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Julia for High-Performance Computing - JuliaCon 2022

Offered By: The Julia Programming Language via YouTube

Tags

Julia Courses CUDA Courses Scientific Computing Courses Parallel Computing Courses High Performance Computing Courses MPI Courses GPU Computing Courses Scalability Courses Supercomputing Courses

Course Description

Overview

Dive into the world of high-performance computing (HPC) with Julia in this comprehensive 2-hour 20-minute minisymposium from JuliaCon 2022. Explore the current state of Julia for HPC through eight informative talks covering topics such as scalable deployments, compute accelerator support, user support, and HPC applications. Learn about the scalability of Julia/GPU stack, updates on CUDA.jl and AMDGPU.jl, and experiences supporting Julia users at supercomputing centers. Gain insights into running Julia code in parallel with MPI and its applications in geoscience. Engage in Q&A sessions and discussions to network with colleagues and share experiences in Julia HPC. Suitable for current and prospective Julia practitioners from industry, academia, and government institutions interested in leveraging Julia's capabilities for supercomputing and addressing challenges in the era of exascale computing.

Syllabus

: William F Godoy (ORNL) & Michael Schlottke-Lakemper (U Stuttgart/HLRS): Julia for High-Performance Computing
.
: Samuel Omlin (CSCS): Scalability of the Julia/GPU stack
.
: Simon Byrne (Caltech/CliMA): MPI.jl
.
: Q&A
.
: Tim Besard (Julia Computing): CUDA.jl: Update on new features and developments
.
: Julian Samaroo (MIT): AMDGPU.jl: State of development and roadmap to the future
.
: Q&A
.
: Albert Reuther (MIT): Supporting Julia Users at MIT LL Supercomputing Center
.
: Johannes Blaschke (NERSC): Supporting Julia users on NERSC’s “Cori” and “Perlmutter” systems
.
: Q&A
.
: Michael Schlottke-Lakemper (U Stuttgart/HLRS): Running Julia code in parallel with MPI: Lessons learned
.
: Ludovic Räss (ETH Zurich): Julia and GPU-HPC for geoscience applications
.
: Q&A, Discussion & Wrap up
.


Taught by

The Julia Programming Language

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