Characterizing Loop Acceleration in Heterogeneous Computing

Saman Biookaghazadeh, Fengbo Ren, Ming Zhao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Computation intensive applications usually consist of multiple nested or flattened loops. These loops are the main building blocks of the applications and embody a specific type of execution pattern. In order to reduce the running time of the loops, developers need to analyze the loops in the code and try to parallelize them on hardware accelerators, such as GPUs, TPUs, and FPGAs, which are increasingly available in the cloud. Unfortunately, the lack of understanding of loop characteristics and the ability of hardware accelerators in handling these types of loops prevents developers from choosing the right platform to develop their applications in the cloud. Also, developing and optimizing code for a specific accelerator is a time-consuming effort. To address these issues, this paper studies the effectiveness of different processors in accelerating common patterns of loops. It identifies five important types of loops that commonly exist in real-world applications, and presents Loopy, the implementations of these loops optimized for different architectures. Using Loopy, the paper also evaluates different hardware in accelerating the loop patterns. The result reveals the architectural differences among different accelerators with regard to different loop patterns. It also provides insights for the developers to choose the right accelerators for their applications. The current version of Loopy supports both FPGAs and GPUs, which are the most versatile and available accelerators.

Original languageEnglish (US)
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
Pages445-455
Number of pages11
ISBN (Electronic)9781665400602
DOIs
StatePublished - Sep 2021
Externally publishedYes
Event14th IEEE International Conference on Cloud Computing, CLOUD 2021 - Virtual, Online, United States
Duration: Sep 5 2021Sep 11 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
Period9/5/219/11/21

Keywords

  • FPGA
  • GPU
  • Heterogeneous computing
  • Loop characterization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Software

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