2026 Julia For Science

Julia for HPC Pt. 1

The Oak Ridge Leadership Computing Facility (OLCF), in conjunction with the Oak Ridge National Laboratory Computer Science and Mathematics Division (CSMD), will host Julia for Science, a 3-hour tutorial introducing the Julia programming language and its ecosystem for computation and data analysis. The session will include hands-on examples using Jupyter Notebooks, project setup, and an introduction to parallel CPU/GPU code using Julia and JACC.jl — a performance-portable library developed at ORNL that recently reached a stable v1.0 release (https://github.com/JuliaGPU/JACC.jl).

Julia’s value proposition is to provide a unifying, productive, and performant scientific programming language built on top of LLVM. Scientific users who need to perform computational analysis and run parallel CPU/GPU kernels are especially encouraged to attend.

Who Should Attend: Anyone who wants a hands-on introduction to Julia and parallel programming for scientific computing.

Presenters: William Godoy, Philip Fackler, and Pedro Valero-Lara (ORNL)

Attendees will learn about:

1. Language basics: installation, syntax, code organization, data types, and the rich mathematical standard library
2. Ecosystem: packaging, testing, CI, metaprogramming, tooling, REPL, and Julia 1.12 or 1.13
3. Parallel programming models for CPU and GPUs (NVIDIA, AMD, Apple, and Intel) using JACC.jl

Code Repositories:

• https://github.com/ornl-training/julia-basics
• https://github.com/JuliaORNL/JACC.jl

Compute Resources: Access to OLCF computational resources is not required. Training accounts will be provided through Odo, with account details emailed after registration.

Registration: Registration is limited to 200 participants. Joining links will be emailed after registration.

Julia for Science Pt. 2

The Oak Ridge Leadership Computing Facility (OLCF), in conjunction with the Oak Ridge National Laboratory Computer Science and Mathematics Division (CSMD), will host Julia for HPC, a hands-on tutorial introducing participants to using Julia for high-performance computing (HPC) applications.

This session will explore advanced topics relevant to HPC, including GPU programming and performance-focused Julia packages.

Who Should Attend:
This session is open to all who want to learn more about using Julia for HPC and scientific computing. Users of OLCF or people interested in portable internode+CPU/GPU parallel programming are especially encouraged to attend.

Presenters:
William Godoy, Philip Fackler and Pedro Valero-Lara (ORNL)

Training Modules:

• Brief recap of session-I on Julia and the HPC ecosystem
• JACC.jl for performance portable science codes: XSBench.jl, miniBUDE, Hartree-Fock, LULESH
• Developing and running a Julia HPC diffusion-reaction app: Gray-Scott on the Odo Cluster
  • Simulation on CPU/GPU using JACC.jl
  • Communication via MPI.jl
  • Parallel I/O with ADIOS2.jl
  • Performance tips
  • Package interactions and configuration with a HPC system
• Interactive computing with Notebooks on OLCF JupyterHub