Yan Guimarães
Yan Guimarães is a Software Engineering student at the University of Brasília (UnB) researching high-performance computing and distributed task scheduling in the Julia Language. He focuses on developing an MPI-based backend for Dagger.jl, a runtime system that uses DAG-based scheduling to handle distributed workloads automatically. He integrates MPI into Dagger's scheduler with one line of code, which enables MPI-aware task placement while hiding communication complexity. He evaluates performance on the Aurora exascale supercomputer and AWS, using parallel Cholesky decomposition benchmarks, showing competitive results on HPC interconnects. This research, developed through Google Summer of Code 2025.
Session
While Julia’s Dagger.jl provides a productive framework for task-based parallelism using Directed Acyclic Graphs (DAGs), its default reliance on TCP-based Distributed.jl limits performance on low-latency HPC interconnects. To bridge this gap, we developed MPIAcceleration, a strategic extension that replaces standard transport with an MPI-aware backend. By leveraging MPI.jl and non-blocking communication, we enable Dagger to use specialized hardware such as InfiniBand and Slingshot while maintaining a simple, high-level API.