A Framework for Verification of Signal Propagation Through Sequential Nanomagnet Logic Devices

Nanomagnet Logic is an emerging technology for low-power, highly-scalable implementation of quantum-dot cellular automata. Feedback permits reuse of logical subroutines, which is a desired functionality of any computational device. Determining whether feedback is feasible is essential to assessing the robustness of nanomagnet logic in any pipelined computing design. Therefore, development of a quantitative approach for verification of feedback paths is critical for development of design and synthesis tools for nanomagnet logic structures. In this paper, a framework for verification of sequential nanomagnet logic devices is presented. A set of definitions for canonical alignment and state definitions for NML paths are presented, as well as mathematical operations for determining the resulting states. The simulation results are presented for quantification of the NML magnetization angles for horizontal, vertical, negative-diagonal, and positive diagonal geometric alignments. The presented framework may be used as the basis for defining a representation of signal propagation for design and verification for robust NML devices and preventing deadlock resulting from improper implementation

Design and Investigation of Genetic Algorithmic and Reinforcement Learning Approaches to Wire Crossing Reductions for pNML Devices

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. 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