Title
EASYPAP: a Framework for Learning Parallel Programming
Abstract
This paper presents EASYPAP, an easy-to-use programming environment designed to help students to learn parallel programming. EASYPAP features a wide range of 2D computation kernels that the students are invited to parallelize using Pthreads, OpenMP, OpenCL or MPI. Execution of kernels can be interactively visualized, and powerful monitoring tools allow students to observe both the scheduling of computations and the assignment of 2D tiles to threads/processes. By focusing on algorithms and data distribution, students can experiment with diverse code variants and tune multiple parameters, resulting in richer problem exploration and faster progress towards efficient solutions. We present selected lab assignments which illustrate how EASYPAP improves the way students explore parallel programming.
Year
DOI
Venue
2020
10.1109/IPDPSW50202.2020.00059
2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
Keywords
DocType
ISSN
parallel programming,visualization,monitoring,education,OpenMP,MPI
Conference
2164-7062
ISBN
Citations 
PageRank 
978-1-7281-7457-0
0
0.34
References 
Authors
5
3
Name
Order
Citations
PageRank
Alice Lasserre100.34
Raymond Namyst2140583.04
Pierre-andré Wacrenier376636.69