Parallel programming: R & Python applications
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| Název: | Parallel programming: R & Python applications |
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| Autoři: | Ammar, Ammar, orcid:0000-0002-8399- |
| Informace o vydavateli: | Zenodo |
| Rok vydání: | 2023 |
| Sbírka: | Zenodo |
| Témata: | parallel computing, thread, CPU, core, OpenMP, posix, process, fork, concurrent |
| Popis: | This presentation is part of the "Parallel Programming" module in the course of "MSB1015 - Scientific Programming" (Maastricht University). The lecture slides aims to introduce parallel programming to master students, clarify and explain related concepts and shed a light on different parallel programming paradigms and their implementations in two programming languages: R & Python. Parallel (Computing) Sequential vs. Parallel Concurrent vs. Parallel Why parallel computing? Socket vs. CPU vs. Core vs. Thread How to parallelize? Levels of Parallelism Parallel Programming Models Threads (Posix) Shared Memory (OpenMP) fork() on Unix-like Systems Message Passing (MPI) Hybrid (MPI + Posix) Forked Process vs. Threaded Process Issues When Parallelizing Memory and parallel programs Parallel computing in R foreach package parallel/doParallel packages Structure of a typical parallel processing code Parallel processing in {caret} mclapply() R packages using parallel processing Parallel computing in Python How many maximum parallel processes can you run? Synchronous and Asynchronous execution How to Parallelize a Pandas DataFrame? Parallel processing in {paratext} package Parallel processing in {Scikit-learn} package Python packages using parallel processing |
| Druh dokumentu: | text |
| Jazyk: | English |
| Relation: | https://zenodo.org/records/12601171; oai:zenodo.org:12601171; https://doi.org/10.5281/zenodo.12601171 |
| DOI: | 10.5281/zenodo.12601171 |
| Dostupnost: | https://doi.org/10.5281/zenodo.12601171 https://zenodo.org/records/12601171 |
| Rights: | Creative Commons Attribution Share Alike 4.0 International ; cc-by-sa-4.0 ; https://creativecommons.org/licenses/by-sa/4.0/legalcode |
| Přístupové číslo: | edsbas.9522D663 |
| Databáze: | BASE |
Nájsť tento článok vo Web of Science | Abstrakt: | This presentation is part of the "Parallel Programming" module in the course of "MSB1015 - Scientific Programming" (Maastricht University). The lecture slides aims to introduce parallel programming to master students, clarify and explain related concepts and shed a light on different parallel programming paradigms and their implementations in two programming languages: R & Python. Parallel (Computing) Sequential vs. Parallel Concurrent vs. Parallel Why parallel computing? Socket vs. CPU vs. Core vs. Thread How to parallelize? Levels of Parallelism Parallel Programming Models Threads (Posix) Shared Memory (OpenMP) fork() on Unix-like Systems Message Passing (MPI) Hybrid (MPI + Posix) Forked Process vs. Threaded Process Issues When Parallelizing Memory and parallel programs Parallel computing in R foreach package parallel/doParallel packages Structure of a typical parallel processing code Parallel processing in {caret} mclapply() R packages using parallel processing Parallel computing in Python How many maximum parallel processes can you run? Synchronous and Asynchronous execution How to Parallelize a Pandas DataFrame? Parallel processing in {paratext} package Parallel processing in {Scikit-learn} package Python packages using parallel processing |
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| DOI: | 10.5281/zenodo.12601171 |