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 |
|