Cost minimization of partitioning circuits with complex resource constraints in FPGAs

In this paper, we formulated a new cost minimization partition problem with complex resource constraints in large FPGAs and proposed a maximum matching and ILP based algorithm to solve it. The ILP solver, LINGO, is employed to find the number of the FPGA chips of each type to minimize the total cost. In order to get a smaller cut-size partition, we proposed a new vertex ordering matching algorithm to partition the given circuit. Experimental results on the MCNC LGSynth91 benchmark show that circuit partition with multiple resource types obtained by our algorithm has 21% lower cost on average than that using simple resource type FPGA. The proposed vertex ordering method reduces the cost by 19% compared with the method without vertex ordering considerations