HEXO: Offloading HPC Compute-Intensive Workloads on Low-Cost, Low-Power Embedded Systems

Pierre Olivier, A. K. M. Fazla Mehrab, Stefan Lankes, Mohamed Lamine Karaoui, Robert Lyerly, Binoy Ravindran

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

OS-capable embedded systems exhibiting a very low power consumption are available at an extremely low price point. It makes them highly compelling in a datacenter context. In this paper we show that sharing long-running, compute-intensive datacenter HPC workloads between a server machine and one or a few connected embedded boards of negligible cost and power consumption can bring significant benefits in terms of consolidation. Our approach, named Heterogeneous EXecution Offloading (HEXO), selectively offloads Virtual Machines (VMs) from server class machines to embedded boards. Our design tackles several challenges. We address the Instruction Set Architecture (ISA) difference between typical servers (x86) and embedded systems (ARM) through hypervisor and guest OS-level support for heterogeneous-ISA runtime VM migration. We cope with the low amount of resources in embedded systems by using lightweight VMs: unikernels. VMs are offloaded based on an estimation of the slowdown expected from running on a given board. We build a prototype of HEXO and demonstrate significant increase in throughput (up to 67%) and energy efficiency (up to 56%) over a set of macro-benchmarks running datacenter compute-intensive jobs.
Original languageEnglish
Title of host publicationHPDC '19: Proceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing
PublisherAssociation for Computing Machinery
Pages85-96
ISBN (Print)978-1-4503-6670-0
DOIs
Publication statusPublished - 1 Jun 2019
EventHPDC '19: Proceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing - Phoenix, United States
Duration: 22 Jun 201929 Jun 2019

Conference

ConferenceHPDC '19: Proceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing
Country/TerritoryUnited States
CityPhoenix
Period22/06/1929/06/19

Fingerprint

Dive into the research topics of 'HEXO: Offloading HPC Compute-Intensive Workloads on Low-Cost, Low-Power Embedded Systems'. Together they form a unique fingerprint.

Cite this