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Design and fabrication of neuromorphic devices towards emulating artificial intelligence

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dc.contributor.advisor Kulkarni, G.U.
dc.contributor.author B, Bharath
dc.date.accessioned 2021-07-16T10:49:24Z
dc.date.available 2021-07-16T10:49:24Z
dc.date.issued 2020
dc.identifier.citation B, Bharath. 2020, Design and fabrication of neuromorphic devices towards emulating artificial intelligence, Ph.D thesis, Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru en_US
dc.identifier.uri https://libjncir.jncasr.ac.in/xmlui/handle/123456789/3125
dc.description Open access en_US
dc.description.abstract Artificial Intelligence (AI) aims to simulate human intelligence in machines so that they can think like humans, and perform human-like cognition [1]. Although the present-day supercomputers can perform excellent calculations, they are very slow and inefficient compared to the human brain! [2,3] For example, a supercomputer takes around 500 s to emulate 5 s of human brain activity by consuming ~ MWs of energy [4]. This is much due to the conventional von Neumann computer architecture, where the memory and processing units are physically separate and are connected by limited interconnects known as bus bars [5,6]. During processing, data shuttles between these units, which makes the process slow and inefficient. Besides, limited transistor density in a processor chip also influences the computational ability. Although the advancing lithography technique is endeavoring to miniaturize transistors to the lowest dimension possible [7] to create a high density on board, the computational performance is still under satisfying. As the transistor scaling down approaches the theoretical limit, their packing density in a chip may not hold the famous Moore’s law any further [8]. en_US
dc.language English en
dc.language.iso English en_US
dc.publisher Jawaharlal Nehru Centre for Advanced Scientific Research en_US
dc.subject Neuromorphic devices en_US
dc.title Design and fabrication of neuromorphic devices towards emulating artificial intelligence en_US
dc.type Thesis en_US
dc.type.qualificationlevel Doctoral en_US
dc.type.qualificationname Ph.D en_US
dc.publisher.department Chemistry and Physics of Materials Unit (CPMU) en_US


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