DAS: Dynamic Adaptive Scheduling for Energy-Efficient Heterogeneous SoCs
| Autor: | Ali Akoglu, Allen-Jasmin Farcas, Radu Marculescu, Umit Y. Ogras, Anish Krishnakumar, Sahil Hassan, A. Alper Goksoy |
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| Rok vydání: | 2022 |
| Předmět: |
FOS: Computer and information sciences
Speedup General Computer Science Computer science Workload Integrated circuit Parallel computing law.invention Scheduling (computing) Bridging (programming) Orders of magnitude (bit rate) Task (computing) Computer Science - Distributed Parallel and Cluster Computing Control and Systems Engineering law Hardware Architecture (cs.AR) Distributed Parallel and Cluster Computing (cs.DC) Computer Science - Hardware Architecture Efficient energy use |
| Zdroj: | IEEE Embedded Systems Letters. 14:51-54 |
| ISSN: | 1943-0671 1943-0663 |
| Popis: | Domain-specific systems-on-chip (DSSoCs) aim at bridging the gap between application-specific integrated circuits (ASICs) and general-purpose processors. Traditional operating system (OS) schedulers can undermine the potential of DSSoCs since their execution times can be orders of magnitude larger than the execution time of the task itself. To address this problem, we propose a dynamic adaptive scheduling (DAS) framework that combines the benefits of a fast (low-overhead) scheduler and a slow (sophisticated, high-performance but high-overhead) scheduler. Experiments with five real-world streaming applications show that DAS consistently outperforms both the fast and slow schedulers. For 40 different workloads, DAS achieves on average 1.29x speedup and 45% lower EDP compared to the sophisticated scheduler at low data rates and 1.28x speedup and 37% lower EDP than the fast scheduler when the workload complexity increases. 4 pages, 2 tables, 3 figures, 1 algorithm, Accepted for publication in IEEE Embedded Systems Letters |
| Databáze: | OpenAIRE |
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