written in C#, VB.NET or any other .NET Language
Find Memory Leaks and Optimize Memory Usage in any .NET Program .NET Memory Profiler is a powerful tool for finding memory leaks and optimizing the memory usage in programs written in C#, VB.NET or any other .NET Language. With the help of the profiling guides, the automatic memory analyzer, and specialized trackers, you can make sure that your program has no memory or resource leaks, and that the
dann 2013/05/26
csharp

memory

profiling
ãƒªãƒ³ã‚¯
mmi2010040065 65..79
.......................................................................................................................................................................................................................... GOOGLE-WIDE PROFILING: A CONTINUOUS PROFILING INFRASTRUCTURE FOR DATA CENTERS .......................................................................................................
dann 2011/06/17
google

performance

profiling

cool
ãƒªãƒ³ã‚¯
GitHub - jbellis/jamm: Java Agent for Memory Measurements
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dann 2011/04/20
java

profiling

memory
ãƒªãƒ³ã‚¯
profile and pstats â€” Performance Analysis â€” PyMOTW 3
The profile module provides APIs for collecting and analyzing statistics about how Python source consumes processor resources. Note This output reports in this section have been reformatted to fit on the page. Lines ending with backslash (\) are continued on the next line. Running the ProfilerÂ¶ The most basic starting point in the profile module is run(). It takes a string statement as argument, a
dann 2010/10/16
python

profiling

performance
ãƒªãƒ³ã‚¯
/dev/tty: Using VisualVM to fix live Tomcat and JMV problems (Java)
dann 2010/09/30
visualvm

java

profiling

performance
ãƒªãƒ³ã‚¯
ruby-profã¨KCacheGrindã§ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒ«é‡ŽéƒŽã«ãªã‚‹ - æ˜¼ãƒ¡ã‚·ç‰©èªž
é€Ÿã•ãŒè¶³ã‚Šãªã„ï¼ï¼ï¼ï¼ï¼ ãã‚“ãªæ™‚ã¯ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒªãƒ³ã‚°ã®æ™‚é–“ã§ã™ãã€‚ Rubyã«ã¯æ¨™æº–æ·»ä»˜ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã¨ã—ã¦ profile ã¨ã„ã†ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒ©ãŒã¤ã„ã¦ãã‚‹ã€‚ã§ã‚‚ã“ã®ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã¯ã‚ã¾ã‚Šã«é…ã™ãŽã¦å®Ÿç”¨ã«è€ãˆãªã„ã‹ã‚‰ã€å¤šåˆ†èª°ã‚‚ä½¿ã£ã¦ã„ãªã„ã€‚ã»ã¨ã‚“ã©ã®Rubyistã¯ ruby-prof ã‚’ä½¿ã£ã¦ã„ã‚‹ã“ã¨ã ã‚ã†ã€‚ ä»Šå›žã¯ã“ã® ruby-prof ã‚’ä½¿ã£ã¦ Ruby ãƒ—ãƒã‚°ãƒ©ãƒ ã®ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒªãƒ³ã‚°ã™ã‚‹æ–¹æ³•ã‚’ç´¹ä»‹ã™ã‚‹ã€‚ è¨ˆæ¸¬ã™ã‚‹ï¼ˆruby-profï¼‰ ruby-profã¯rubygemsã§ç°¡å˜ã«å…¥ã‚‹ã€‚ $ gem install ruby-profruby-profã¨ã„ã†ã‚³ãƒžãƒ³ãƒ‰ãƒ©ã‚¤ãƒ³ãƒ„ãƒ¼ãƒ«ãŒã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã•ã‚Œã‚‹ã€‚ã“ã‚Œã‚’ä½¿ã†ã¨ã€ãƒ—ãƒã‚°ãƒ©ãƒ ã‚’å¤‰æ›´ã™ã‚‹ã“ã¨ãªãæ‰‹è»½ã«ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒªãƒ³ã‚°ã‚’è¡Œã†ã“ã¨ãŒã§ãã‚‹ã€‚ruby-profã‚³ãƒžãƒ³ãƒ‰ã®usageã¯ä»¥ä¸‹ã®ã¨ãŠã‚Šã€‚ ruby_prof 0.9.2 Usage: ruby_
dann 2010/09/20
ruby-prof

ruby

profiling

performance
ãƒªãƒ³ã‚¯
PHPãƒ—ãƒã‚°ãƒ©ãƒ ã‚’è§£æžã—ã¦ä½•å‡¦ãŒé‡ã„ã‹ï¼ŸãŒãƒ–ãƒ©ã‚¦ã‚¶ä¸Šã§ç°¡å˜ã«åˆ†ã‹ã‚‹ã€ŒXHProfã€:phpspoté–‹ç™ºæ—¥èªŒ
PHPãƒ—ãƒã‚°ãƒ©ãƒ ã‚’è§£æžã—ã¦ä½•å‡¦ãŒé‡ã„ã‹ï¼ŸãŒãƒ–ãƒ©ã‚¦ã‚¶ä¸Šã§ç°¡å˜ã«åˆ†ã‹ã‚‹ã€ŒXHProfã€ 2009å¹´03æœˆ25æ—¥- XHProf Documentation (Draft) PHPãƒ—ãƒã‚°ãƒ©ãƒ ã‚’è§£æžã—ã¦ä½•å‡¦ãŒé‡ã„ã‹ï¼ŸãŒãƒ–ãƒ©ã‚¦ã‚¶ä¸Šã§ç°¡å˜ã«åˆ†ã‹ã‚‹ã€ŒXHProfã€ã€‚ é€šå¸¸ã€PHPã§ã®ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒªãƒ³ã‚°ã¨ã„ã†ã¨ã€Xdebugã§ãƒ•ã‚¡ã‚¤ãƒ«ã‚’åãå‡ºã—ã¦ã€WinCacheGrindã‚„KCacheGrindã§èªã¿è¾¼ã‚€ã¨ã„ã†ã®ãŒå®šç•ªã§ã™ã€‚ ã§ã™ãŒã€ã“ã®æ–¹æ³•ã ã¨ã€ãƒ•ã‚¡ã‚¤ãƒ«ã‚’åãå‡ºã—ãŸãƒ•ã‚¡ã‚¤ãƒ«ã‚’GETã—ã¦ã€ã‚½ãƒ•ãƒˆã«èªã¿è¾¼ã¾ã›ã‚‹ã€ã¨ã„ã†ã¡ã‚‡ã£ã¨é¢å€’ãªæ‰‹é †ãŒå¿…è¦ã§ã—ãŸã€‚ XHProf ã‚’ä½¿ãˆã°ã€ãƒ–ãƒ©ã‚¦ã‚¶ä¸Šã§ã€ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒªãƒ³ã‚°ãŒå‡ºæ¥ã‚‹ã¿ãŸã„ã§ã™ã€‚ XHProfã®ç‰¹å¾´ ã¾ãšã€ã‚»ã‚°ãƒ¡ãƒ³ãƒˆã”ã¨ã®å®Ÿè¡Œæ™‚é–“ã‚„ãƒ¡ãƒ¢ãƒªåˆ©ç”¨ã®çŠ¶æ³ãªã‚“ã‹ãŒãƒ–ãƒ©ã‚¦ã‚¶ã§è¦‹ã‚Œã¾ã™ã€‚ ãƒ—ãƒã‚°ãƒ©ãƒ ã®æ§‹é€ ã‚’æŠŠæ¡ã™ã‚‹ã®ã«ã‚‚ä½¿ãˆã¾ã™ã€‚ ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒªãƒ³ã‚°ã®éšŽå±¤è¡¨ç¤º ï¼’ã¤ã®ãƒ—ãƒãƒ•ã‚¡
dann 2009/12/13
php

debug

profiling
ãƒªãƒ³ã‚¯
Lessons Learned in Large Computations with Ruby - Kevin Menard's Weblog
Introduction This is the follow-up post to my GitHub Contest Recap post that I promised. As mentioned, I submitted two entries for the GitHub contest, starting with Ruby and then rewriting in Java. This post summarizes why I ultimately dropped Ruby in favor of Java for this particular task. I apologize for its length, but it is divided into discrete sections and can be read in chunks without great
dann 2009/10/19
profiling

java

ruby
ãƒªãƒ³ã‚¯
æ¯Žç§’100å›žJavaScriptãŒå®Ÿè¡Œã£ã¦ã®ãŒã©ã®ç¨‹åº¦ãªã®ã‹ - os0x.blog
éžãƒãƒƒãƒˆã§èžã„ãŸè©±ãªã©ã‚‚å«ã‚ã€ã“ã“ã¾ã§ã‚„ã£ã¦ã‚‚ä¿¡ã˜ãªã„äººã‚‚ã„ã£ã±ã„ã„ã‚‹ã¿ãŸã„ã§ã€ãã“ã¾ã§ç–‘ã†äººã®ãŸã‚ã«ã¨ã‚Šã‚ãˆãšãƒ‘ãƒƒãƒã¯å‡ºã—ã¦ãŠã„ãŸã®ã ãŒã€ã¿ã‚“ãªã€Œæ€ªã—ã„ã‚ˆãã€ã£ã¦é™°ã§è¨€ã†ã ã‘ã§ã€èª°ã‚‚è¿½è©¦ã¯ã—ã¦ãã‚Œãªã‹ã£ãŸã¿ãŸã„ã ã€‚ä»–äººã®æ›¸ã„ãŸã€ã—ã‹ã‚‚CPUä½¿ç”¨çŽ‡ãªã‚“ã¦å‰²ã¨ã©ã†ã§ã‚‚ã„ã„ç³»ã®ã‚¨ãƒ³ãƒˆãƒªãªã‚“ã¦ã‚ã–ã‚ã–æ¤œè¨¼ã™ã‚‹äººã¯ãã‚Šã‚ƒã„ãªã„ã ã‚ã†ã¨ã¯æ€ã†ã‘ã©ã€æ°—åˆ†ãŒæ‚ªã„ã®ã‚‚ç¢ºã‹ã ã€‚ã©ã†ã›èª°ã‚‚è©¦ã•ãªã„ãªã‚‰ã€ãƒ‘ãƒƒãƒè‡ªä½“ã¯æ¬¡ã®ãƒã‚¿ã«ã¨ã£ã¨ãã‚ƒã‚ˆã‹ã£ãŸãªãâ€¦ã€‚ http://d.hatena.ne.jp/tkng/20091003/1254578195 ã§ã¯æŠ˜è§’ãªã®ã§ã€æ¤œè¨¼ã‚’ã€‚Firefoxå‰æãªã‚‰ã€Firebugã®ãƒ—ãƒãƒ•ã‚¡ã‚¤ãƒ«æ©Ÿèƒ½ã§ä¸€ç™ºãªã®ã§ã€æ¤œè¨¼ç”¨ãƒžã‚·ãƒ³*1ã§ä»¥ä¸‹ã®ã‚¹ã‚¯ãƒªãƒ—ãƒˆå®Ÿè¡Œã€‚ // ==UserScript== // @name google stats // @namespace http://ss-o.n
dann 2009/10/06
firefox

profiling
ãƒªãƒ³ã‚¯
Profiling Ruby With Google's Perftools - igvita.com
By Ilya Grigorik on June 13, 2009 Benchmarking, profiling and debugging are all areas where better tool support could really benefit the Ruby community. Built in benchmark library and extensions such as ruby-prof provide us with a minimal level of introspection to help identify the common bottlenecks, but they still fall short of the available tools for the JVM, or other dynamic runtimes. If you'r
dann 2009/06/15
ruby

profiling

google
ãƒªãƒ³ã‚¯
NYTProf.pm
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dann 2009/04/24
profiling

perl
ãƒªãƒ³ã‚¯
Slide 1
dann 2008/11/08
profiling

performance
ãƒªãƒ³ã‚¯
Jon Schutz Technical Notes and Recommendations Â» Adding Action Timings to your Catalyst Output
dann 2008/11/03
catalyst

performance

perl

profiling
ãƒªãƒ³ã‚¯
NYTProf 2.04 gives you 90% smaller data files
dann 2008/10/04
perl

profiling

performance
ãƒªãƒ³ã‚¯
NYTProf v2 - OSCON 2008
A screencast of my presentation about the Devel::NYTProf v2 perl source code profiler that I gave at the Open Source Convention (OSCON) in July 2008. 41 minutes long. See also http://search.cpan.org/dist/Devel-NYTProf/ and http://blog.timbunce.org/2008/07/15/nytprof-v2-a-major-advance-in-perl-profilers/ View fullscreen for a more detailed picture.
dann 2008/08/07
perl

profiling
ãƒªãƒ³ã‚¯
Oracle Java Technologies | Oracle
dann 2005/10/16
jfluid

profiling
ãƒªãƒ³ã‚¯
1