Ruby 3.2’s YJIT is Production-Ready

YJIT, a just-in-time (JIT) implementation on top of CRuby built at Shopify, is now production-ready and delivering major improvements to performance and speed. Maxime (Senior Staff Engineer and leader of the YJIT project) shares the updates that have been made in this newest version of YJIT, and future plans for further optimization.

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Shopify
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Maxime Chevalier-Boisvert
•11 min read•advanced•
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AWSRailsRubyRust

Overview

The article discusses the production readiness of YJIT, a Just-In-Time compiler for Ruby, highlighting its development journey, major improvements in Ruby 3.2, and its deployment at Shopify. Key advancements include performance enhancements, reduced memory usage, and support for ARM64 architecture.

What You'll Learn

1

How to implement YJIT in Ruby applications for performance gains

2

Why porting YJIT from C to Rust improves safety and maintainability

3

How to optimize memory usage in JIT compilers

4

When to deploy YJIT in production environments for Ruby applications

Prerequisites & Requirements

  • Understanding of Just-In-Time compilation concepts
  • Familiarity with Rust programming language(optional)

Key Questions Answered

What performance improvements does YJIT provide in Ruby 3.2?
YJIT in Ruby 3.2 offers approximately 38% speedup over the interpreter for railsbench, and cumulatively, it is 57% faster than the Ruby 3.1.3 interpreter. These improvements enhance the efficiency of Ruby applications significantly.
How does YJIT handle memory usage compared to previous versions?
YJIT has reduced its memory overhead to about one third of what it was in Ruby 3.1, making it more suitable for production use. This was achieved through optimizations in metadata storage and implementing a garbage collector for unused machine code.
What new features does YJIT 3.2 support?
YJIT 3.2 introduces support for ARM64 CPUs, allowing it to run natively on Apple M1/M2 and AWS Graviton processors. This expands its usability across various platforms beyond the previous x86-64 support.
When did Shopify decide to deploy YJIT in production?
Shopify began deploying YJIT in production about a year ago, and with the improvements in Ruby 3.2, it is now deemed production-ready. They have observed real speedups of 5% to 10% in request completion times.

Key Statistics & Figures

Speedup over Ruby 3.1.3 interpreter
57%
Cumulative improvement of YJIT in Ruby 3.2
Memory overhead reduction
approximately one third
Compared to YJIT in Ruby 3.1
Speedup on railsbench
38%
Compared to the Ruby 3.2 interpreter
Request completion time improvement
5% to 10%
Observed during Shopify's production deployment of YJIT

Technologies & Tools

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Programming Language
Ruby
Core language for which YJIT is a Just-In-Time compiler
Programming Language
Rust
Used to rewrite YJIT for improved safety and maintainability

Key Actionable Insights

1
Consider integrating YJIT into your Ruby applications to leverage significant performance improvements.
With YJIT providing up to 57% faster execution compared to Ruby 3.1.3, integrating it can enhance application responsiveness and efficiency, especially for high-traffic environments.
2
Evaluate the memory usage of your JIT compiler and optimize it to ensure production readiness.
YJIT's reduction in memory overhead to one third of its previous usage illustrates the importance of memory optimization for deploying JIT compilers in production.
3
Stay updated with the latest Ruby versions and their features to maximize performance.
Ruby 3.2's enhancements, including YJIT support for ARM64, highlight the need for developers to adapt to new releases to fully utilize performance gains.

Common Pitfalls

1
Underestimating the memory overhead of JIT compilers can lead to deployment challenges.
Many developers may overlook the additional memory requirements of JIT compilers, which can complicate production deployments, as seen with YJIT's initial challenges in Ruby 3.1.

Related Concepts

Just-in-time Compilation
Ruby Performance Optimization
Memory Management In Programming Languages
Arm64 Architecture Support