Parallel Coding with Julia

Course Description

Julia is a high-level programming language well suited for scientific computing and data science. Just-in-time compilation, among other things, makes Julia really fast yet interactive. For heavy computations, Julia supports multi-threaded and multi-process parallelism, both naïvely and via a number of external packages. It also supports memory arrays distributed across multiple processes either on the same or different nodes. In this hands-on workshop, we will start with a quick review of Julia’s multi-threading features but will focus primarily on Distributed standard library and its large array of tools. We will demo parallelization using two problems: a slowly converging series and a Julia set. We will run examples on a multi-core laptop and an HPC cluster.

The lecture notes for this course are available on Alex’s website

Alex Razoumov
Alex Razoumov
Research Solutions Lead