The SpiNNaker Project

被引：951

作者：

Furber, Steve B. ^{[1
]}

Galluppi, Francesco ^{[1
]}

Temple, Steve ^{[1
]}

Plana, Luis A. ^{[1
]}

机构：

[1] Univ Manchester, Sch Comp Sci, Manchester M13 9PL, Lancs, England

来源：

PROCEEDINGS OF THE IEEE | 2014年 / 102卷 / 05期

基金：

英国工程与自然科学研究理事会;

关键词：

Brain modeling; multicast algorithms; multiprocessor interconnection networks; neural network hardware; parallel programming; LARGE-SCALE MODEL; ON-CHIP; ARCHITECTURE; SIMULATION;

D O I：

10.1109/JPROC.2014.2304638

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The spiking neural network architecture (SpiNNaker) project aims to deliver a massively parallel million-core computer whose interconnect architecture is inspired by the connectivity characteristics of the mammalian brain, and which is suited to the modeling of large-scale spiking neural networks in biological real time. Specifically, the interconnect allows the transmission of a very large number of very small data packets, each conveying explicitly the source, and implicitly the time, of a single neural action potential or "spike.'' In this paper, we review the current state of the project, which has already delivered systems with up to 2500 processors, and present the real-time event-driven programming model that supports flexible access to the resources of the machine and has enabled its use by a wide range of collaborators around the world.

引用

页码：652 / 665

页数：14

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