期刊
出版社
IEEE
DOI: 10.1109/ieeeconf44664.2019.9048700
关键词
Stochastic computing; Hamiltonian; SystemVerilog model; FPGA
资金
- Brainware LSI project of MEXT, Japan
- JST PRESTO Grant [JPMJPR18M5]
- CANON MEDICAL SYSTEMS CORPORATION
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 largescale 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.
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