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)
Cited by
1 articles.
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