FPGA placement methodology based on grey relational clustering

摘要

This paper aims at developing grey relational clustering for FPGA placement. The proposed GRAP (Grey Relational Clustering Apply to Placement) algorithm was combined with grey relational clustering and CAPRI algorithm to successfully solve FPGA placement design problem. Experimental results demonstrate that the GRAP compares the Hilbert, Z and Snake with BB cost function in space filling curve. The GRAP improved BB cost by 0.753%, 0.324% and 0.096% for the Hilbert, Z and Snake, respectively.