2-input 4-output Programmable Spin Wave Logic Gate

TL;DR

This paper introduces a novel 4-output programmable spin wave logic gate that can evaluate multiple Boolean functions with intrinsic fanout, energy efficiency, and reconfigurability, advancing spin wave computing technology.

Contribution

It proposes a reconfigurable 4-output spin wave logic gate capable of evaluating various Boolean functions with fanout and energy balancing, validated through micromagnetic simulations.

Findings

Achieves 3x energy reduction over conventional SW gates.

Provides 16x energy savings compared to 16nm CMOS implementations.

Demonstrates flexible Boolean function evaluation with fanout capabilities.

Abstract

To bring Spin Wave (SW) based computing paradigm into practice and develop ultra low power Magnonic circuits and computation platforms, one needs basic logic gates that operate and can be cascaded within the SW domain without requiring back and forth conversion between the SW and voltage domains. To achieve this, SW gates have to possess intrinsic fanout capabilities, be input-output data representation coherent, and reconfigurable. In this paper, we address the first and the last requirements and propose a novel 4-output programmable SW logic. First, we introduce the gate structure and demonstrate that, by adjusting the gate output detection method, it can parallelly evaluate any 4-element subset of the 2-input Boolean function set AND, NAND, OR, NOR, XOR, and XNOR. Furthermore, we adjust the structure such that all its 4 outputs produce SWs with the same energy and demonstrate that it can evaluate Boolean function sets while providing fanout capabilities ranging from 1 to 4. We validate our approach by instantiating and simulating different gate configurations such as 4-output AND/OR, 4-output XOR/XNOR, output energy balanced 4-output AND/OR, and output energy balanced 4-output XOR/XNOR by means of Object Oriented Micromagnetic Framework (OOMMF) simulations. Finally, we evaluate the performance of our proposal in terms of delay and energy consumption and compare it against existing state-of-the-art SW and 16nm CMOS counterparts. The results indicate that for the same functionality, our approach provides 3x and 16x energy reduction, when compared with conventional SW and 16nm CMOS implementations, respectively.