Abstrakt

Design productivity, compilation and acceleration for data analytic applications

 Deming Chen

 Deep Neural Networks (DNNs) are computation intensive. Without efficient hardware implementations of DNNs, many promising AI applications will not be practically realizable. In this talk, we will analyze several challenges facing the AI community for mapping DNNs to hardware accelerators. Especially, we will evaluate FPGA's potential role in accelerating DNNs for both the cloud and edge devices.

Indiziert in

Chemical Abstracts Service (CAS)
Google Scholar
Open J Gate
Academic Keys
ResearchBible
The Global Impact Factor (GIF)
CiteFactor
Kosmos IF
Elektronische Zeitschriftenbibliothek
RefSeek
Hamdard-Universität
Weltkatalog wissenschaftlicher Zeitschriften
IndianScience.in
Gelehrter
Publons
International Innovative Journal Impact Factor (IIJIF)
Internationales Institut für organisierte Forschung (I2OR)
Kosmos

Mehr sehen