Multiobjective Optimization of SAR Reconstruction on Hybrid Multicore Systems

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Abstract

Hybrid multicore processors (HMPs) are poised to dominate the landscape of the next generation of computing on the desktop as well as on exascale systems. HMPs consist of general purpose CPU cores along with specialized coprocessors and can provide high performance for a wide spectrum of applications at significantly lower energy requirements per floating-point operations per second (FLOP). In this article, we develop parallel algorithms and software for constructing multiresolution synthetic aperture radar images on HMPs. We develop several load balancing algorithms for optimizing time performance and energy on HMPs. We also present a systematic approach for deriving the energy-time performance tradeoffs on HMPs in the presence of dynamic voltage frequency scaling. Pareto-optimal curves are presented on a system consisting of 24 traditional cores and a GPU.

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Wijayasiri, A., Banerjee, T., Ranka, S., Sahni, S., & Schmalz, M. (2020). Multiobjective Optimization of SAR Reconstruction on Hybrid Multicore Systems. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 4674–4688. https://doi.org/10.1109/JSTARS.2020.3014531

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