Social and Behavioral Sciences Commons^™

Bibliometric Review Of Fpga Based Implementation Of Cnn, Priti Shahane, Piyush Tyagi, Purba Saha, Shravan Sainath, Swanand Bedekar

Library Philosophy and Practice (e-journal)

Nowadays Convolution Neural Network (CNN) has become the state of the art for machine learning algorithms due to their high accuracy. However, implementation of CNN algorithms on hardware platforms becomes challenging due to high computation complexity, memory bandwidth and power consumption. Hardware accelerators such as Graphics Processing Unit (GPU), Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC) are suitable platforms to model CNN algorithms. Recently FPGAs have been considered as an attractive platform for CNN implementation. Modern FPGAs have various embedded hardware and software blocks such as a soft processor, DSP slice and memory blocks. These embedded resources …