Cluster based architecture synthesis minimizing the resources under time constraint

Xiyang Liu, Ailong Song, Zili Shao, Chunxiang Li, Ke Chen, Wei Wang

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

2 Citations (Scopus)

Abstract

High performance using minimal resources has become a serious problem for digital signal processing (DSP) applications. The number of addressable registers is a significant obstacle for centralized architecture achieving high performance of DSP applications. In this paper, we propose a novel cluster based architecture synthesis algorithm, using minimal resources with time and register constraints, which adds a new cluster rather than inserts memory operations when registers are inadequate. By counting the register, inter-cluster communications and function units requirements during scheduling, the cluster with optimal performance is selected to schedule every instruction of the application. The redundant resources of the initial configuration obtained by our algorithm are further optimized. The experiments demonstrate that, compared with the centralized architecture synthesis, our approach achieves up to 224% improvement in success rate for general cases and up to 369% improvement for cases with tight constraints, and effectively reduces the resources usage.
Original languageEnglish
Title of host publication2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
Pages1558-1561
Number of pages4
DOIs
Publication statusPublished - 8 Nov 2010
Event2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
Duration: 14 Mar 201019 Mar 2010

Conference

Conference2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
CountryUnited States
CityDallas, TX
Period14/03/1019/03/10

Keywords

  • Clustering methods
  • Digital filters
  • Registers
  • Scheduling

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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