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dc.contributor.authorSze, Vivienne
dc.contributor.authorChen, Yu-Hsin
dc.contributor.authorYang, Tien-Ju
dc.contributor.authorEmer, Joel S
dc.date.accessioned2021-03-09T19:08:18Z
dc.date.available2021-03-09T19:08:18Z
dc.date.issued2020-08
dc.identifier.issn1943-0582
dc.identifier.issn1943-0590
dc.identifier.urihttps://hdl.handle.net/1721.1/130112
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/mssc.2020.3002140en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceProf. Sze via Phoebe Ayersen_US
dc.subjectElectrical and Electronic Engineeringen_US
dc.titleHow to Evaluate Deep Neural Network Processors: TOPS/W (Alone) Considered Harmfulen_US
dc.typeArticleen_US
dc.identifier.citationSze, Vivienne et al. "How to Evaluate Deep Neural Network Processors: TOPS/W (Alone) Considered Harmful." IEEE Solid-State Circuits Magazine 12, 3 (August 2020): 28 - 41. © 2020 IEEEen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Microsystems Technology Laboratoriesen_US
dc.relation.journalIEEE Solid-State Circuits Magazineen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.date.submission2021-03-05T15:32:10Z
mit.journal.volume12en_US
mit.journal.issue3en_US
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusComplete


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