Julia’s GC Reimagined: Flexibility and MMTk Integration
Diogo Netto, Luis Eduardo de Souza Amorim
Julia's mark-sweep GC poses some challenges to heap-intensive workloads like RelationalAI's cloud application, such as fragmentation and long pauses. The runtime's tight coupling with the GC prevents the adoption of new collectors. We introduced a GC interface to decouple the runtime from the GC, and integrated MMTk as one new alternative collector. MMTk provides cutting-edge GC algorithms, and allows community-driven innovation. We present preliminary results from using MMTk in RAI's workloads.
General
Main Room 1 (Main stage)