Performance of Static and Dynamic Task Scheduling for Real-Time Engine Control System on Embedded Multicore Processor

Yoshitake Oki, Hiroki Mikami, Hikaru Nishida, Dan Umeda, Keiji Kimura*, Hironori Kasahara

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

Embedded multicore processors running hard real-time applications such as engine control programs require an appropriate scheduling routine to meet the real-time deadline constraints. These applications typically consist of various conditional branches which change the flow of the program and the task executions based on sensors inputs and vehicle status information. Conventionally, dynamic on-line scheduling was the only option for such applications that have unpredictable runtime behaviors. However, techniques for compilers and schedulers allow static off-line scheduling to be applied to engine control programs by utilizing execution profile feedback methods to feed task execution time information to the compiler. This paper is the first to compare dynamic scheduling and static scheduling schemes through the OSCAR multi-grain automatic parallelizing compiler and its overheads on an actual engine control program using an embedded multicore processor implemented on an FPGA. Evaluations and analysis on the engine control program indicate promising results for static scheduling, recording a 2.53 × speedup on 4 cores compared to single core execution. In contrast, speedup on dynamic scheduling with 4 cores was only 0.86x compared to sequential execution. The evaluation shows that static scheduling with execution profile feedback methods is an effective tool for real hard-real time control applications that have task granularity that is too fine for dynamic scheduling on embedded multicore processors.

Original languageEnglish
Title of host publicationLanguages and Compilers for Parallel Computing - 32nd International Workshop, LCPC 2019, Revised Selected Papers
EditorsSantosh Pande, Vivek Sarkar
PublisherSpringer Science and Business Media Deutschland GmbH
Pages1-14
Number of pages14
ISBN (Print)9783030727888
DOIs
Publication statusPublished - 2021
Event32nd International Workshop on Languages and Compilers for Parallel Computing, LCPC 2019 - Atlanta, United States
Duration: 2019 Oct 222019 Oct 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11998 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference32nd International Workshop on Languages and Compilers for Parallel Computing, LCPC 2019
Country/TerritoryUnited States
CityAtlanta
Period19/10/2219/10/24

Keywords

  • Dynamic scheduling
  • Hard real-time control systems
  • Multicore
  • Parallelizing compiler
  • Performance comparison
  • Scheduling overhead
  • Static scheduling

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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