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Thermal-aware adaptive energy minimization of open MP parallel applications

Thermal-aware adaptive energy minimization of open MP parallel applications
Thermal-aware adaptive energy minimization of open MP 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
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 open MP parallel applications. At DATE2015: Workshop on Designing with Uncertainty - Opportunities & Challenges in Conjunction with Design and Test in Europe (DATE) Conference (13/03/15) 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.

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More information

Published date: March 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: https://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: 30 Nov 2018 01:33

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