Designing an Exascale Interconnect using Multi-objective Optimization

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

  • External authors:
  • Jose Pascual Saiz
  • Joshua Lant
  • Andrew Attwood
  • Caroline Concatto
  • Javier Navaridas
  • Mikel Luján

Abstract

Exascale performance will be delivered by systems composed of millions of interconnected computing cores. The way these computing elements are connected with each other (network topology) has a strong impact on many performance characteristics. In this work we propose a multi-objective optimizationbased framework to explore possible network topologies to be implemented in the EU-funded ExaNeSt project. The modular design of this system’s interconnect provides great flexibility to design topologies optimized for specific performance targets such as communications locality, fault tolerance or energyconsumption. The generation procedure of the topologies is formulated as a three-objective optimization problem (minimizing some topological characteristics) where solutions are searched using evolutionary techniques. The analysis of the results, carried out using simulation, shows that the topologies meet the required performance objectives. In addition, a comparison with a wellknown topology reveals that the generated solutions can provide better topological characteristics and also higher performance
for parallel applications.

Bibliographical metadata

Original languageEnglish
Title of host publicationIEEE Congress on Evolutionary Computation 2017
PublisherInstitute of Electrical and Electronics Engineers
DOIs
StatePublished - 2017
Event2017 IEEE Congress on Evolutionary Computation - San Sebastian, Spain

Conference

Conference2017 IEEE Congress on Evolutionary Computation
Abbreviated titleCEC 2017
CountrySpain
CitySan Sebastian
Period5/06/178/06/17
Internet address