research-article

A Synergistic Approach to Predictable Compilation and Scheduling on Commodity Multi-Cores

Authors:

Björn Forsberg,

Maxim Mattheeuws,

Andrea Marongiu,

Luca BeniniAuthors Info & Claims

LCTES '20: The 21st ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems

Pages 108 - 118

https://doi.org/10.1145/3372799.3394369

Published: 16 June 2020 Publication History

Abstract

Commodity multi-cores are still uncommon in real-time systems, as resource sharing complicates traditional timing analysis. The Predictable Execution Model (PREM) tackles this issue in software, through scheduling and code refactoring. State-of-the-art PREM compilers analyze tasks one at a time, maximizing task-level performance metrics, and are oblivious to system-level scheduling effects (e.g. memory serialization when tasks are co-scheduled). We propose a solution that allows PREM code generation and system scheduling to interact, based on a genetic algorithm aimed at maximizing overall system performance. Experiments on commodity hardware show that the performance increase can be as high as 31% compared to standard PREM code generation, without negatively impacting the predictability guarantees.

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Cited By

Dudzik KKirschner MBetancourt VBecker J(2024)Work in Progress: Predictable Execution of Isolated Real-Time Tasks on Multicore Systems Using the LET Paradigm2024 IEEE 30th Real-Time and Embedded Technology and Applications Symposium (RTAS)10.1109/RTAS61025.2024.00038(386-389)Online publication date: 13-May-2024
https://doi.org/10.1109/RTAS61025.2024.00038
Dave SNowatzki TShrivastava AAamodt TSwift MJerger N(2023)Explainable-DSE: An Agile and Explainable Exploration of Efficient HW/SW Codesigns of Deep Learning Accelerators Using Bottleneck AnalysisProceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 410.1145/3623278.3624772(87-107)Online publication date: 25-Mar-2023
https://dl.acm.org/doi/10.1145/3623278.3624772
Park SLee JKim H(2022)Software-Level Memory Regulation to Reduce Execution Time Variation on Multicore Real-Time SystemsIEEE Access10.1109/ACCESS.2022.320370210(93799-93811)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3203702
Show More Cited By

Index Terms

A Synergistic Approach to Predictable Compilation and Scheduling on Commodity Multi-Cores
1. Computer systems organization
  1. Real-time systems

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cover image ACM Conferences

LCTES '20: The 21st ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems

June 2020

163 pages

ISBN:9781450370943

DOI:10.1145/3372799

General Chair:
Jingling Xue
UNSW Sydney, Australia
,
Program Chair:
Changhee Jung
Purdue University, USA

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 16 June 2020

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LCTES '20: 21st ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems

June 16, 2020

London, United Kingdom

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Cited By

Dudzik KKirschner MBetancourt VBecker J(2024)Work in Progress: Predictable Execution of Isolated Real-Time Tasks on Multicore Systems Using the LET Paradigm2024 IEEE 30th Real-Time and Embedded Technology and Applications Symposium (RTAS)10.1109/RTAS61025.2024.00038(386-389)Online publication date: 13-May-2024
https://doi.org/10.1109/RTAS61025.2024.00038
Dave SNowatzki TShrivastava AAamodt TSwift MJerger N(2023)Explainable-DSE: An Agile and Explainable Exploration of Efficient HW/SW Codesigns of Deep Learning Accelerators Using Bottleneck AnalysisProceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 410.1145/3623278.3624772(87-107)Online publication date: 25-Mar-2023
https://dl.acm.org/doi/10.1145/3623278.3624772
Park SLee JKim H(2022)Software-Level Memory Regulation to Reduce Execution Time Variation on Multicore Real-Time SystemsIEEE Access10.1109/ACCESS.2022.320370210(93799-93811)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3203702
Schuh MMaiza CGoossens JRaymond Pde Dinechin B(2020)A study of predictable execution models implementation for industrial data-flow applications on a multi-core platform with shared banked memory2020 IEEE Real-Time Systems Symposium (RTSS)10.1109/RTSS49844.2020.00034(283-295)Online publication date: Dec-2020
https://doi.org/10.1109/RTSS49844.2020.00034

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