Energy minimization for periodic real-time tasks on heterogeneous processing units

Adopting multiple processing units to enhance the computing capability or reduce the power consumption has been widely accepted for designing modern computing systems. Such configurations impose challenges on energy efficiency in hardware and software implementations. This work targets power-aware and energy-efficient task partitioning and processing unit allocation for periodic real-time tasks on a platform with a library of applicable processing unit types. Each processing unit type has its own power consumption characteristics for maintaining its activeness and executing jobs. This paper proposes polynomial-time algorithms for energy-aware task partitioning and processing unit allocation. The proposed algorithms first decide how to assign tasks onto processing unit types to minimize the energy consumption, and then allocate processing units to fit the demands. The proposed algorithms for systems without limitation on the allocated processing units are shown with an (m+1)-appro...

• Type: Conference
• Year: 2009
• Where: IPPS
• Authors: Jian-Jia Chen, Andreas Schranzhofer, Lothar Thiele
• Keywords: Distributed And Parallel Computing, IPPS 2009, Processing Unit Allocation, Processing Unit Types, Processing Units