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Currently, there is no complete top-down workflow for pNML. Researchers must instead simultaneously handle place-and-route, timing, and logic minimization by hand. These tasks include multiple NP-Hard subproblems, and the lack of automated tools for solving them for pNML precludes the design of large-scale pNML circuits."]},{"key":"dc:title","label":"Title","values":["Design and Investigation of Genetic Algorithmic and Reinforcement Learning Approaches to Wire Crossing Reductions for pNML Devices"]}]}],"canonical_facts":{"dc:contributor":["Matthew A. Morrison","Yixin Chen","Richard Gordon"],"dc:creator":["Gunter, Alexander Keith"],"dc:date.available":["2020-01-23T08:00:00Z"],"dc:description.abstract":["Perpendicular nanomagnet logic (pNML) is an emerging post-CMOS technology which encodes binary data in the polarization of single-domain nanomagnets and performs operations via fringing field interactions. Currently, there is no complete top-down workflow for pNML. 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