Work-in-Progress: Ultra-fast yet Accurate Performance Prediction for Deep Neural Network Accelerators

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dc.contributor.author Bringmann, Oliver
dc.date.accessioned 2023-05-19T05:11:00Z
dc.date.available 2023-05-19T05:11:00Z
dc.date.issued 2022-11-02
dc.identifier.isbn 978-1-6654-7296-8
dc.identifier.issn 2643-1726
dc.identifier.uri http://hdl.handle.net/10900/141252
dc.language.iso en de_DE
dc.publisher IEEE de_DE
dc.relation.uri https://doi.org/10.1109/CASES55004.2022.00020 de_DE
dc.subject.ddc 004 de_DE
dc.title Work-in-Progress: Ultra-fast yet Accurate Performance Prediction for Deep Neural Network Accelerators de_DE
dc.type Article de_DE
dc.type ConferenceObject de_DE
utue.personen.roh Lübeck, Konstantin
utue.personen.roh Jung, Alexander Louia-Ferdinand
utue.personen.roh Wedlich, Felix
utue.personen.roh Bringmann, Oliver
dcterms.isPartOf.ZSTitelID 2022 International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (CASES) de_DE


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