PhD student at the MIT JuliaLab, HPC enthusiast.
Static walks through dynamic programs -- a conversation with type-inference.
Efficient performance engineering for Julia programs heavily relies on understanding the result of type-inference on your program, this talk will introduce a tool to have a conversation with type-inference.
Concolic Fuzzing -- Or how to run a theorem prover on your Julia code
Concolic testing is a technique that uses concrete execution to create a symbolic representation of a program, which can be used to prove properties of programs or do provable exhaustive fuzzing.
Cassette and company -- Dynamic compiler passes
Chat about Cassette, Vinyl, IRTools, and Aborist. Things that rewrite the code at compile-time, based on context.
A discussion of the Julia GPU ecosystem
Performant parallelism with productivity and portability.
This BoF will be a forum to discuss the state of the state around performant parallelism for distributed memory programming in Julia. Performance, parallelism, productivity and portability are four P's of distributed memory parallelism that over the last 30 years have proved hard to satisfy simultaneously in a general solution. The goal of this BoF is discussion and exploration of approaches for providing performant distributed memory parallelism in Julia in ways that are portable and that reflect the productivity vision of Julia. The format will consist of a series of presentations and a discussion/Q&A section. It will look both within Julia and across other languages at the last 30 years of efforts in this space. The motivation for the BoF is that meeting the four P's well remains an unsolved problem. For now projects that seek all of performance, parallelism at scale, portability and productivity typically have to make compromises in one or more of these areas. The hoped for outcome is some shared momentum and sharing of ideas for developing Julian approaches that lessen (or eliminate) the need to compromise in any of the four P's in the future.