Survey on FPGA-based Accelerators for CNNs

CNNs (convolutional neural networks) have been recently successfully 
applied for a wide range of cognitive challenges. Given high 
computational demands of CNNs, custom hardware accelerators are vital 
for boosting their performance. The high energy-efficiency, computing 
capabilities and reconfigurability of FPGA make it a promising platform 
for hardware acceleration of computation-intensive CNNs.

Our research paper (attached) surveys 75+ techniques for implementing 
and optimizing CNN algorithms on FPGA. Accepted in Neural Computing and 
Applications journal 2018.

We hope that this paper will attract the attention of both developers 
and researchers towards potential of FPGA in accelerating their 
applications.