Communication-aware Task Partition based Energy Optimization Method for Heterogeneous System

Targeted for the heterogeneous parallel system consisting of general purpose processor and application-specific accelerator,this paper proposes an energy optimization method of coordinating communication-aware task partition and voltage scaling.The main ideal is partitioning a parallel task graph and mapping each task onto heterogeneous processing units to minimize the energy consumption within performance constraint.In current heterogeneous parallel systems,the host processor and accelerator are connected via system bus,which incurs in un-neglected overhead;therefore,communication-aware task partition method is the key problem.This paper proposes an ILP-based static optimal energy optimization method and the genetic algorithm based dynamic energy optimization method.Finally,we validate the efficiency of the proposed methods with a typical scientific application.