Overhead-aware system-level joint energy and performance optimization for streaming applications on multiprocessor systems-on-chip

Hui Liu, Zili Shao, Meng Wang, Ping Chen

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

40 Citations (Scopus)

Abstract

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.
Original languageEnglish
Title of host publicationProceedings of the 20th Euromicro Conference on Real-Time Systems, ECRTS 2008
Pages92-101
Number of pages10
DOIs
Publication statusPublished - 24 Sep 2008
Event20th Euromicro Conference on Real-Time Systems, ECRTS 2008 - Prague, Czech Republic
Duration: 2 Jul 20084 Jul 2008

Conference

Conference20th Euromicro Conference on Real-Time Systems, ECRTS 2008
CountryCzech Republic
CityPrague
Period2/07/084/07/08

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture

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