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This content will become publicly available on June 4, 2026

Title: Visualizing MPI Collective Communication
Communication collectives are at the heart of distributed-memory parallel algorithms and the Message Passing Interface. In parallel computing courses, students can learn about collectives not only to utilize them as building blocks to implement other algorithms, but also as exemplars for designing and analyzing efficient algorithms. We develop a visualization tool to help students understand different algorithms for collective operations as well as evaluate and analyze the algorithms' efficiencies. Our implementation is written in C++ with OpenMP and uses the Thread Safe Graphics Library. We simulate distributed-memory message passing to implement the algorithms, and the threads concurrently illustrate their local memories and message passing using a shared canvas. Our tool includes visualizations of different algorithms for Scatter, Gather, ReduceScatter, AllGather, Broadcast, Reduce, AllReduce, and AlltoAll.  more » « less
Award ID(s):
2106920 1942892
PAR ID:
10618223
Author(s) / Creator(s):
; ;
Publisher / Repository:
IEEE Computer Society
Date Published:
Format(s):
Medium: X
Location:
Milan, Italy
Sponsoring Org:
National Science Foundation
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