Designing an Exascale Interconnect using Multi-objective Optimization
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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.
for parallel applications.
Bibliographical metadata
Original language | English |
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Title of host publication | IEEE Congress on Evolutionary Computation 2017 |
Publisher | IEEE |
DOIs | |
Publication status | Published - 2017 |
Event | 2017 IEEE Congress on Evolutionary Computation - San Sebastian, Spain Event duration: 5 Jun 2017 → 8 Jun 2017 http://www.cec2017.org/ |
Conference
Conference | 2017 IEEE Congress on Evolutionary Computation |
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Abbreviated title | CEC 2017 |
Country | Spain |
City | San Sebastian |
Period | 5/06/17 → 8/06/17 |
Internet address |