This repository provides materials for a session that is part of the I2DS Tools for Data Science workshop run at the Hertie School, Berlin in November 2022. The student-run workshop is part of the course Introduction to Data Science taught by Simon Munzert at the Hertie School, Berlin, in Fall 2022.
This session will introduce you to Parallel Programming with the future package. Parallel programming is all about breaking down tasks into smaller tasks and executing them simultaneously. It’s a great tool for running large-scale projects quickly and accurately. Not all tasks are parallelizable though! The ideal parallelizable task would be one where little or no effort is needed to separate the problem into a number of parallel tasks.
The goals of this session are to (1) equip you with conceptual knowledge about what parallel programming is, (2) Introduce you to the futures package and give some examples, and (3) provide you with practice material as well as some further readings.
- Maria Fernanda Ortega
- Danial Riaz
- Parallel Programming tutorial on Githack
- A Future for R: A Comprehensive Overview
- Bryan Lewis introducing the foreach & future packages
The material in this repository is made available under the MIT license.
Maria Fernanda Ortega and Danial Riaz prepared the presentation slides, practice material and the recording.