Paper Info
Title
Energy-Efficient Run-Time Mapping and Thread Partitioning of Concurrent OpenCL Applications on CPU-GPU MPSoCs.
Abstract
Heterogeneous Multi-Processor Systems-on-Chips (MPSoCs) containing CPU and GPU cores are typically required to execute applications concurrently. However, as will be shown in this paper, existing approaches are not well suited for concurrent applications as they are developed either by considering only a single application or they do not exploit both CPU and GPU cores at the same time. In this paper, we propose an energy-efficient run-time mapping and thread partitioning approach for executing concurrent OpenCL applications on both GPU and GPU cores while satisfying performance requirements. Depending upon the performance requirements, for each concurrently executing application, the mapping process finds the appropriate number of CPU cores and operating frequencies of CPU and GPU cores, and the partitioning process identifies an efficient partitioning of the applications’ threads between CPU and GPU cores. We validate the proposed approach experimentally on the Odroid-XU3 hardware platform with various mixes of applications from the Polybench benchmark suite. Additionally, a case-study is performed with a real-world application SLAMBench. Results show an average energy saving of 32% compared to existing approaches while still satisfying the performance requirements.
Year
DOI
Venue
2017
10.1145/3126548
ACM Trans. Embedded Comput. Syst.
Keywords
Field
DocType
Energy consumption, Heterogeneous MPSoC, OpenCL applications, Performance, Run-time management
Suite,Computer science,Efficient energy use,Parallel computing,Exploit,Thread (computing),Real-time computing,Multi-core processor,Energy consumption,CPU shielding,Embedded system
Journal
Volume
Issue
ISSN
16
5
1539-9087
Citations 
PageRank 
References 
5
0.45
25
Authors
5
Name
Order
Citations
PageRank
Amit Kumar Singh1196.81
Alok Prakash216720.47
Basireddy Karunakar Reddy3306.51
geoffrey merrett441149.30
B. M. Al-Hashimi524615.05