**DISCLAIMER: Please note that this project is experimental. It is very much a work in progress, it may cause your software to crash, and current performance results will vary widely, especially on larger applications.**
- MoreVMs 2021 talk: [YJIT: Building a New JIT Compiler Inside CRuby](https://www.youtube.com/watch?v=vucLAqv7qpc)
- ECOOP 2016 talk: [Interprocedural Type Specialization of JavaScript Programs Without Type Analysis](https://www.youtube.com/watch?v=sRNBY7Ss97A)
- ECOOP 2016 paper: [Interprocedural Type Specialization of JavaScript Programs Without Type Analysis](https://drops.dagstuhl.de/opus/volltexte/2016/6101/pdf/LIPIcs-ECOOP-2016-7.pdf)
- ECOOP 2016 talk: [Simple and Effective Type Check Removal through Lazy Basic Block Versioning](https://www.youtube.com/watch?v=S-aHBuoiYE0)
- ECOOP 2015 paper: [Simple and Effective Type Check Removal through Lazy Basic Block Versioning](https://arxiv.org/pdf/1411.0352.pdf)
YJIT is a work in progress and as such may not yet be mature enough for mission-critical software. Below is a list of known limitations, all of which we plan to eventually address:
- No garbage collection for generated code.
Because there is no GC for generated code yet, your software could run out of executable memory if it is large enough. You can change how much executable memory is allocated using [YJIT's command-line options](https://github.com/Shopify/yjit#command-line-options).
The YJIT `ruby` binary can be built with either GCC or Clang. For development, we recommend enabling debug symbols so that assertions are enabled as this makes debugging easier. Enabling debug mode will also make it possible for you to disassemble code generated by YJIT. However, this causes a performance hit. For maximum performance, compile with GCC, without the `DRUBY_DEBUG` or `YJIT_STATS` build options. More detailed build instructions are provided in the [Ruby README](https://github.com/ruby/ruby#how-to-compile-and-install).
To support disassembly of the generated code, `libcapstone` is also required (`brew install capstone` on MacOS, `sudo apt-get install -y libcapstone-dev` on Ubuntu/Debian and `sudo dnf -y install capstone-devel` on Fedora).
The machine code generated for a given method can be printed by adding `puts YJIT.disasm(method(:method_name))` to a Ruby script. Note that no code will be generated if the method is not compiled.
We have collected a set of benchmarks and implemented a simple benchmarking harness in the [yjit-bench](https://github.com/Shopify/yjit-bench) repository. This benchmarking harness is designed to disable CPU frequency scaling, set process affinity and disable address space randomization so that the variance between benchmarking runs will be as small as possible. Please kindly note that we are at an early stage in this project.
This section contains tips on writing Ruby code that will run as fast as possible on YJIT. Some of this advice is based on current limitations of YJIT, while other advice is broadly applicable. It probably won't be practical to apply these tips everywhere in your codebase, but you can profile your code using a tool such as [stackprof](https://github.com/tmm1/stackprof) and refactor the specific methods that make up the largest fractions of the execution time.
You can also compile YJIT in debug mode and use the `--yjit-stats` command-line option to see which bytecodes cause YJIT to exit, and refactor your code to avoid using these instructions in the hottest methods of your code.
or that we don't have a good reproduction for it, so please open an issue and provide as much information as you can about your configuration and a description of how you encountered the problem. List the commands you used to run YJIT so that we can easily reproduce the issue on our end and investigate it. If you are able to produce a small program reproducing the error to help us track it down, that is very much appreciated as well.