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The Slowdown or Race-to-idle Question: Workload-Aware Energy Optimization of SMT Multicore Platforms under Process Variation

The Slowdown or Race-to-idle Question: Workload-Aware Energy Optimization of SMT Multicore Platforms under Process Variation
The Slowdown or Race-to-idle Question: Workload-Aware Energy Optimization of SMT Multicore Platforms under Process Variation
Two widely used approaches for reducing energy consumption in multithreaded workloads are slowdown (using DVFS) and race-to-idle. In this paper, we first demonstrate that most energy-efficient choice is dependent on (1) workload (memory bound, CPU bound etc.), (2) process variation and (3) support for Simultaneous Multithreading (SMT). We then propose an approach for mapping application threads on SMT multicore systems at run-time, to minimize energy consumption. The proposed approach interfaces with the OS and hardware performance counters to characterize application threads. This characterization captures the effect of process variation on execution time and identifies the break-even operating point, where one strategy (slowdown or race-to-idle) outperforms the other. Thread mapping is performed using these characterized data by iteratively collapsing application threads (SMT) followed by binary programming-based thread mapping. Finally, performance slack is exploited at run-time to select between slowdown and race-to-idle, based upon the break-even operating point calculated for each individual thread. This end-to-end approach is implemented as a run-time manager for the Linux operating system and is validated across a range of high performance applications. Results demonstrate up to 13% energy reduction over all state-of-the-art approaches, with an average of 18% improvement over Linux.
Das, Anup
2a0d6cea-309b-4053-a62e-234807f89306
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
Al-Hashimi, Bashir M.
0b29c671-a6d2-459c-af68-c4614dce3b5d
Das, Anup, Merrett, Geoff V. and Al-Hashimi, Bashir M. (2015) The Slowdown or Race-to-idle Question: Workload-Aware Energy Optimization of SMT Multicore Platforms under Process Variation At Conference on Design, Automation and Test in Europe 2016, Germany. 14 - 18 Mar 2016. 4 pp.

Das, Anup, Merrett, Geoff V. and Al-Hashimi, Bashir M. (2015) The Slowdown or Race-to-idle Question: Workload-Aware Energy Optimization of SMT Multicore Platforms under Process Variation At Conference on Design, Automation and Test in Europe 2016, Germany. 14 - 18 Mar 2016. 4 pp.

Record type: Conference or Workshop Item (Paper)

Abstract

Two widely used approaches for reducing energy consumption in multithreaded workloads are slowdown (using DVFS) and race-to-idle. In this paper, we first demonstrate that most energy-efficient choice is dependent on (1) workload (memory bound, CPU bound etc.), (2) process variation and (3) support for Simultaneous Multithreading (SMT). We then propose an approach for mapping application threads on SMT multicore systems at run-time, to minimize energy consumption. The proposed approach interfaces with the OS and hardware performance counters to characterize application threads. This characterization captures the effect of process variation on execution time and identifies the break-even operating point, where one strategy (slowdown or race-to-idle) outperforms the other. Thread mapping is performed using these characterized data by iteratively collapsing application threads (SMT) followed by binary programming-based thread mapping. Finally, performance slack is exploited at run-time to select between slowdown and race-to-idle, based upon the break-even operating point calculated for each individual thread. This end-to-end approach is implemented as a run-time manager for the Linux operating system and is validated across a range of high performance applications. Results demonstrate up to 13% energy reduction over all state-of-the-art approaches, with an average of 18% improvement over Linux.

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Accepted/In Press date: 29 October 2015
Venue - Dates: Conference on Design, Automation and Test in Europe 2016, Germany, 2016-03-14 - 2016-03-18
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 384892
URI: http://eprints.soton.ac.uk/id/eprint/384892
PURE UUID: 51570274-c588-4faf-bec8-1736e51b9edc
ORCID for Geoff V. Merrett: ORCID iD orcid.org/0000-0003-4980-3894

Catalogue record

Date deposited: 09 Dec 2015 10:49
Last modified: 13 Nov 2017 00:03

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Contributors

Author: Anup Das
Author: Geoff V. Merrett ORCID iD

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