Genetic Algorithm based pipeline scheduling in high-level synthesis

Xiaohao Gao, Takeshi Yoshimura

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルProceedings of International Conference on ASIC
出版社IEEE Computer Society
ISBN(印刷版)9781467364157
DOI
出版ステータスPublished - 2013
イベント2013 IEEE 10th International Conference on ASIC, ASICON 2013 - Shenzhen
継続期間: 2013 10 282013 10 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

フィンガープリント 「Genetic Algorithm based pipeline scheduling in high-level synthesis」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル