Guest Editor Introduction: Special Issue on Nano/Bio-Inspired Applications and Architectures

Abstract

The field of computing today is faced with a major challenge—how to efficiently design and implement computing systems to solve tomorrow’s complex problems? Architects recognize that biology is a valuable source of inspiration for efficiently solving many complex problems in architecture, networks, and nanoscale systems. Designers also recognize the importance of nanotechnology for efficient implementation of computing systems. Recent trends suggest a significant shift in research focus towards biologically inspired computing and nanotechnology. This special issue contains four excellent papers on the topics related to nano/bio-inspired applications and architectures. The first two papers address the challenges associated withmodeling and validation of complex biological systems. In the first paper, “Brain Derived Vision Algorithm on High Performance Architectures”, Nageswaran et al. exploit the features of modern microprocessors to efficiently model and implement massively parallel brain systems. This paper describes the details of a brain derived vision algorithm that is derived from the anatomical structure, and physiological operating principles of thalamo-cortical brain circuits. The authors show that many characteristics of the algorithm lend themselves to implementation on IBM CELL architecture, and yield significant speedups that equal or exceed the performance of specialized solutions such as FPGAs, and thus enabling real-time object recognition for robotic systems. In the second paper, “On-Line Testing of Lab-on-Chip Using Reconfigurable Digital-Microfluidic Compactors”, Zhao and Chakrabarty present an online-testing method to improve dependability of microfluidic lab-on-chip devices. Dependability is an essential system attribute for such devices since they are expected to be deployed