Short Article Open Access

Design productivity, compilation and acceleration for data analytic applications

Abstract

 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.

 Deming Chen

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