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An exploration of neuromorphic systems and related design issues/challenges in dark silicon era

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dc.contributor.author Chaturvedi, Nitin
dc.date.accessioned 2023-03-15T06:54:02Z
dc.date.available 2023-03-15T06:54:02Z
dc.date.issued 2017
dc.identifier.uri https://iopscience.iop.org/article/10.1088/1757-899X/331/1/012003
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9735
dc.description.abstract The current microprocessors has shown a remarkable performance and memory capacity improvement since its innovation. However, due to power and thermal limitations, only a fraction of cores can operate at full frequency at any instant of time irrespective of the advantages of new technology generation. This phenomenon of under-utilization of microprocessor is called as dark silicon which leads to distraction in innovative computing. To overcome the limitation of utilization wall, IBM technologies explored and invented neurosynaptic system chips. It has opened a wide scope of research in the field of innovative computing, technology, material sciences, machine learning etc. In this paper, we first reviewed the diverse stages of research that have been influential in the innovation of neurosynaptic architectures. These, architectures focuses on the development of brain-like framework which is efficient enough to execute a broad set of computations in real time while maintaining ultra-low power consumption as well as area considerations in mind. We also reveal the inadvertent challenges and the opportunities of designing neuromorphic systems as presented by the existing technologies in the dark silicon era, which constitute the utmost area of research in future. en_US
dc.language.iso en en_US
dc.publisher IOP en_US
dc.subject EEE en_US
dc.subject Silicon era en_US
dc.subject Neuromorphic systems en_US
dc.title An exploration of neuromorphic systems and related design issues/challenges in dark silicon era en_US
dc.type Article en_US


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