Multi-objective GA to schedule task graphs on heterogeneous voltage frequency islands

Abstract

Energy consumption of multiprocessor's system is increasing day by day. The capability of multiprocessor systems and high compute-intensive tasks play a major role in increasing energy consumption. Voltage frequency island (VFI) architecture partitioned the cores into groups for which voltage/frequency can be controlled by a single switch. VFI plays a major role in optimizing the energy consumption. We have generated the initial population by using the slot technique to VFI architecture. The genetic algorithm studied by many researchers to solve scheduling problems. So we combined the genetic algorithm with the VFI-enabled architecture and slot approach called VFIGen. Then apply the VFIGen algorithm to optimize the energy consumption. When comparing the results of the proposed one with the existing state-of-art we achieved the performance gain by $28\%$ to $39\%$.