JuliaCon 2025

Rabab Alomairy

I am a postdoctoral researcher at the MIT JuliaLab and an HPC enthusiast who loves solving complex problems by thinking in parallel. My research intersects High-Performance Computing (HPC) and Artificial Intelligence (AI), exploring how advanced computational techniques can optimize AI algorithms for increased efficiency and effectiveness. I was honored as one of the Rising Stars in Computational and Data Sciences by U.S. Department of Energy. My collaborations extend internationally, including with the Innovative Computing Lab at the University of Tennessee and MINES ParisTech. In Summer 2021, I was a visiting scholar at the Innovative Computing Lab, where I contributed to a milestone of the Software for Linear Algebra Targeting Exascale (SLATE) project , a joint initiative of the U.S. Department of Energy’s Office of Science and the National Nuclear Security Administration (NNSA).


Sessions

07-22
09:00
180min
Hands-on with Julia for HPC on GPUs and CPUs
Ludovic Räss, Samuel Omlin, Johannes Blaschke, Rabab Alomairy

Julia offers the best of both worlds: high-level expressiveness combined with low-level performance, allowing developers to leverage modern hardware accelerators without needing expertise in hardware-specific languages. This workshop demonstrates how Julia makes high-performance computing (HPC) accessible by covering key topics such as resource configuration, distributed computing, CPU and GPU code optimization, and scalable workflows.

General
Main Room 3
07-23
16:00
10min
Automated algorithm selection discovery via LLMs
Rushil Shah, Emmanuel Lujan, Rabab Alomairy

The DARPA-MIT SmartSolve project tackles the challenge of dynamically selecting optimal algorithms and architectures through an automated discovery framework. As part of this effort, we present advances on optimizing algorithm and data structure choices tailored to linear algebra. Contributions include automated benchmarking across diverse matrix patterns, database-driven selection via Pareto analysis, and exploring large language models for automatic heuristic generation.

Julia for High-Performance Computing
Main Room 4
07-25
11:00
60min
Dagger.jl Birds of a Feather
Julian P Samaroo, Felipe Tomé, Rabab Alomairy

Round-table discussion of everything about Dagger.jl. Success or failure stories, ideas for new features, discussion of existing bugs or missing documentation, and more!

General
Main Room 4