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Communication-Aware Energy Consumption Model in Heterogeneous Computing Systems.
- Source :
-
Computer Journal . Jan2024, Vol. 67 Issue 1, p78-94. 17p. - Publication Year :
- 2024
-
Abstract
- Large heterogeneous computing systems are composed of conventional central processing units and graphics processing units (GPUs) where communication plays a crucial role for system performance. This paper presents an energy consumption analytical model in terms of communication perception for the communication–computing pipeline characterization of discrete GPUs systems. We propose a dynamically adaptive energy-efficient task assignment approach, which harnesses particle swarm optimization. Static energy optimization is addressed by optimal task partition granularity. The experimental results demonstrate that the communication-based energy optimization algorithms can be more energy-saving than those without communication consideration. For some application benchmarks, the energy consumption can be saved by up to 31%. This implies the potential that the energy-saving optimization methods can be incorporated in system engineering processes. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00104620
- Volume :
- 67
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Computer Journal
- Publication Type :
- Academic Journal
- Accession number :
- 174909938
- Full Text :
- https://doi.org/10.1093/comjnl/bxac159