Bio-inspired massively parallel architectures for nanotechnologies

Massively parallel single-chip multiprocessors (CMP) share a number of traits with biological systems such as neural networks. These biological systems have therefore inspired a number of concepts that may help to overcome some of the problems that will come up in future circuit technologies. In this work we present a first comparison of CMPs based on processor cores of different complexity and estimate the efficiency of CMPs with regards to overall performance and energy consumption. The analysis is based on an analytical model of chip multiprocessing that can help to estimate the runtime and energy consumption of different parallel algorithms. As in previous work we will use the GigaNetIC(1) architecture as a basis for the different CMP architectures.