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Introduction to parallel processing, using R

Contributors: Timothée Bacri University of Bergen, Norway.

Correspondence to: [email protected]

This repository contains the code used for the presentation on December 6 2022 of the self selected topic of Timothée Bacri, during his PhD at the University of Bergen. The presentation was held physically, and the slides and talk were recorded.

The video of the presentation can be found at https://youtu.be/3wbqr1D04Bw, and the slides can be found on the pdf document code and slides/fast_computing.pdf.

Building / compiling the PDF slides

Before compiling, monitoring_progress_bar.zip must be unzipped. The video was too heavy to upload on GitHub, so I had to compress it.

A PDF for the slides can be compiled with the knitr and rmarkdown packages using R from the file code and slides/fast_computing.Rmd file. It is advised to open the file code and slides/Self-selected topic.Rproj to set the working directory automatically.

The code on the slide Race condition / concurrent writing is cached because otherwise, it intentionally causes some errors and the user must click OK on the windows that pops up. Remove cache=TRUE or change it to cache=FALSE to compile these parts.

You can click on the knit button on RStudio. Alternatively, you can execute the following R command to compile the .Rmd file

rmarkdown::render('fast_computing.Rmd',  encoding = 'UTF-8');

Author

Timothée Bacri - timothee-bacri

License

The content of this project itself is licensed under the MIT License, and the underlying source code is licensed under the GNU GPLv3 License.

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