title: NeuroPipe-Chip: A digital neuro-processor for spiking neural networks.
abstract: Computing complex spiking artificial neural networks (SANNs) on conventional hardware platforms is far from reaching real-time requirements. Therefore we propose a neuro-processor, called NeuroPipe-Chip, as part of an accelerator board. In this paper, we introduce two new concepts on chip-level to speed up the computation of SANNs. These concepts are implemented in a prototype of the NeuroPipe-Chip. We present the hardware structure of the prototype and evaluate its performance in a system simulation based on a hardware description language (HDL). For the computation of a simple SANN for image segmentation, the NeuroPipe-Chip operating at 100 MHz shows an improvement of more than two orders of magnitude compared to an Alpha 500 MHz workstation and approaches real-time requirements for the computation of SANNs in the order of 10(6) neurons. Hence, such an accelerator would allow for applications of complex SANNs to solve real-world tasks like real-time image processing. The NeuroPipe-Chip has been fabricated in an Alcatel 0.35-mum digital CMOS technology.
authors.affiliation: Inst. of Microelectron., Technische Univ. Berlin.
authors.forename: T
authors.initials: T
authors.lastname: Schoenauer
authors.forename: S
authors.initials: S
authors.lastname: Atasoy
authors.forename: N
authors.initials: N
authors.lastname: Mehrtash
authors.forename: H
authors.initials: H
authors.lastname: Klar