Reworking Memory Management in CRuby | Rails at Scale

Shopify sponsors and collaborates with academia to take Ruby to new heights. In this post, we give an overview of what we’ve built in collaboration with the Australian National UniversityThe Australian National University (ANU) and Shopify are collaborating on integrating the Memory Management Toolkit (MMTk) with Ruby. We are supporting the project and working alongside ANU researchers to explore how to build a next-generation garbage collector for Ruby. If you’re not familiar with MMTk, it offers a highly modular, VM-neutral framework for rapidly building high-performance garbage collectors. Once a language plugs into MMTk, it can leverage a wide range of built-in garbage collection algorithms, ranging from canonical collectors such as NoGC, Mark and Sweep, and Immix to more performant collectors such as Generational Immix and Sticky Immix. Many of these algorithms are considerably more sophisticated than the Mark and Sweep algorithm used in Ruby and have the potential to deliver significant performance gains.