Leech, Charles and Vala, Charan Kumar and Acharyya, Amit and Yang, Sheng and Merrett, Geoffrey and Al-Hashimi, Bashir
(2017)
Run-time performance and power optimization of parallel disparity estimation on many-core platforms.
ACM Transactions on Embedded Computing Systems.
ISSN 1539-9087
(In Press)
Abstract
This paper investigates the use of many-core systems to execute the disparity estimation algorithm, used in stereo vision applications, as these systems can provide flexibility between performance scaling and power consumption. We present a learning-based run-time management approach which achieves a required performance threshold whilst minimizing power consumption through dynamic control of frequency and core allocation. Experimental results are obtained from a 61-core Intel Xeon Phi platform for the above investigation. The same performance can be achieved with an average reduction in power consumption of 27.8% and increased energy efficiency by 30.04% when compared to DVFS control alone without run-time management.
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