Abstract
By their very nature, Spin Waves (SWs) with different frequencies can
propagate through the same waveguide without affecting each other, while
only interfering with their own species. Therefore, more SW encoded data
sets can coexist, propagate, and interact in parallel, which opens the
road towards hardware replication free parallel data processing. In this
paper, we take advantage of these features and propose a novel data
parallel spin wave based computing approach. To explain and validate the
proposed concept, byte-wide 2-input XOR and 3-input Majority gates are
implemented and validated by means of Object Oriented MicroMagnetic
Framework (OOMMF) simulations. Furthermore, we introduce an optimization
algorithm meant to minimize the area overhead associated with
multifrequency operation and demonstrate that it diminishes the
byte-wide gate area by 30% and 41% for XOR and Majority
implementations, respectively. To get inside on the practical
implications of our proposal we compare the byte-wide gates with
conventional functionally equivalent scalar SW gate based
implementations in terms of area, delay, and power consumption. Our
results indicate that the area optimized 8-bit 2-input XOR and 3-input
Majority gates require 4.47x and 4.16x less area, respectively, at the
expense of 5% and 7% delay increase, respectively, without inducing
any power consumption overhead. Finally, we discuss factors that are
limiting the currently achievable parallelism to 8 for phase based gate
output detection and demonstrate by means of OOMMF simulations that this
can be increased 16 for threshold based detection based gates.