JavaScript エンジンの高速化
これらの JavaScript エンジンのうち、以下では特に JavaScriptCore を扱います。 最適化の基本戦略 JavaScript をはじめとする動的言語は、主にインタープリタにおいて実行されます。しかし、インタープリタはコンパイルされたコードと比較して実行に時間を要するという欠点があります。そこで、インタープリタの最適化では、バイトコードの JIT コンパイルが最初に行われます。 しかし、コンパイルには当然時間がかかります。少しでも高速化されたコードを生成するには、より多くの時間をコンパイルにかけなければなりません。コンパイルによる速度向上とコンパイルのレイテンシはトレードオフの関係にあります。 そこで、多くの JavaScript エンジンは、インタープリタと多階層の JIT コンパイラの組み合わせで構成されています。次の図は、主要な JavaScript エンジンの設計
Writing Truly Memory Safe JIT Compilers
Last month the V8 team published an excellent blog post on what they call the V8 Sandbox. This isn’t a sandbox for your JavaScript code — it’s intended to mitigate browser exploits caused by bugs in the JIT compiler itself. That’s important work because they report that most Chrome exploits start with a V8 memory safety bug. V8 is written in C++, so it may seem like these are the sort of bugs you’
JavaScript 実行エンジン V8 の JIT 出力コードを読んでみよう
Chrome の JavaScript はとても高速なことでも有名ですが、その実行エンジンは V8 と呼ばれます。V8 自体は独立したモジュールであり、Node.js 等にも使われております。 V8 が JavaScript を高速に実行する技術の一つが JIT (Just In Time) コンパイルです（一般的に JIT と呼ばれます）。これは、そのまま実行すると遅い JavaScript を実行中にリアルタイムに直接マシンコードに変換し（これが Just In Time と呼ばれる所以です）、途中からそのコードに入れ替えて実行することで高速化を達成しています。特に何度も実行される関数で効力を発揮します。 JIT という名前は聞いたことがあろうとも、実際に JIT がどのようなコードを実行しているのかを確認する機会は滅多にないでしょう。この記事では、実際に V8 の JIT の出力を確
Needle: A DFA Based Regex Library that Compiles to JVM ByteCode
Needle: A DFA Based Regex Library that Compiles to JVM ByteCode Many years ago, Kragen complained about the implementation and performance of Java regexes, and suggested that an implementation that emitted JVM bytecode could perform better. It's been a minute, but I'm happy to report that complaining on the Internet has served its purpose. Today, I'm releasing the 0.0.1 version of needle, a librar
PEP 744 – JIT Compilation | peps.python.org
PEP 744 – JIT Compilation Author: Brandt Bucher <brandt at python.org>, Savannah Ostrowski <savannahostrowski at gmail.com> Discussions-To: Discourse thread Status: Draft Type: Informational Created: 11-Apr-2024 Python-Version: 3.13 Post-History: 11-Apr-2024 Table of Contents Abstract Motivation Rationale Specification Support Backwards Compatibility Debugging Security Implications Apple Silicon H
Ruby 3.3 YJITのメモリ管理とRJIT 〜すべてが新しくなった2つのJITを使いこなす | gihyo.jp
Ruby 3.3リリース！ 新機能解説 Ruby 3.3 YJITのメモリ管理とRJIT 〜すべてが新しくなった2つのJITを使いこなす 2023年12月25日、Ruby 3.3.0がリリースされ、様々な新機能が加えられました。本連載では実際に携わった皆さんにその新しいRubyをご紹介いただきます。 RubyはJust-In-Time（JIT）コンパイラという機能を備えており、これを有効化すると実行時に機械語を生成して様々な最適化が行なわれ、実行が高速になります。Ruby 3.3にはYJITとRJITという2つのJITコンパイラがあり、デフォルトでは無効になっていますが、それぞれ--yjitと--rjitで有効化できます。 この回では、Ruby 3.3でYJITの性能特性が変化した点や、YJITに新たに追加された便利な機能、またRJITはどのように使うものであるかについて解説します。 YJ
Python 3.13 gets a JIT
Happy New Year everyone! In late December 2023 (Christmas Day to be precise), CPython core developer Brandt Bucher submitted a little pull-request to the Python 3.13 branch adding a JIT compiler. This change, once accepted would be one of the biggest changes to the CPython Interpreter since the Specializing Adaptive Interpreter added in Python 3.11 (which was also from Brandt along with Mark Shann
Maglev - V8’s Fastest Optimizing JIT · V8
In Chrome M117 we introduced a new optimizing compiler: Maglev. Maglev sits between our existing Sparkplug and TurboFan compilers, and fills the role of a fast optimizing compiler that generates good enough code, fast enough. Background # Until 2021 V8 had two main execution tiers: Ignition, the interpreter; and TurboFan, V8’s optimizing compiler focused on peak performance. All JavaScript code is
YJIT Is the Most Memory-Efficient Ruby JIT
This year, the YJIT team and I have gotten a paper accepted at MPLR 2023 (Managed Programming Languages and Runtimes), which is now freely available through ACM open access. The paper, titled “Evaluating YJIT’s Performance in a Production Context: A Pragmatic Approach”, goes into details of the strategy taken to evaluate YJIT’s performance in a production context. One of our key findings, when com
LuaJIT Internals: Intro
Welcome to the LuaJIT blog series. In this one, we will go over some basic introduction, stuff like the motivation behind this research, setup notes, etc. Table of Contents LuaJIT Internals(Pt. 0/3): Intro / This post LuaJIT Internals(Pt. 1/3): Stepping into the VM LuaJIT Internals(Pt. 2/3): Fighting the JIT Compiler LuaJIT Internals(Pt. 3/3): Crafting Shellcodes (Bonus!) LuaJIT Sandbox Escape: Th
JavaScript JIT compiler
This playlist contains videos where I worked on the JIT (just-in-time) compiler for Ladybird's JavaScript engine (LibJS)
Browser hacking: JIT fast path for JavaScript ToBoolean()
Follow me on X: https://x.com/awesomekling Sponsor me on GitHub: https://github.com/sponsors/awesomekling Support me on Patreon: https://patreon.com/awesomekling Donate via PayPal: https://paypal.me/awesomekling Discord: https://discord.gg/serenityos Merch: https://store.serenityos.org/ SerenityOS is a new operating system that we're building from scratch. https://serenityos.org Ladybird is a cr
Browser hacking: Let's add a JIT compiler to LibJS
Follow me on X: https://x.com/awesomekling Sponsor me on GitHub: https://github.com/sponsors/awesomekling Support me on Patreon: https://patreon.com/awesomekling Donate via PayPal: https://paypal.me/awesomekling Discord: https://discord.gg/serenityos Merch: https://store.serenityos.org/ SerenityOS is a new operating system that we're building from scratch. https://serenityos.org Ladybird is a cr
An MIR-based JIT prototype for Ruby | Red Hat Developer
I am a GCC compiler engineer, and for the past 15 years, I have primarily focused on the GCC register allocator and instruction scheduler. The major development of the GCC register allocator and instruction scheduler was completed quite some time ago, and these days, my main responsibility is maintaining these essential GCC components. About six years ago, I began dedicating half of my work time t
Ruby 3.3’s YJIT Runs Shopify’s Production Code 15% Faster
Ruby 3.2 YJIT is Battle-Tested Shopify deploys YJIT on business-critical services in production, such as Storefront Renderer, the software that powers all online storefronts on Shopify’s platform, and Shopify’s Monolith. As of the Ruby 3.2 release, YJIT sped up our Storefront Renderer by 10% on average. Storefront Renderer is a complex application. Your more reasonable-sized app might get better/w
An Introduction to Interpreters and JIT Compilation
Last week, I gave two lectures at the Programming Language Implementation Summer School (PLISS). PLISS was very well organized and the students and other presenters made for a very enjoyable week of new ideas, learning, and discussing. For my own lectures, I decided to take an approach that focused more on the high-level ideas and can introduce a wider audience to how we build interpreters and a r
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Finding Simple Rewrite Rules for the JIT with Z3
How JIT Compilers are Implemented and Fast: Pypy, LuaJIT, Graal and More | kipply's blog
Browser hacking: Basic try...catch in the JavaScript JIT
Let's prototype a JavaScript JIT compiler!