07-28, 19:50–20:00 (UTC), Purple
Catwalk.jl can speed up long-running Julia processes by minimizing the overhead of dynamic dispatch. It is a JIT compiler that continuosly re-optimizes dispatch code based on data collected at runtime.
It features a low overhead statistical profiler and a tunable cost model to drive recompilation decisions.
I will talk about its target use case, performance characteristics, some implementation details and its connections to the Julia ecosystem.
Working on a sparse-AI actor runtime, researching decentralized algorithms, playing with runtime code generation.