A Design Framework for Invertible Logic

Invertible logic using a probabilistic magnetoresistive device model has been recently presented that can operate in bidirectional ways and solve several problems quickly, such as factorization and combinational optimization. In this paper, we present a design framework for large- scale invertible l...

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Bibliographic Details
Main Authors: Onizawa, N., Nishino, K., Smithson, S., Meyer, B., Gross, W., Yamagata, H., Fujita, H., Hanyu, T.
Format: Conference Proceeding
Language:English
Subjects:
FPGA
Hamiltonian
Stochastic computing
SystemVer- ilog model
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Summary:Invertible logic using a probabilistic magnetoresistive device model has been recently presented that can operate in bidirectional ways and solve several problems quickly, such as factorization and combinational optimization. In this paper, we present a design framework for large- scale invertible logic circuits. Our approach makes use of linear programming to create a Hamiltonian library with the minimum number of nodes. In addition, as the device model is approximated based on stochastic computing in SystemVerilog, a faster simulation using the compiled SystemC binary is realized than a conventional SPICE-level simulation. We have evaluated our framework on designing invertible multipliers, which realizes almost 5 order-of-magnitude faster simulation than a conventional method.
ISSN:2576-2303
DOI:10.1109/IEEECONF44664.2019.9048700