Combining Genetic Algorithms Based Task Mapping and Optimal Voltage Selection for Energy-Efficient Distributed System Synthesis
Energy consumption has become one of dominant design concerns in distributed embedded systems. Dynamic voltage scaling (DVS) techniques have been proved to be quite effective in reducing both dynamic and static power consumption simultaneously. Thus, integrating processing elements (PEs) supporting DVS techniques into distributed embedded systems synthesis becomes an imperative way to make an energy-efficient design budget. In this paper, we propose a synthesis framework, which integrates task mapping, scheduling and voltage selection together to minimize energy consumption of distributed systems. Genetic algorithms based task mapping are deployed to do task mapping in the outer loop, which can maximize the energy saving possibilities. A nonlinear programming based optimal voltage selection engine is then used in the inner loop. Unlike previous approaches, this combination is the first time to be implemented, and relevant experiment results show that, comparing to separate synthesis flows, up to 40％ more energy savings are achieved.
Yongpan Liu Huazhong Yang Rong Luo Hui Wang
Department of Electronics Engineering, Tsinghua University, 100084, Beijing, China
国际会议
2006 International Conference on Communications,Circuits and Systems(第四届国际通信、电路与系统学术会议)
广西桂林
英文
2074-2078
2006-06-25（万方平台首次上网日期，不代表论文的发表时间）