A Design Framework for Invertible Logic

Invertible logic using a probabilistic magnetoresistive device model has been recently presented that can compute functions in bidirectional ways and solve several problems quickly, such as factorization combinational optimization. In this article, we present design framework for invertible circuits. Our approach makes use of linear programming to create Hamiltonian library with the minimum number nodes small invertible-logic functions. addition, is approximated based on stochastic computing synthesizable SystemVerilog, faster simulation compiled SystemC binary realized than conventional SPICE-level verified field-programmable gate array (FPGA) prototyping. Using our framework, circuits are designed emulated (verified) SystemC, exhibiting five order-of-magnitude work.