TY - JOUR
T1 - Brain-Inspired Computing
AU - Furber, Steve B.
N1 - The design and construction of the SpiNNaker machine was supported by EPSRC (the UK Engineering and Physical Sciences Research Council) under grants EP/D07908X/1 and EP/G015740/ 1, in collaboration with the universities of Southampton, Cambridge and Sheffield and with industry partners ARM Ltd, Silistix Ltd and Thales. Ongoing development of the software is supported by the EU ICT Flagship Human Brain Project (FP7-604102), in collaboration with many university and industry partners across the EU and beyond, and our own exploration of the capabilities of the machine is supported by the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement 320689. SpiNNaker has been 15 years in conception and 10 years in construction, and many folk in Manchester and in our various collaborating groups around the world have contributed to get the project to its current state. We gratefully acknowledge all of these contributions.
PY - 2015
Y1 - 2015
N2 - The inner workings of the brain as a biological information processing system remain largely a mystery to science. Yet there is a growing interest in applying what is known about the brain to the design of novel computing systems, in part to explore hypotheses of brain function, but also to see if brain-inspired approaches can point to novel computational systems capable of circumventing the limitations of conventional approaches, particularly in the light of the slowing of the historical exponential progress resulting from Moore’s Law. Although there are, as yet, few compelling demonstrations of the advantages of such approaches in engineered systems, a number of large-scale platforms have been developed recently that promise to accelerate progress both in understanding the biology and in supporting engineering applications. SpiNNaker (Spiking Neural Network Architecture) is one such large-scale example, and much has been learnt in the design, development and commissioning of this machine that will inform future developments in this area.
AB - The inner workings of the brain as a biological information processing system remain largely a mystery to science. Yet there is a growing interest in applying what is known about the brain to the design of novel computing systems, in part to explore hypotheses of brain function, but also to see if brain-inspired approaches can point to novel computational systems capable of circumventing the limitations of conventional approaches, particularly in the light of the slowing of the historical exponential progress resulting from Moore’s Law. Although there are, as yet, few compelling demonstrations of the advantages of such approaches in engineered systems, a number of large-scale platforms have been developed recently that promise to accelerate progress both in understanding the biology and in supporting engineering applications. SpiNNaker (Spiking Neural Network Architecture) is one such large-scale example, and much has been learnt in the design, development and commissioning of this machine that will inform future developments in this area.
U2 - 10.1049/iet-cdt.2015.0171
DO - 10.1049/iet-cdt.2015.0171
M3 - Article
SN - 1751-8601
JO - I E T Computers and Digital Techniques
JF - I E T Computers and Digital Techniques
ER -