Analyzing System-Level Information’s Correlation to FPGA Placement

Author:

Gharibian Farnaz1,Shannon Lesley1,Jamieson Peter2,Chung Kevin3

Affiliation:

1. Simon Fraser University

2. Miami University

3. Leonid Systems

Abstract

One popular placement algorithms for Field-Programmable Gate Arrays (FPGAs) is called Simulated Annealing (SA). This algorithm tries to create a good quality placement from a flattened design that no longer contains any high-level information related to the original design hierarchy. Placement is an NP-hard problem, and as the size and complexity of designs implemented on FPGAs increases, SA does not scale well to find good solutions in a timely fashion. In this article, we investigate if system-level information can be reconstructed from a flattened netlist and evaluate how that information is realized in terms of its locality in the final placement. If there is a strong relationship between good quality placements and system-level information, then it may be possible to divide a large design into smaller components and improve the time needed to create a good quality placement. Our preliminary results suggest that the locality property of the information embedded in the system-level HDL structure (i.e. “module”, “always”, and “if” statements) is greatly affected by designer HDL coding style. Therefore, a reconstructive algorithm, called Affinity Propagation, is also considered as a possible method of generating a meaningful coarse-grain picture of the design.

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Using data-mining techniques to improve combinatorial optimization algorithms;Journal of Algorithms & Computational Technology;2022-01

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