File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Implementation of Discrete Fourier Transform using RRAM Arrays with Quasi-Analog Mapping for High-Fidelity Medical Image Reconstruction

TitleImplementation of Discrete Fourier Transform using RRAM Arrays with Quasi-Analog Mapping for High-Fidelity Medical Image Reconstruction
Authors
Issue Date2021
Citation
Technical Digest - International Electron Devices Meeting, IEDM, 2021, v. 2021-December, p. 12.4.1-12.4.4 How to Cite?
AbstractIn this paper, we report the first experimental implementation of discrete Fourier transform (DFT) on analog resistive switching random-Access memory (RRAM) arrays with computing-in-memory (CIM). Considering the features of transform matrix, we developed a novel conductance mapping strategy, namely quasi-Analog mapping (QAM), to realize high-precision mapping by taking advantage of the analog switching characteristics of our RRAM. Based on the RRAM-based DFT models, high-fidelity medical image reconstruction was further demonstrated, achieving a software-comparable peak signal-To-noise ratio (PSNR) of 26.1 dB. Compared to the commonly used quantized mapping (QM), QAM enhanced the image reconstruction quality and showed strong robustness to RRAM read noise. RRAM-implemented DFT also achieved ~128× higher energy efficiency than CPU. This work provides a general strategy for using RRAM array with CIM feature to accelerate signal processing algorithms.
Persistent Identifierhttp://hdl.handle.net/10722/334819
ISSN
2023 SCImago Journal Rankings: 1.047
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhao, Han-
dc.contributor.authorLiu, Zhengwu-
dc.contributor.authorTang, Jianshi-
dc.contributor.authorGao, Bin-
dc.contributor.authorZhou, Ying-
dc.contributor.authorYao, Peng-
dc.contributor.authorXi, Yue-
dc.contributor.authorQian, He-
dc.contributor.authorWu, Huaqiang-
dc.date.accessioned2023-10-20T06:50:58Z-
dc.date.available2023-10-20T06:50:58Z-
dc.date.issued2021-
dc.identifier.citationTechnical Digest - International Electron Devices Meeting, IEDM, 2021, v. 2021-December, p. 12.4.1-12.4.4-
dc.identifier.issn0163-1918-
dc.identifier.urihttp://hdl.handle.net/10722/334819-
dc.description.abstractIn this paper, we report the first experimental implementation of discrete Fourier transform (DFT) on analog resistive switching random-Access memory (RRAM) arrays with computing-in-memory (CIM). Considering the features of transform matrix, we developed a novel conductance mapping strategy, namely quasi-Analog mapping (QAM), to realize high-precision mapping by taking advantage of the analog switching characteristics of our RRAM. Based on the RRAM-based DFT models, high-fidelity medical image reconstruction was further demonstrated, achieving a software-comparable peak signal-To-noise ratio (PSNR) of 26.1 dB. Compared to the commonly used quantized mapping (QM), QAM enhanced the image reconstruction quality and showed strong robustness to RRAM read noise. RRAM-implemented DFT also achieved ~128× higher energy efficiency than CPU. This work provides a general strategy for using RRAM array with CIM feature to accelerate signal processing algorithms.-
dc.languageeng-
dc.relation.ispartofTechnical Digest - International Electron Devices Meeting, IEDM-
dc.titleImplementation of Discrete Fourier Transform using RRAM Arrays with Quasi-Analog Mapping for High-Fidelity Medical Image Reconstruction-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/IEDM19574.2021.9720547-
dc.identifier.scopuseid_2-s2.0-85126912771-
dc.identifier.volume2021-December-
dc.identifier.spage12.4.1-
dc.identifier.epage12.4.4-
dc.identifier.isiWOS:000812325400052-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats