A Novel Meta-Heuristic for Green Computing on VFI-NoC-HMPSoCs

Abstract

The number of processors has increased significantly on multiprocessor system therefore, Voltage Frequency Island (VFI) recently adopted for effective energy management mechanism in the large scale multiprocessor chip designs. Heterogeneous VFI, Network-on-Chip (NoC) based Multiprocessor System-on-Chips (MPSoCs) i.e. VFI-NoC-HMPSoCs are widely adopted in computational extensive applications due to their higher performance and an exceptional Quality-of-Service (QoS). Proper task scheduling using search-based algorithms on multiprocessor architectures can significantly improve the performance and energy-efficiency of a battery-constrained embedded system. In this paper, unlike the existing population-based optimization algorithms, we propose a novel population-based algorithm called ARSH-FATI that can dynamically switch between explorative and exploitative search modes at run-time for performance trade-off. We also developed a communication contention-aware Earliest Edge Consistent Deadline First (EECDF) scheduling algorithm. Our static scheduler ARHS-FATI collectively performs task mapping and ordering. Consequently, its performance is superior to the existing state-of-the-art approach proposed for homogeneous VFI based NoC-MPSoCs. We conducted the experiments on 8 real benchmarks adopted from Embedded Systems Synthesis Benchmarks (E3S). Our static scheduling approach ARSH-FATI outperformed state-of-the-art technique and achieved an average energy-efficiency of 15% and 20% over CA-TMES-Search and CA-TMES-Quick respectively.