A novel placement algorithm for symmetrical FPGA

Xu Wenyao; Xu Kejun; Xu Xinmin

doi:10.1109/ICASIC.2007.4415870

A novel placement algorithm for symmetrical FPGA

Xu Wenyao
, Xu Kejun
, Xu Xinmin

Department of Computer Science and Engineering

Zhejiang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

Placement becomes a vital current concern in FPGA CAD flow. This paper presents a novel FPGA placement algorithm based on ant colony optimization (ACO), a new meta-heuristic algorithm characterized by inherent parallelism, positive feedback mechanism, and stochastic decision policy with swarm intelligence. We test the performance of our proposed algorithm using a set of Microelectronics Center of North Carolina (MCNC) benchmark circuits on island-style architecture FPGA, and have a comprehensive comparison with simulated annealing (SA), genetic algorithm (GA) and hybrid meta-heuristic approach mixed GA and SA. The experimental results show that our placement algorithm can achieves promising performance and is a potential approach for FPGA placement.

Original language	English
Title of host publication	ASICON 2007 - 2007 7th International Conference on ASIC Proceeding
Pages	1281-1284
Number of pages	4
DOIs	https://doi.org/10.1109/ICASIC.2007.4415870
State	Published - 2007
Event	2007 7th International Conference on ASIC, ASICON 2007 - Guilin, China Duration: Oct 26 2007 → Oct 29 2007

Publication series

Name	ASICON 2007 - 2007 7th International Conference on ASIC Proceeding

Conference

Conference	2007 7th International Conference on ASIC, ASICON 2007
Country/Territory	China
City	Guilin
Period	10/26/07 → 10/29/07

Access to Document

10.1109/ICASIC.2007.4415870

Cite this

@inproceedings{248b428475d64d74876a86dad6edeb09,

title = "A novel placement algorithm for symmetrical FPGA",

abstract = "Placement becomes a vital current concern in FPGA CAD flow. This paper presents a novel FPGA placement algorithm based on ant colony optimization (ACO), a new meta-heuristic algorithm characterized by inherent parallelism, positive feedback mechanism, and stochastic decision policy with swarm intelligence. We test the performance of our proposed algorithm using a set of Microelectronics Center of North Carolina (MCNC) benchmark circuits on island-style architecture FPGA, and have a comprehensive comparison with simulated annealing (SA), genetic algorithm (GA) and hybrid meta-heuristic approach mixed GA and SA. The experimental results show that our placement algorithm can achieves promising performance and is a potential approach for FPGA placement.",

author = "Xu Wenyao and Xu Kejun and Xu Xinmin",

year = "2007",

doi = "10.1109/ICASIC.2007.4415870",

language = "English",

isbn = "1424411327",

series = "ASICON 2007 - 2007 7th International Conference on ASIC Proceeding",

pages = "1281--1284",

booktitle = "ASICON 2007 - 2007 7th International Conference on ASIC Proceeding",

note = "2007 7th International Conference on ASIC, ASICON 2007 ; Conference date: 26-10-2007 Through 29-10-2007",

}

Wenyao, X, Kejun, X & Xinmin, X 2007, A novel placement algorithm for symmetrical FPGA. in ASICON 2007 - 2007 7th International Conference on ASIC Proceeding., 4415870, ASICON 2007 - 2007 7th International Conference on ASIC Proceeding, pp. 1281-1284, 2007 7th International Conference on ASIC, ASICON 2007, Guilin, China, 10/26/07. https://doi.org/10.1109/ICASIC.2007.4415870

TY - GEN

T1 - A novel placement algorithm for symmetrical FPGA

AU - Wenyao, Xu

AU - Kejun, Xu

AU - Xinmin, Xu

PY - 2007

Y1 - 2007

N2 - Placement becomes a vital current concern in FPGA CAD flow. This paper presents a novel FPGA placement algorithm based on ant colony optimization (ACO), a new meta-heuristic algorithm characterized by inherent parallelism, positive feedback mechanism, and stochastic decision policy with swarm intelligence. We test the performance of our proposed algorithm using a set of Microelectronics Center of North Carolina (MCNC) benchmark circuits on island-style architecture FPGA, and have a comprehensive comparison with simulated annealing (SA), genetic algorithm (GA) and hybrid meta-heuristic approach mixed GA and SA. The experimental results show that our placement algorithm can achieves promising performance and is a potential approach for FPGA placement.

AB - Placement becomes a vital current concern in FPGA CAD flow. This paper presents a novel FPGA placement algorithm based on ant colony optimization (ACO), a new meta-heuristic algorithm characterized by inherent parallelism, positive feedback mechanism, and stochastic decision policy with swarm intelligence. We test the performance of our proposed algorithm using a set of Microelectronics Center of North Carolina (MCNC) benchmark circuits on island-style architecture FPGA, and have a comprehensive comparison with simulated annealing (SA), genetic algorithm (GA) and hybrid meta-heuristic approach mixed GA and SA. The experimental results show that our placement algorithm can achieves promising performance and is a potential approach for FPGA placement.

UR - https://www.scopus.com/pages/publications/48349116471

U2 - 10.1109/ICASIC.2007.4415870

DO - 10.1109/ICASIC.2007.4415870

M3 - Conference contribution

AN - SCOPUS:48349116471

SN - 1424411327

SN - 9781424411320

T3 - ASICON 2007 - 2007 7th International Conference on ASIC Proceeding

SP - 1281

EP - 1284

BT - ASICON 2007 - 2007 7th International Conference on ASIC Proceeding

T2 - 2007 7th International Conference on ASIC, ASICON 2007

Y2 - 26 October 2007 through 29 October 2007

ER -

A novel placement algorithm for symmetrical FPGA

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this