A nano‐scale architecture for constant time image processing

Abstract

In this paper, we study a nano‐scale highly parallel computing architecture for image processing: a reconfigurable mesh that is interconnected with ferromagnetic spin‐wave buses. In this architecture, information is encoded into the phase of the spin‐wave, and interommunications are performed without any charge transfer. This spin‐wave reconfigurable mesh, while requiring the same number of switches as standard reconfigurable mesh, is capable of simultaneously transmitting multiple waves on each of the spin‐wave paths using different frequencies. Moreover, in this architecture, the superposition characteristic of spin‐waves allows concurrent writes if all the requesting processors write a “1”. Employing these parallel features, we present three constant time image processing applications for this architecture. We show that given an N1/2 × N1/2 image, using a N × N spin‐wave reconfigurable mesh, in constant time, all figures. can be labelled, and the nearest neighbour, and the convex hull of a single figure can be found. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Efficient parallel processing with spin-wave nanoarchitectures

“…Since the maximum value of the inputs is N , this procedure takes O(log N) time. If the number of inputs is less than or equal to N , the minimum and maximum can be found in O(1) as presented in [38].…”

“…Therefore, the total time complexity of finding the convex hull of a figure will be O(log N). The O(1) time variation of this algorithm for a smaller image size has been presented in [38].…”

Magnonic logic circuits

“…There are other possible schemes proposed for magnetic networks with spin wave bus [19,20]. The main motive of the spin wave-based architectures is to exploit wave phenomena for data transmission and parallel data processing.…”