Area-Aware Decomposition for Single-Electron Transistor Arrays

Abstract

Single-electron transistor (SET) at room temperature has been demonstrated as a promising device for extending Moore’s law due to its ultra-low power consumption. Existing SET synthesis methods synthesize a Boolean network into a large reconfigurable SET array where the height of SET array equals the number of primary inputs. However, recent experiments on device level have shown that this height is restricted to a small number, say, 10, rather than arbitrary value due to the ultra-low driving strength of SET devices. On the other hand, the width of an SET array is also suggested to be a small value. Consequently, it is necessary to decompose a large SET array into a set of small SET arrays where each of them realizes a sub-function of the original circuit with no more than 10 inputs. Thus, this article presents two techniques for achieving area-efficient SET array decomposition: One is a width minimization algorithm for reducing the area of a single SET array; the other is a depth-bounded mapping algorithm, which decomposes a Boolean network into many sub-functions such that the widths of the corresponding SET arrays are balanced. The width minimization algorithm leads to a 25%--41% improvement compared to the state of the art, and the mapping algorithm achieves a 60% reduction in total area compared to a naïve approach.