Last year, during the pandemic, I took a job at Shopify, a company that runs a massive server infrastructure powered by Ruby on Rails. I joined a team with multiple software engineers working on improving the performance of Ruby code in a variety of ways, ranging from optimizing the CRuby interpreter and its garbage collector to the implementation of TruffleRuby, an alternative Ruby implementation. Since then, I’ve been working with a team of skilled engineers from Shopify and GitHub on YJIT, a new Just-in-time (JIT) compiler built inside CRuby.
This project is important to Shopify and Ruby developers worldwide because speed is an underrated feature. There’s already a JIT compiler inside CRuby, known as MJIT, which has been in the works for three years. And while it has delivered speedups on smaller benchmarks, so far, it’s been less successful at delivering real-world speedups on widely used Ruby applications such as Ruby on Rails. With YJIT, we take a data-driven approach and focus specifically on performance hotspots of larger applications such as Rails and Shopify Core (Shopify’s main Rails monolith).
YJIT is a project to gradually build a JIT compiler inside CRuby such that more and more of the code is executed by the JIT, which will eventually replace the interpreter for most of the execution. The compiler, which is soon to become officially part of CRuby, is based on Basic Block Versioning (BBV), a JIT compiler architecture I started developing during my PhD. I’ve given talks about YJIT this year at the MoreVMs 2021 workshop and another one at RubyKaigi 2021 if you’re curious to hear more about the approach we’re taking.
We’re about one year into the YJIT project at this point, and so far, we’re pleased with the results, which have significantly improved since the MoreVMs talk. According to our set of benchmarks, we’ve achieved speedups over the CRuby interpreter of 20% on railsbench, 39% on liquid template rendering, and 37% on activerecord. YJIT also delivers very fast warm up. It reaches near-peak performance after a single iteration of any benchmark and performs at least as well as the interpreter on every benchmark, even on the first iteration.
Building YJIT inside CRuby comes with some limitations. It means that our JIT compiler has to be written in C and that we have to work with design decisions in the CRuby codebase that weren’t made with a high-performance JIT compiler in mind. However, it has the key advantage that YJIT is able to maintain almost 100% compatibility with existing Ruby code and packages. We pass the CRuby test suite, comprising about 30,000 tests, and we have also been able to pass all of the tests of the Shopify Core CI, a codebase that contains over three million lines of code and depends (directly and indirectly) on over 500 Ruby gems, as well as all the tests in the CI for GitHub’s backend. We also have a working deployment to a small percentage of production servers at Shopify.
We believe that the BBV architecture that powers YJIT offers some key advantages when compiling dynamically-typed code. Having end-to-end control over the full code generation pipeline will allow us to go farther than what’s possible with the current architecture of MJIT, which is based on GCC. Notably, YJIT can quickly specialize code based on type information and patch code at run time based on the run-time behavior of programs. The advantage in terms of compilation speed and warmup time is also difficult to match.
The Ruby core developers have invited the YJIT team to merge the compiler into Ruby 3.1. It’s a great honor for my colleagues and myself to have our work become officially part of Ruby. This means, in a few months, every Ruby developer will have the opportunity to try YJIT by simply passing a command-line option to the Ruby binary. However, our journey doesn’t stop there, and we already have plans in the works to make YJIT and CRuby even faster.
Currently, only about 79% of instructions in railsbench are executed by YJIT, and the rest run in the interpreter, meaning that there’s still a lot we can do to improve upon our current results. There’s a clear path forward, and we believe YJIT can deliver much better performance than it does now. However, as part of building YJIT, we’ve had to dig through the implementation of CRuby to understand it in detail. In doing so, we’ve identified a few key elements in its architecture that we believe can be improved to unlock higher performance. These improvements won’t just help YJIT, they’ll help MJIT too, and some of them will even make the interpreter faster. As such, we will likely try to upstream some of this work separately from YJIT.
I may expand on some of these in future blog posts, but here is a tentative list of potential improvements to CRuby that we would like to tackle:
- Moving CRuby to an object model based on object shapes.
- Changing the CRuby type tagging scheme to reduce the cost of type checks.
- Implementing a more fine-grained constant caching mechanism.
- A faster, more lightweight calling convention.
- Rewriting C runtime methods in Ruby so that JIT compilers can inline through them.
Matz (Yukihiro Matsumoto) has stated in his recent talk at Euruko 2021 that Ruby would remain conservative with language additions in the near future. We believe this is a wise decision as rapid language changes can make it difficult for JIT implementations to get off the ground and stay up to date. It makes some sense, in our opinion, for Ruby to focus on internal changes that will make the language more robust and deliver very competitive performance in the future.
I hope you’re as excited about the future of YJIT and Ruby as we are. If you’re interested in trying YJIT, it’s available on GitHub under the same open source license as CRuby. If you run into bugs, we’d appreciate it if you would open an issue and help us find a simple reproduction. Stay tuned as two additional blog posts about YJIT are coming soon, with details about how you can try YJIT, and the performance tracking system we’ve built for speed.yjit.org.
Maxime Chevalier-Boisvert obtained a PhD in compiler design at the University of Montreal in 2016, where she developed Basic Block Versioning (BBV), a JIT compiler architecture optimized for dynamically-typed programming languages. She is currently leading a project at Shopify to build YJIT, a new JIT compiler built inside CRuby.
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