ToPoliNano: Nanoarchitectures Design Made Real

Many facts about emerging nanotechnologies are yet to be assessed. There are still major concerns, for instance, about maximum achievable device density, or about which architecture is best fit for a specific application. Growing complexity requires taking into account many aspects of technology, application and architecture at the same time. Researchers face problems that are not new per se, but are now subject to very different constraints, that need to be captured by design tools. Among the emerging nanotechnologies, two-dimensional nanowire based arrays represent promising nanostructures, especially for massively parallel computing architectures. Few attempts have been done, aimed at giving the possibility to explore architectural solutions, deriving information from extensive and reliable nanoarray characterization. Moreover, in the nanotechnology arena there is still not a clear winner, so it is important to be able to target different technologies, not to miss the next big thing. We present a tool, ToPoliNano, that enables such a multi-technological characterization in terms of logic behavior, power and timing performance, area and layout constraints, on the basis of specific technological and topological descriptions. This tool can aid the design process, beside providing a comprehensive simulation framework for DC and timing simulations, and detailed power analysis. Design and simulation results will be shown for nanoarray-based circuits. ToPoliNano is the first real design tool that tackles the top down design of a circuit based on emerging technologie

The challenges of nanostructures for theory

It is tempting to believe that modelling in nanotechnology is much the same as that for conventional solid-state physics. However, important areas of nanotechnology address different systems. The mechanics of DNA (for instance) resembles spaghetti more than silicon, the statistical physics needed is often not carrier statistics, and the role of viscosity (the low Reynolds number limit) is not always the familiar one. The idea of equilibrium may be irrelevant, as the kinetics of nonequilibrium (perhaps quasi-steady state) can be crucial. Even when the issues are limited to nanoscale structures (rather than functions), there is a complex range of ideas. Some features, like elasticity and electrostatic energies, have clear macroscopic analogies, but different questions emerge, such as the accuracy of self-organisation. Others concepts like epitaxy and templating are usually micro- or mesostructural. Some of the ideas, which emerge in modelling for the nanoscale, suggest parallels between molecular motors and recombination enhanced diffusion in semiconductors. (C) 2002 Elsevier Science B.V. All rights reserved

Highly Scalable Neuromorphic Hardware with 1-bit Stochastic nano-Synapses

Thermodynamic-driven filament formation in redox-based resistive memory and the impact of thermal fluctuations on switching probability of emerging magnetic switches are probabilistic phenomena in nature, and thus, processes of binary switching in these nonvolatile memories are stochastic and vary from switching cycle-to-switching cycle, in the same device, and from device-to-device, hence, they provide a rich in-situ spatiotemporal stochastic characteristic. This work presents a highly scalable neuromorphic hardware based on crossbar array of 1-bit resistive crosspoints as distributed stochastic synapses. The network shows a robust performance in emulating selectivity of synaptic potentials in neurons of primary visual cortex to the orientation of a visual image. The proposed model could be configured to accept a wide range of nanodevices.Comment: 9 pages, 6 figure