Cortical Models Onto CMOL and CMOS— Architectures and Performance/Price

摘要

Here we introduce a highly simplified model of the neocortex based on spiking neurons, and then investigate various mappings of this model to the CMOL CrossNet nanogrid nanoarchitecture. The performance/price is estimated for several architectural configurations both with and without nanoscale circuits. In this analysis we explore the time multiplexing of computational hardware for a pulse-based variation of the model. Our analysis demonstrates that the mixed-signal CMOL implementation has the best performance/price in both nonspiking and spiking neural models. However, these circuits also have serious power density issues when interfacing the nanowire crossbars to analog CMOS circuits. Although the results presented here are based on biologically based computation, the use of pulse-based data representation for nanoscale circuits has much potential as a general architectural technique for a range of nanocircuit implementation.