Binary decision diagram‐based synthesis technique for improved mapping of Boolean functions inside memristive crossbar‐slices

Abstract

Memristors are two‐terminal nano‐electronic devices that make it possible to design non‐volatile memory and logic circuits with high integration density. The logic operations of memristor‐based circuits are performed by applying suitable voltages across them. Researchers have been widely experimenting with this device to efficiently implement particular logic functions. However, recently, a synthesis methodology for arbitrary logic functions has been reported, where an input Boolean function is first represented as a Binary Decision Diagram (BDD), followed by the mapping of the BDD‐nodes (netlists of 2‐input NOR and NOT gates) inside a cluster of sliced crossbar‐arrays. The authors propose to map the BDD‐nodes for any input Boolean function to the crossbar‐slices using an improved technique, where each BDD‐node is mapped more efficiently, and the node‐logic is implemented following the Memristor Aided loGIC (MAGIC) design style. Our proposed mapping‐based realization of a BDD‐node has superior performance and energy‐efficiency than the existing IMPLY and MAGIC‐based BDD‐node designs techniques, provided all three node‐designs are implemented inside the similar‐sized crossbars. Comparative‐study of the synthesis results showed that the memristive‐circuits generated using our proposed technique are 26.95% faster, and need 42.32% lesser memristors (on average) than their peers, implemented using the existing approach of slicing crossbar‐architecture.

Reliability Analysis of Cold-standby Systems with Subsystems Using Conditional Binary Decision Diagrams

“…In [16], BDDs were set to be elements of a newly lifted domain that were applied to analyze program families, the internal nodes were labeled with Boolean features and leaf nodes belong to an existing single-program analysis domain. An improved technique related to mapping the nodes of the BDD for any input Boolean function to the crossbar slices is proposed in [17]. In [18], the BDD was used for a genetic algorithm reordering optimizer, and it can iteratively process a large population with a randomized mixing of low destructive crossover/mutation operators.…”