Energy-aware resource allocation for multicores with per-core frequency scaling

Xinghui Zhao; Nadeem Jamali

doi:10.1186/s13174-014-0009-x

Back

Energy-aware resource allocation for multicores with per-core frequency scaling

Journal article

Open access

Energy-aware resource allocation for multicores with per-core frequency scaling

Xinghui Zhao and Nadeem Jamali

Journal of internet services and applications, Vol.5(1), pp.1-15

12/2014

DOI: https://doi.org/10.1186/s13174-014-0009-x

Handle:

https://hdl.handle.net/2376/114620

Files and links (1)

url

https://doi.org/10.1186/s13174-014-0009-xView

Published (Version of record) Open

Abstract

Processor Architectures

Computer Systems Organization and Communication Networks

Computer Applications

Energy conservation

Computer Science

Business Information Systems

Information Systems and Communication Service

Resource management

Performance

Computer Communication Networks

Frequency scheduling

With the growing ubiquity of computer systems, the energy consumption of these systems is of increasing concern. Multicore architectures offer a potential opportunity for energy conservation by allowing cores to operate at lower frequencies when the processor demand low. Until recently, this has meant operating all cores at the same frequency, and research on analyzing power consumption of multicores has assumed that all cores run at the same frequency. However, emerging technologies such as fast voltage scaling and Turbo Boost promise to allow cores on a chip to operate at different frequencies.This paper presents an energy-aware resource management model, DREAM-MCP, which provides a flexible way to analyze energy consumption of multicores operating at non-uniform frequencies. This information can then be used to generate a fine-grained energy-efficient schedule for execution of the computations – as well as a schedule of frequency changes on a per-core basis – while satisfying performance requirements of computations. To evaluate our approach, we have carried out two case studies, one involving a problem with static workload (Gravitational N-Body Problem), and another involving a problem with dynamic workload (Adaptive Quadrature). Experimental results show that for both problems, the energy savings achieved using this approach far outweigh the energy consumed in the reasoning required for generating the schedules.

Metrics

13 Record Views

See more details

Details

Title: Energy-aware resource allocation for multicores with per-core frequency scaling
Creators: Xinghui Zhao - School of Engineering and Computer Science Washington State University 14204 NE Salmon Creek Ave. Vancouver 98686 WA USA
Nadeem Jamali - Department of Computer Science University of Saskatchewan 110 Science Place Saskatoon S7N 5C9 SK Canada
Publication Details: Journal of internet services and applications, Vol.5(1), pp.1-15
Academic Unit: Engineering and Computer Science (VANC), School of
Publisher: Springer London; London
Identifiers: 99900548334701842
Language: English
Resource Type: Journal article