Peachy parallel assignments (EduHPC 2020)

Henri Casanova, Rafael Ferreira Da Silva, Arturo Gonzalez-Escribano, William Koch, Yuri Torres, David P. Bunde

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Peachy Parallel Assignments are high-quality assignments for teaching parallel and distributed computing. They are selected competitively for presentation at the Edu∗ workshops. All of the assignments have been successfully used in class and they are selected based on the their ease of adoption by other instructors and for being cool and inspirational to students. This paper presents a paper-and-pencil assignment asking students to analyze the performance of different system configurations and an assignment in which students parallelize a simulation of the evolution of simple living organisms.

Original languageEnglish
Title of host publicationProceedings of EduHPC 2020
Subtitle of host publicationWorkshop on Education for High Performance Computing, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages53-58
Number of pages6
ISBN (Electronic)9781665422963
DOIs
StatePublished - Nov 2020
Event2020 IEEE/ACM Workshop on Education for High Performance Computing, EduHPC 2020 - Virtual, Atlanta, United States
Duration: Nov 13 2020Nov 13 2020

Publication series

NameProceedings of EduHPC 2020: Workshop on Education for High Performance Computing, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis

Conference

Conference2020 IEEE/ACM Workshop on Education for High Performance Computing, EduHPC 2020
Country/TerritoryUnited States
CityVirtual, Atlanta
Period11/13/2011/13/20

Keywords

  • Curriculum Development
  • GPGPU
  • High-Performance Computing education
  • MPI
  • OpenMP
  • Parallel computing education
  • Parallel programming
  • Parallel simulation
  • Peachy Parallel Assignments
  • Performance analysis

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