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

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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