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Energy-aware task mapping and scheduling for reliable embedded computing systems

Energy-aware task mapping and scheduling for reliable embedded computing systems
Energy-aware task mapping and scheduling for reliable embedded computing systems
Task mapping and scheduling are critical in minimizing energy consumption while satisfying the performance requirement of applications enabled on heterogeneous multiprocessor systems. An area of growing concern for modern multiprocessor systems is the increase in the failure probability of one or more component processors. This is especially critical for applications where performance degradation (e.g., throughput) directly impacts the quality of service requirement. This article proposes a design-time (offline) multi-criterion optimization technique for application mapping on embedded multiprocessor systems to minimize energy consumption for all processor fault-scenarios. A scheduling technique is then proposed based on self-timed execution to minimize the schedule storage and construction overhead at runtime. Experiments conducted with synthetic and real applications from streaming and nonstreaming domains on heterogeneous MPSoCs demonstrate that the proposed technique minimizes energy consumption by 22% and design space exploration time by 100x, while satisfying the throughput requirement for all processor fault-scenarios. For scalable throughput applications, the proposed technique achieves 30% better throughput per unit energy, compared to the existing techniques. Additionally, the self-timed execution-based scheduling technique minimizes schedule construction time by 95% and storage overhead by 92%.
Das, Anup K.
2a0d6cea-309b-4053-a62e-234807f89306
Kumar, Akash
3e1191e9-dc51-4f9e-8e47-80524db219dc
Veeravalli, Bharadwaj
b836c94d-baad-450a-826b-84021f56db49
Das, Anup K.
2a0d6cea-309b-4053-a62e-234807f89306
Kumar, Akash
3e1191e9-dc51-4f9e-8e47-80524db219dc
Veeravalli, Bharadwaj
b836c94d-baad-450a-826b-84021f56db49

Das, Anup K., Kumar, Akash and Veeravalli, Bharadwaj (2014) Energy-aware task mapping and scheduling for reliable embedded computing systems. ACM Transactions on Embedded Computing Systems, 13 (2s). (doi:10.1145/2544375.2544392).

Record type: Article

Abstract

Task mapping and scheduling are critical in minimizing energy consumption while satisfying the performance requirement of applications enabled on heterogeneous multiprocessor systems. An area of growing concern for modern multiprocessor systems is the increase in the failure probability of one or more component processors. This is especially critical for applications where performance degradation (e.g., throughput) directly impacts the quality of service requirement. This article proposes a design-time (offline) multi-criterion optimization technique for application mapping on embedded multiprocessor systems to minimize energy consumption for all processor fault-scenarios. A scheduling technique is then proposed based on self-timed execution to minimize the schedule storage and construction overhead at runtime. Experiments conducted with synthetic and real applications from streaming and nonstreaming domains on heterogeneous MPSoCs demonstrate that the proposed technique minimizes energy consumption by 22% and design space exploration time by 100x, while satisfying the throughput requirement for all processor fault-scenarios. For scalable throughput applications, the proposed technique achieves 30% better throughput per unit energy, compared to the existing techniques. Additionally, the self-timed execution-based scheduling technique minimizes schedule construction time by 95% and storage overhead by 92%.

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More information

Published date: January 2014
Organisations: Electronics & Computer Science

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Local EPrints ID: 375488
URI: https://eprints.soton.ac.uk/id/eprint/375488
PURE UUID: 4eaaf941-df53-432b-9e17-4e142a65c0c2

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Date deposited: 27 Mar 2015 12:53
Last modified: 15 Jul 2019 21:26

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