Research - Introduction to parallel computing with Python, Julia, and R

Objectives

Target audience

Any PhD students, post-docs, researchers of UNIL and CHUV who develop some codes for the clusters and want to learn the basis of parallel computing in order to improve performance of their codes.

Content

In a first presentation, the main principles of parallel computing are introduced. Thanks to few examples, different ways of parallelising a program are presented (data decomposition, functional decomposition, …).

Then a second presentation will focus on Python and the specificities of the language regarding parallel computing. In particular the following libraries will be presented: Numpy, Numba, CuPy, Dask.

A third presentation will focus on Julia, especially on it's characteristics that make it suitable for high performance computing. This will cover mainly the native Julia libraries dedicated to various forms of parallelism.

Finally, the last presentation will focus on R and it's simple mechanisms and external libraries to benefit from multi-core architectures.

At the end of the course, the participants are expected to:

Length

2 days

Organization

On a quarterly basis

Location

To be defined

Prerequisites

IMPORTANT: Please register using your UNIL email address!


Course dates and registration


Revision #4
Created 30 September 2022 11:18:48 by Emmanuel Jeanvoine
Updated 15 November 2023 13:18:27 by Emmanuel Jeanvoine