This research paper prepared by ETH Zürich was published in the journal “Proceedings of the ACM on Measurement and Analysis of Computing Systems“.
Abstract
Cloud computing represents an appealing opportunity for cost-effective deployment of HPC workloads on the best-fitting hardware. However, although cloud and on-premise HPC systems offer similar computational resources, their network architecture and performance may differ significantly. For example, these systems use fundamentally different network transport and routing protocols, which may introduce network noise that can eventually limit the application scaling. This work analyzes network performance, scalability, and cost of running HPC workloads on cloud systems. First, we consider latency, bandwidth, and collective communication patterns in detailed small-scale measurements, and then we simulate network performance at a larger scale. We validate our approach on four popular cloud providers and three on-premise HPC systems, showing that network (and also OS) noise can significantly impact performance and cost both at small and large scale.
Authors
Daniele De Sensi, Tiziano De Matteis, Konstantin Taranov,
Salvatore Di Girolamo, Tobias Rahn, Torsten Hoefler (ETH Zürich).
DOI: 10.1145/3570609