  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.
