We know that Ruby and especially Rails applications can be very dynamic and pretty large. Though, many of the optimizations interpreters and even just-in-time compilers use have been invented in the 1980s and 1990s before Ruby and Rails even existed. So, I was wondering: do these optimizations still have a chance of coping with the millions of lines of Ruby code that large Rails apps from Shopify, Stripe, or GitLab have?
Here at Kent, we have a large group of researchers working on Programming Languages and Systems (PLAS), and within this group, we have a small team focusing on research on interpreters, compilation, and tooling to make programming easier.
Apr 17, 2018: A Typical Truffle Specialization Pitfall
Writing specializations is generally pretty straight forward, but there is at least one common pitfall. When designing specializations, we need to remind ourselves that type-based specializations are technically guards.
Next weekend starts one of the major conferences of the programming languages research community. The conference hosts many events including our Meta’16 workshop on Metaprogramming, SPLASH-I with research and industry talks, the Dynamic Languages Symposium, and the OOPSLA research track.
Jan 12, 2016: Type Hierarchies and Guards in Truffle Languages
Continuing a little bit with writing notes on Truffle and Graal, this one is based on my observations in SOMns and changes to its message dispatch mechanism. Specifically, I refactored the main message dispatch chain in SOMns. As in Self and Newspeak, all interactions with objects are message sends. Thus, field access and method invocation is essentially the same. This means that message sending is a key to good performance.
Step 5: Optimizing the Interpreter for Compilation
The year leading up to SPLASH has been pretty busy. Beside my own talks on Tracing vs. Partial Evaluation and Optimizing Communicating Event-Loop Languages with Truffle, there are going to be three other presentations on work I was involved in.