Optimal and Heuristic Algorithms to Synthesize Lattices of Four-Terminal Switches

In this work, we study implementation of Boolean functions with nano-crossbar arrays where each crosspoint behaves as a fourterminal switch controlled by a Boolean literal. These types of arrays are commonly called as switching lattices. We propose optimal and heuristic algorithms that minimize lattice sizes to implement a given Boolean function. The algorithms are mainly constructed on a technique that finds Boolean functions of lattices having independent inputs. This technique works recursively by using transition matrices representing columns and rows of the lattice. It performs symbolic manipulation of Boolean literals as opposed to using truth tables that allows us to successfully find Boolean functions having up to 81 variables corresponding to a 9×9-lattice. With a Boolean function of a certain sized lattice, we check if a given function can be implemented with this lattice size by defining the problem as a satisfiability problem. This process is repeated until a desired solution is found. Additionally, we fix the previously proposed algorithm that is claimed to be optimal. The fixed version guarantees optimal sizes. Finally, we perform synthesis trials on standard benchmark circuits to evaluate the proposed algorithms by considering lattice sizes and runtimes in comparison with the recently proposed three algorithms.This work is supported by the EU-H2020-RISE project NANOxCOMP #691178 and the TUBITAK-Career project #113E760

Realization of Four-Terminal Switching Lattices: Technology Development and Circuit Modeling

Our European Union’s Horizon-2020 project aims to develop a complete synthesis and performance optimization methodology for switching nano-crossbar arrays that leads to the design and construction of an emerging nanocomputer. Within the project, we investigate different computing models based on either two-terminal switches, realized with field effect transistors, resistive and diode devices, or four-terminal switches. Although a four-terminal switch based model offers a significant area advantage, its realization at the technology level needs further justifications and raises a number of questions about its feasibility. In this study, we answer these questions. First, by using three dimensional technology computer-aided design (TCAD) simulations, we show that four-terminal switches can be directly implemented with the CMOS technology. For this purpose, we try different semiconductor gate materials in different formations of geometric shapes. Then, by fitting the TCAD simulation data to the standard CMOS current-voltage equations, we develop a Spice model of a four-terminal switch. Finally, we successfully perform Spice circuit simulations on four-terminal switches with different sizes. As a follow-up work within the project, we will proceed to the fabrication step.This work is part of a project that has received funding from the European Union’s H2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 691178, and supported by the TUBITAK-Career project #113E760

Integrated Synthesis Methodology for Crossbar Arrays

Nano-crossbar arrays have emerged as area and power efficient structures with an aim of achieving high performance computing beyond the limits of current CMOS. Due to the stochastic nature of nano-fabrication, nano arrays show different properties both in structural and physical device levels compared to conventional technologies. Mentioned factors introduce random characteristics that need to be carefully considered by synthesis process. For instance, a competent synthesis methodology must consider basic technology preference for switching elements, defect or fault rates of the given nano switching array and the variation values as well as their effects on performance metrics including power, delay, and area. Presented synthesis methodology in this study comprehensively covers the all specified factors and provides optimization algorithms for each step of the process.This work is part of a project that has received funding from the European Union’s H2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 691178, and supported by the TUBITAK-Career project #113E76