Impact of High-Level Synthesis on Reliability of Artificial Neural Network Hardware Accelerators-Reference-Cited by-同舟云学术

Impact of High-Level Synthesis on Reliability of Artificial Neural Network Hardware Accelerators

Author:

Traiola Marcello¹^ORCID,dos Santos Fernando Fernandes¹^ORCID,Rech Paolo²^ORCID,Cazzaniga Carlo³^ORCID,Sentieys Olivier¹,Kritikakou Angeliki¹^ORCID

Affiliation:

1. Irisa, INRIA, CNRS, University of Rennes, Rennes, France

2. Department of Industrial Engineering, University of Trento, Trento, Italy

3. ISIS Facility, Rutherford Appleton Laboratory, Didcot, U.K.

Funder

European Union’s Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie

Brittany Region and under the RadNext

Agence nationale de la recherche (ANR) Fault-aware timing behaviour for safety-critical multicore Systems

ANR RE-TRUSTING

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

Reference39 articles.

5. Understanding error propagation in deep learning neural network (DNN) accelerators and applications;Li

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