A Survey on Convolutional Neural Network Accelerators: GPU, FPGA and ASIC-Reference-Cited by-同舟云学术

A Survey on Convolutional Neural Network Accelerators: GPU, FPGA and ASIC

Published:2022-01-07 Issue: Volume: Page:
ISSN:
Container-title:2022 14th International Conference on Computer Research and Development (ICCRD)
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Author:

Hu Yunxiang¹,Liu Yuhao²,Liu Zhuovuan³

Affiliation:

1. Macao University of Science and Technology,Faculty of information Technology,Macao,China

2. Huazhong University of Science and Technology,School of Optical and Electronic Information,Wuhan,China

3. Xi'an Jiaotong-Liverpool University,Department of Electrical and Electronic Engineering,Suzhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9730106/9730125/09730377.pdf?arnumber=9730377

Reference23 articles.

1. Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks?

2. Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks

3. Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays;pouchet;Polyhedral-based Data Reuse Optimization for Configurable Computing,0

4. An electrically trainable artificial neural network (ET ANN) with 10240 floating gate synapses;holler;International Joint Conference on Neural Networks,0

5. DianNao

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