2025 Julia For Science Part 2: HPC

2025 Julia for HPC

Thursday, June 26, 2025 | 1:00–4:00 PM EDT 
Location: Zoom
Contact: Suzanne Parete-Koon, [email protected]

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, SNS, HFIR, NERSC, and ALCF resources are especially encouraged to attend.

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

Training Modules:

• Brief introduction to 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
• • 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 Jupyter and Pluto.jl notebooks

Compute Resources:

Participants will need access to HPC systems for this session. Please apply  for access to OLCF’s Odo training system (similar architecture to Frontier). To do this apply for project TRN036. This guide https://docs.olcf.ornl.gov/systems/odo_user_guide.html#obtaining-access-to-odo will show you how. Note: OLCF account applications must be received by June 19, 2025.

Training Materials:

1. Julia v1.11 release candidate: https://julialang.org/downloads/

2. HPC Gray-Scott example:

https://github.com/JuliaORNL/GrayScott.jl

https://juliaornl.github.io/TutorialJuliaHPC/

3. JACC:

https://github.com/JuliaORNL/JACC.jl

https://github.com/JuliaORNL/JACC-applications

4. Recommended reading:
Julia’s Value Proposition for Better Scientific Software

.