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

Type of publication
Publication in Conference Proceedings/Workshop
Authors

Björn Forsberg, Maxim Mattheeuws, Andreas Kurth, Andrea Marongiu, Luca Benini. ACM. 2020.

Conference / Journal
The 21st ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems
Publisher
Association for Computing Machinery (ACM)
Year of publication
2020
Place of publication
New York, NY, USA.
Citation

Björn Forsberg, Maxim Mattheeuws, Andreas Kurth, Andrea Marongiu, Luca Benini. A Synergistic Approach to Predictable Compilation and Scheduling on Commodity Multi-Cores. 

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.

DOI
https://doi.org/10.1145/3372799.3394369