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Ruby’s performance is getting better and better with each release and the newly released 2.5.0 version is no different. Before the release of Ruby 2.4 last year I benchmarked Ruby 2.3.3p222 and 2.4.0preview3 and was pleasantly surprised. Since the release notes of Ruby 2.5 highlight some performance improvements I ran another benchmark. This time I benchmarked Ruby 2.3.6, 2.4.3 and 2.5.0 on all th
この記事はRuby Advent Calendar 2017 17日目の記事です。 benchmark_driver.gem とは Rubyの処理系を高速化していく上で重要な計測環境を改善するため、Ruby本体のリポジトリにあるbenchmark/driver.rbの後継として作られたベンチマークツールです。普通にRubyのスクリプトのパフォーマンスを比較するのにも使えます。 また、このgemはRuby Association開発助成金2017に採択されたプロジェクトとして開発されています。 何が便利なのか Procの起動を行なわない精度の良い計測ができる 皆さんがベンチマークによく使うのは、標準ライブラリの benchmark.rb か、見易い比較結果を得られる benchmark-ips.gem 等でしょう。 benchmark-ips.gem でよく使われるインターフェースや ben
Sam Saffron Programming, Technology and the Art of Hacking Lately I needed to add some instruments into Discourse. I wanted every request to measure: How many SQL statements and Redis commands are executed? How much time was spent in those sections? This can easily be abstracted to a more generalize problem of class ExternalClass def method_to_measure end end Solving this problem breaks down into
Towards Ruby3x3 Performance Introducing RTL and MJIT Vladimir Makarov Red Hat September 21, 2017 Vladimir Makarov (Red Hat) Towards Ruby3x3 Performance September 21, 2017 1 / 30 About Myself Red Hat, Toronto office, Canada Tools group (GCC, Glibc, LLVM, Rust, Go, OpenMP) I part of a bigger platform enablement team (porting Linux kernel to new hardware) 20 years of work on GCC 2 years of work on MR
はじめに JuanitoFatas/fast-rubyにRubyの役割の似たメソッドのパフォーマンスがまとまっていたが、結果だけでなくコードも並べて一覧化したかったので、当該リポジトリをcloneしてきて、以下のscriptを実行してまとめなおした。 File.open('./result.md', 'w') do |dest| $stdout = dest Dir.glob('code/**/*rb').each do |f| dest.puts "## #{File.basename(f, '.rb')}" dest.puts "\`\`\`rb" dest.puts File.open(f).read dest.puts "\`\`\`" dest.puts dest.puts "\`\`\`" require "./#{f}" dest.puts "\`\`\`" dest.put
Ruby 2.4.0 introduced a lot of great new features. One of them was open addressing for hash tables - the details of open addressing are a bit obscure, but Ruby hash tables are now faster. Everybody uses hash tables, so everybody gets extra speed. Awesome! But how did that happen? There's an interesting story there. Let's tell that story and benchmark with Rails Ruby Bench, shall we? (Don't care ab
「Rubyのしくみ」を読んでいたら、「キーワード引数って遅いんじゃないか?」と思ったので調べてみました。 まずは結果から。 rubyの各バージョンで、キーワード引数がどのくらい遅いのかを調べてみました。 調査コードは以下です。 Makefile VERSIONS= \ 2.0.0-p0 \ 2.1.0 \ 2.2.0-preview1 \ 2.2.0-preview2 \ 2.2.0 \ 2.3.0 run: $(VERSIONS) $(VERSIONS): @rbenv global $@ @rbenv rehash @echo "" @echo "===============================================================" @ruby -v @echo "----------------------------------------
This week, I've been playing with Puma processes. Headius, Nate Berkopec, you can probably stop reading now. You won't learn much ;-) One consequence of the GIL is that a single Ruby process has limited ability to fully use the capabilities of a multi-core machine, including a larger AWS instance. As a result, the optimum number of Rails processes for your AWS instance is probably not just one. I'
Ruby 2.4 got released this Christmas with a lot of exciting features. One of the most underrated features in ruby 2.4 is hash table improvements. Before going into details about implementation, let’s first check the benchmark to know how this change gonna affect your ruby application. Some benchmarks are: Getting keys and values of a hash h = {} 10000.times do |i| h[i] = nil end # Get all hash val
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