A Visual Analytics System for Optimizing Communications in Massively Parallel Applications

Takanori Fujiwara, Preeti Malakar, Khairi Reda, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Current and future supercomputers have tens of thousands of compute nodes interconnected with high-dimensional networks and complex network topologies for improved performance. Application developers are required to write scalable parallel programs in order to achieve high throughput on these machines. Application performance is largely determined by efficient inter-process communication. A common way to analyze and optimize performance is through profiling parallel codes to identify communication bottlenecks. However, understanding gigabytes of profiled at a is not a trivial task. In this paper, we present a visual analytics system for identifying the scalability bottlenecks and improving the communication efficiency of massively parallel applications. Visualization methods used in this system are designed to comprehend large-scale and varied communication patterns on thousands of nodes in complex networks such as the 5D torus and the dragonfly. We also present efficient rerouting and remapping algorithms that can be coupled with our interactive visual analytics design for performance optimization. We demonstrate the utility of our system with several case studies using three benchmark applications on two leading supercomputers. The mapping suggestion from our system led to 38% improvement in hop-bytes for Mini AMR application on 4,096 MPI processes.

Original languageEnglish (US)
Title of host publication2017 IEEE Conference on Visual Analytics Science and Technology, VAST 2017 - Proceedings
EditorsTobias Schreck, Brian Fisher, Shixia Liu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages59-70
Number of pages12
ISBN (Electronic)9781538631638
DOIs
StatePublished - Dec 21 2018
Event2017 IEEE Conference on Visual Analytics Science and Technology, VAST 2017 - Phoenix, United States
Duration: Oct 1 2017Oct 6 2017

Other

Other2017 IEEE Conference on Visual Analytics Science and Technology, VAST 2017
CountryUnited States
CityPhoenix
Period10/1/1710/6/17

Keywords

  • Communication visualization
  • Parallel communications
  • Performance analysis
  • Supercomputing
  • Visual analytics

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Information Systems
  • Media Technology

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