Analysing digital in-memory computing for advanced finFET node

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dc.contributor.author Devaraddi, Veerendra S.
dc.contributor.author Mekie, Joycee
dc.date.accessioned 2012-09-29T14:45:09Z
dc.date.available 2012-09-29T14:45:09Z
dc.date.issued 2021-08
dc.identifier.citation Devaraddi, Veerendra S. and Mekie, Joycee, "Analysing digital in-memory computing for advanced finFET node", arXiv, Cornell University Library, DOI: arXiv:2108.00778, Aug. 2021. en_US
dc.identifier.uri http://arxiv.org/abs/2108.00778
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/6790
dc.description.abstract Digital In-memory computing improves energy efficiency and throughput of a data-intensive process, which incur memory thrashing and, resulting multiple same memory accesses in a von Neumann architecture. Digital in-memory computing involves accessing multiple SRAM cells simultaneously, which may result in a bit flip when not timed critically. Therefore we discuss the transient voltage characteristics of the bitlines during an SRAM compute. To improve the packaging density and also avoid MOSFET down-scaling issues, we use a 7-nm predictive PDK which uses a finFET node. The finFET process has discrete fins and a lower Voltage supply, which makes the design of in-memory compute SRAM difficult. In this paper, we design a 6T SRAM cell in 7-nm finFET node and compare its SNMs with a UMC 28nm node implementation. Further, we design and simulate the rest of the SRAM peripherals, and in-memory computation for an advanced finFET node.
dc.description.statementofresponsibility by Veerendra S Devaraddi and Joycee M. Mekie
dc.language.iso en_US en_US
dc.publisher Cornell University Library en_US
dc.title Analysing digital in-memory computing for advanced finFET node en_US
dc.type Pre-Print en_US
dc.relation.journal arXiv


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