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Feasibility study of the Software-Based Self Test methodology on a Hardware Accelerator for Neural Networks.-

Lorenzo Zaia

Feasibility study of the Software-Based Self Test methodology on a Hardware Accelerator for Neural Networks.-.

Rel. Paolo Bernardi. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2020

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Abstract:

The general subject of the MS Thesis is the preliminary study about the reliability issues of Hardware Accelerator for Neural Networks and the counteractions that can be taken to detect erroneous behaviours occurring during the mission of the device.

Relators: Paolo Bernardi
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 102
Subjects:
Corso di laurea: Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering)
Classe di laurea: New organization > Master science > LM-32 - COMPUTER SYSTEMS ENGINEERING
Aziende collaboratrici: DOLPHIN DESIGN
URI: http://webthesis.biblio.polito.it/id/eprint/16773
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