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 co-processors and can provide high performance for a wide spectrum of applications at significantly lower energy requirements per FLOP. In this paper, we develop parallel algorithms and software for constructing multi-resolution SAR 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 trade-offs 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.
