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Overhead-Aware System-Level Joint Energy and Performance Optimization for Streaming Applications on Multiprocessor Systems-on-Chip

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4 Author(s)
Hui Liu ; Software Eng. Inst., Xidian Univ., Xi''an ; Zili Shao ; Meng Wang ; Ping Chen

In this paper, we focus on joint energy and performance optimization for streaming applications on multiprocessor systems-on-chip by combining task-level coarse-grained software pipelining with DVS (dynamic voltage scaling)and DPM (dynamic power management) techniques with the considerations of transition overhead, inter-processor communication and discrete voltage levels. We propose a two-phase approach to solve the problem. In the first phase, we propose a coarse-grained task parallelization algorithm called RDAG to transform a periodic dependent task graph into a set of independent tasks based on the retiming technique[19]. In the second phase, we propose a novel scheduling algorithm called SpringS that works like a spring by iteratively adjusting task scheduling and voltage selection by combining DVS and DPM. We conduct experiments with a set of benchmarks from E3S [10] and TGFF [27]. The experimental results show that our technique can achieve 49:8% energy saving on average compared with the approach in [20], that applied DVS and DPM without software pipelining. In addition, given a tight timing constraint, our technique can obtain a feasible solution while the approach in [20] cannot.

Published in:

Real-Time Systems, 2008. ECRTS '08. Euromicro Conference on

Date of Conference:

2-4 July 2008