Architecture-Specific Performance Optimization of Compute-Intensive FaaS Functions

Mohak Chadha, Anshul Jindal, Michael Gerndt

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

16 Scopus citations

Abstract

FaaS allows an application to be decomposed into functions that are executed on a FaaS platform. The FaaS platform is responsible for the resource provisioning of the functions. Recently, there is a growing trend towards the execution of compute-intensive FaaS functions that run for several seconds. However, due to the billing policies followed by commercial FaaS offerings, the execution of these functions can incur significantly higher costs. Moreover, due to the abstraction of underlying processor architectures on which the functions are executed, the performance optimization of these functions is challenging. As a result, most FaaS functions use pre-compiled libraries generic to x86-64 leading to performance degradation. In this paper, we examine the underlying processor architectures for Google Cloud Functions (GCF) and determine their prevalence across the 19 available GCF regions. We modify, adapt, and optimize three compute-intensive FaaS workloads written in Python using Numba, a JIT compiler based on LLVM, and present results wrt performance, memory consumption, and costs on GCF. Results from our experiments show that the optimization of FaaS functions can improve performance by 12.8x (geometric mean) and save costs by 73.4% on average for the three functions. Our results show that optimization of the FaaS functions for the specific architecture is very important. We achieved a maximum speedup of 1.79x by tuning the function especially for the instruction set of the underlying processor architecture.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE 14th International Conference on Cloud Computing, CLOUD 2021
EditorsClaudio Agostino Ardagna, Carl K. Chang, Ernesto Daminai, Rajiv Ranjan, Zhongjie Wang, Robert Ward, Jia Zhang, Wensheng Zhang
PublisherIEEE Computer Society
Pages478-483
Number of pages6
ISBN (Electronic)9781665400602
DOIs
StatePublished - Sep 2021
Event14th IEEE International Conference on Cloud Computing, CLOUD 2021 - Virtual, Online, United States
Duration: 5 Sep 202111 Sep 2021

Publication series

NameIEEE International Conference on Cloud Computing, CLOUD
Volume2021-September
ISSN (Print)2159-6182
ISSN (Electronic)2159-6190

Conference

Conference14th IEEE International Conference on Cloud Computing, CLOUD 2021
Country/TerritoryUnited States
CityVirtual, Online
Period5/09/2111/09/21

Keywords

  • Function-As-A-service (FaaS)
  • LLVM
  • Numba
  • cost
  • heterogeneity
  • performance optimization
  • serverless computing

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