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Energy-efficient charge sharing-based 8T2C SRAM in-memory accelerator for binary neural networks in 28nm CMOS

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dc.contributor.authorOh, Hyunmyung-
dc.contributor.authorKim, Hyungjun-
dc.contributor.authorAhn, Daehyun-
dc.contributor.authorPark, Jihoon-
dc.contributor.authorKim, Yulhwa-
dc.contributor.authorLee, Inhwan-
dc.contributor.authorKim, Jae-Joon-
dc.date.accessioned2022-10-05T04:09:54Z-
dc.date.available2022-10-05T04:09:54Z-
dc.date.created2022-07-21-
dc.date.issued2021-11-
dc.identifier.citationIEEE ASIAN SOLID-STATE CIRCUITS CONFERENCE (A-SSCC 2021)-
dc.identifier.urihttps://hdl.handle.net/10371/185285-
dc.description.abstractWe present an 8-transistor and 2-capacitor (8T2C) SRAM cell-based in-memory hardware for Binary Neural Network (BNN) computation. The proposed design accumulates multiplication results using a DRAM-like charge sharing operation, which makes it more tolerant to process variations and avoiding issues that hinder low voltage operations of conventional SRAM-CIM designs. Measurement results show that a 256x64 macro implemented in a 28nm CMOS achieves 3182 TOPS/VV at 0.7 V.-
dc.language영어-
dc.publisherIEEE-
dc.titleEnergy-efficient charge sharing-based 8T2C SRAM in-memory accelerator for binary neural networks in 28nm CMOS-
dc.typeArticle-
dc.identifier.doi10.1109/A-SSCC53895.2021.9634784-
dc.citation.journaltitleIEEE ASIAN SOLID-STATE CIRCUITS CONFERENCE (A-SSCC 2021)-
dc.identifier.wosid000768220800062-
dc.identifier.scopusid2-s2.0-85124020370-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorKim, Jae-Joon-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
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