Genetic Algorithm based pipeline scheduling in high-level synthesis

Xiaohao Gao, Takeshi Yoshimura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this work, we present a Genetic Algorithm (GA) based method for pipeline scheduling optimization. The objective is to minimize the circuit area under both data initiation interval and pipeline latency constraints. In the initialization, the scheduler generates a series of solutions between As Soon As Possible (ASAP) and As Late As Possible (ALAP) interval. Afterwards a Linear Programming (LP) algorithm is applied for transforming unfeasible solutions to feasible solutions, which are input to GA for searching the optimization result. In the experiments, our proposed algorithm achieves an average of 29.74% area improvement by comparing with ASAP and ALAP methods.

Original languageEnglish
Title of host publicationProceedings of International Conference on ASIC
PublisherIEEE Computer Society
ISBN (Print)9781467364157
DOIs
Publication statusPublished - 2013
Event2013 IEEE 10th International Conference on ASIC, ASICON 2013 - Shenzhen
Duration: 2013 Oct 282013 Oct 31

Other

Other2013 IEEE 10th International Conference on ASIC, ASICON 2013
CityShenzhen
Period13/10/2813/10/31

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering

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  • Cite this

    Gao, X., & Yoshimura, T. (2013). Genetic Algorithm based pipeline scheduling in high-level synthesis. In Proceedings of International Conference on ASIC [6811982] IEEE Computer Society. https://doi.org/10.1109/ASICON.2013.6811982