Latest posts
- Sorry for marking all the posts as unreadJan 31, 2024
I noticed that the URLs were all a little off (had two slashes instead of one) and went in and fixed it. I did not think everyone's RSS software was going to freak out the way it did. PS: this is a special RSS-only post that is not visible on the site. Enjoy.
- Partial static single information formMay 12, 2026
In compilers, static single information form (SSI) is a common extension to static single assignment form (SSA). It was introduced by C. Scott Ananian in 1999 in his MS thesis (PDF) 1. SSI extends your existing SSA intermediate representation by discovering facts from your existing program and reifying them as path-dependent/flow-sensitive IR nodes. That might sound complicated, but at least the b
- Value numberingApr 04, 2026
Welcome back to compiler land. Today we’re going to talk about value numbering, which is like SSA, but more. Static single assignment (SSA) gives names to values: every expression has a name, and each name corresponds to exactly one expression. It transforms programs like this: x = 0 x = x + 1 x = x + 1 where the variable x is assigned more than once in the program text, into programs like this
- Using Perfetto in ZJITMar 27, 2026
Originally published on Rails At Scale. Look! A trace of slow events in a benchmark! Hover over the image to see it get bigger. Now read on to see what the slow events are and how we got this pretty picture. The rules The first rule of just-in-time compilers is: you stay in JIT code. The second rule of JIT is: you STAY in JIT code! When control leaves the compiled code to run in the interpreter—w
- A fuzzer for the Toy OptimizerFeb 25, 2026
Another entry in the Toy Optimizer series. It’s hard to get compiler optimizers right. Even if you build up a painstaking test suite by hand, you will likely miss corner cases, especially corner cases at the interactions of multiple components or multiple optimization passes. I wanted to see if I could write a fuzzer to catch some of these bugs automatically. But a fuzzer alone isn’t much use with
- Type-based alias analysis in the Toy OptimizerFeb 16, 2026
Another entry in the Toy Optimizer series. Last time, we did load-store forwarding in the context of our Toy Optimizer. We managed to cache the results of both reads from and writes to the heap—at compile-time! We were careful to mind object aliasing: we separated our heap information into alias classes based on what offset the reads/writes referenced. This way, if we didn’t know if object a and b
- A multi-entry CFG design conundrumJan 22, 2026
Background and bytecode design The ZJIT compiler compiles Ruby bytecode (YARV) to machine code. It starts by transforming the stack machine bytecode into a high-level graph-based intermediate representation called HIR. We use a more or less typical1 control-flow graph (CFG) in HIR. We have a compilation unit, Function, which has multiple basic blocks, Block. Each block contains multiple instructio
- The GDB JIT interfaceDec 30, 2025
GDB is great for stepping through machine code to figure out what is going on. It uses debug information under the hood to present you with a tidy backtrace and also determine how much machine code to print when you type disassemble. This debug information comes from your compiler. Clang, GCC, rustc, etc all produce debug data in a format called DWARF and then embed that debug information inside t
- Load and store forwarding in the Toy OptimizerDec 24, 2025
Another entry in the Toy Optimizer series. A long, long time ago (two years!) CF Bolz-Tereick and I made a video about load/store forwarding and an accompanying GitHub Gist about load/store forwarding (also called load elimination) in the Toy Optimizer. I said I would write a blog post about it, but never found the time—it got lost amid a sea of large life changes. It’s a neat idea: do an abstract
- ZJIT is now available in Ruby 4.0Dec 24, 2025
Originally published on Rails At Scale. ZJIT is a new just-in-time (JIT) Ruby compiler built into the reference Ruby implementation, YARV, by the same compiler group that brought you YJIT. We (Aaron Patterson, Aiden Fox Ivey, Alan Wu, Jacob Denbeaux, Kevin Menard, Max Bernstein, Maxime Chevalier-Boisvert, Randy Stauner, Stan Lo, and Takashi Kokubun) have been working on ZJIT since the beginning of
- How to annotate JITed code for perf/samplyDec 18, 2025
Brief one today. I got asked “does YJIT/ZJIT have support for [Linux] perf?” The answer is yes, and it also works with samply (including on macOS!), because both understand the perf map interface. This is the entirety of the implementation in ZJIT1: fn register_with_perf(iseq_name: String, start_ptr: usize, code_size: usize) { use std::io::Write; let perf_map = format!("/tmp/perf-{}.map",