The University of Southampton
University of Southampton Institutional Repository

Thermal-aware adaptive energy minimization of openMP parallel applications

Thermal-aware adaptive energy minimization of openMP parallel applications
Thermal-aware adaptive energy minimization of openMP parallel applications
Energy minimization of parallel applications considering thermal distributions among the processor cores is an emerging challenge for current and future generations of many-core computing systems. This paper proposes an adaptive energy minimization approach that hierarchically applies dynamic voltage\slash frequency scaling (DVFS), thread-to-core affinity and dynamic concurrency controls (DCT) to address this challenge. The aim is to minimize the energy consumption and achieve balanced thermal distributions among cores, thereby improving the lifetime reliability of the system, while meeting a specified power budget requirement. Fundamental to this approach is an iterative learning-based control algorithm that adapts the VFS and core allocations dynamically based on the CPU workloads and thermal distributions of the processor cores, guided by the CPU performance counters at regular intervals. The adaptation is facilitated through modified OpenMP library-based power budget annotations. The proposed approach is extensively validated on an Intel Xeon E5-2630 platform with up to 12 CPUs running NAS parallel benchmark applications.
1-3
Shafik, Rishad Ahmed
aa0bdafc-b022-4cb2-a8ef-4bf8a03ba524
Das, Anup K.
2a0d6cea-309b-4053-a62e-234807f89306
Yang, Sheng
04b9848f-ddd4-4d8f-93b6-b91a2144d49c
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d
Shafik, Rishad Ahmed, Das, Anup K., Yang, Sheng, Merrett, Geoff V. and Al-Hashimi, Bashir (2015) Thermal-aware adaptive energy minimization of openMP parallel applications At DATE2015: Workshop on Designing with Uncertainty - Opportunities & Challenges in Conjunction with Design and Test in Europe (DATE) Conference, France. 09 - 13 Mar 2015. 3 pp, pp. 1-3.

Shafik, Rishad Ahmed, Das, Anup K., Yang, Sheng, Merrett, Geoff V. and Al-Hashimi, Bashir (2015) Thermal-aware adaptive energy minimization of openMP parallel applications At DATE2015: Workshop on Designing with Uncertainty - Opportunities & Challenges in Conjunction with Design and Test in Europe (DATE) Conference, France. 09 - 13 Mar 2015. 3 pp, pp. 1-3.

Record type: Conference or Workshop Item (Paper)

Abstract

Energy minimization of parallel applications considering thermal distributions among the processor cores is an emerging challenge for current and future generations of many-core computing systems. This paper proposes an adaptive energy minimization approach that hierarchically applies dynamic voltage\slash frequency scaling (DVFS), thread-to-core affinity and dynamic concurrency controls (DCT) to address this challenge. The aim is to minimize the energy consumption and achieve balanced thermal distributions among cores, thereby improving the lifetime reliability of the system, while meeting a specified power budget requirement. Fundamental to this approach is an iterative learning-based control algorithm that adapts the VFS and core allocations dynamically based on the CPU workloads and thermal distributions of the processor cores, guided by the CPU performance counters at regular intervals. The adaptation is facilitated through modified OpenMP library-based power budget annotations. The proposed approach is extensively validated on an Intel Xeon E5-2630 platform with up to 12 CPUs running NAS parallel benchmark applications.

PDF date2015-ws-camera-ready.pdf - Accepted Manuscript
Download (360kB)

More information

e-pub ahead of print date: 2015
Venue - Dates: DATE2015: Workshop on Designing with Uncertainty - Opportunities & Challenges in Conjunction with Design and Test in Europe (DATE) Conference, France, 2015-03-09 - 2015-03-13
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 373337
URI: http://eprints.soton.ac.uk/id/eprint/373337
PURE UUID: ac5fcfb7-9594-4e64-b6d1-a59e3d13fc2c
ORCID for Geoff V. Merrett: ORCID iD orcid.org/0000-0003-4980-3894

Catalogue record

Date deposited: 15 Jan 2015 14:30
Last modified: 17 Jul 2017 21:34

Export record

Contributors

Author: Rishad Ahmed Shafik
Author: Anup K. Das
Author: Sheng Yang
Author: Geoff V. Merrett ORCID iD

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×