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Intelligent colocation of HPC workloads

Author
Vieira, F.; Petrucci, V.; Nishtala, R.; Carpenter, P.; Mossé, D.
Type of activity
Journal article
Journal
Journal of parallel and distributed computing
Date of publication
2021-05
Volume
151
First page
125
Last page
137
DOI
10.1016/j.jpdc.2021.02.010
Project funding
Arquitectura de Computadors d'Altes Prestacions (ACAP)
High performance computing VII
Models de Programacio i Entorns d'eXecució PARal.lels
Repository
http://hdl.handle.net/2117/340333 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S0743731521000319 Open in new window
Abstract
Many server applications suffer from a bottleneck in the shared caches, instruction execution units, I/O or memory bandwidth, even though the remaining resources may be underutilized. It is hard for developers and runtime systems to ensure that all critical resources are fully exploited by a single application, so an attractive technique for increasing server system utilization is to colocate multiple applications on the same server. When applications share critical resources, however, contentio...
Citation
Vieira, F. [et al.]. Intelligent colocation of HPC workloads. "Journal of parallel and distributed computing", Maig 2021, vol. 151, p. 125-137.
Keywords
Colocation, Machine learning, Performance counters, Performance degradation, Resource manager

Participants

  • Vieira Zacarias, Felippe  (author)
  • Petrucci, Vinicius  (author)
  • Nishtala, Rajiv  (author)
  • Carpenter, Paul Matthew  (author)
  • Mossé, Daniel  (author)