Perpendicular nanomagnet logic (pNML) is an emerging post-CMOS technology which encodes binary data in the polarization of single-domain nanomagnets, and performs fringing field interactions operations. Currently, there does not exist top-down workflows for pNML. Researchers must performing exhaustive place-and-route, timing, and logic minimization by hand. We present a behavioral-level model and parallelizable algorithms to both augment the existing design workflow and enable a future top-down workflow for pNML. These algorithms allow the characterization of a physical design, efficient granular simulation of a circuit, and automatic reduction of wire crossings.