Efficient hardware architectures for accelerating deep neural networks: Survey

P Dhilleswararao, S Boppu, MS Manikandan… - IEEE …, 2022 - ieeexplore.ieee.org
In the modern-day era of technology, a paradigm shift has been witnessed in the areas
involving applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep …

Review of ASIC accelerators for deep neural network

R Machupalli, M Hossain, M Mandal - Microprocessors and Microsystems, 2022 - Elsevier
Deep neural networks (DNNs) have become an essential tool in artificial intelligence, with a
wide range of applications such as computer vision, medical diagnosis, security, robotics …

An updated survey of efficient hardware architectures for accelerating deep convolutional neural networks

M Capra, B Bussolino, A Marchisio, M Shafique… - Future Internet, 2020 - mdpi.com
Deep Neural Networks (DNNs) are nowadays a common practice in most of the Artificial
Intelligence (AI) applications. Their ability to go beyond human precision has made these …

Hardware and software optimizations for accelerating deep neural networks: Survey of current trends, challenges, and the road ahead

M Capra, B Bussolino, A Marchisio, G Masera… - IEEE …, 2020 - ieeexplore.ieee.org
Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning
(DL) is already present in many applications ranging from computer vision for medicine to …

FPGA-based accelerators of deep learning networks for learning and classification: A review

A Shawahna, SM Sait, A El-Maleh - ieee Access, 2018 - ieeexplore.ieee.org
Due to recent advances in digital technologies, and availability of credible data, an area of
artificial intelligence, deep learning, has emerged and has demonstrated its ability and …

An overview of FPGA based deep learning accelerators: challenges and opportunities

T Wang, C Wang, X Zhou… - 2019 IEEE 21st …, 2019 - ieeexplore.ieee.org
With the rapid development of in-depth learning, neural network and deep learning
algorithms have been widely used in various fields, eg, image, video and voice processing …

A survey on convolutional neural network accelerators: GPU, FPGA and ASIC

Y Hu, Y Liu, Z Liu - 2022 14th International Conference on …, 2022 - ieeexplore.ieee.org
In recent years, artificial intelligence (AI) has been under rapid development, applied in
various areas. Among a vast number of neural network (NN) models, the convolutional …

Efficient processing of deep neural networks: A tutorial and survey

V Sze, YH Chen, TJ Yang, JS Emer - Proceedings of the IEEE, 2017 - ieeexplore.ieee.org
Deep neural networks (DNNs) are currently widely used for many artificial intelligence (AI)
applications including computer vision, speech recognition, and robotics. While DNNs …

A survey and taxonomy of FPGA-based deep learning accelerators

AG Blaiech, KB Khalifa, C Valderrama… - Journal of Systems …, 2019 - Elsevier
Deep learning, the fastest growing segment of Artificial Neural Network (ANN), has led to the
emergence of many machine learning applications and their implementation across multiple …

Fast and efficient convolutional accelerator for edge computing

A Ardakani, C Condo, WJ Gross - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Convolutional neural networks (CNNs) are a vital approach in machine learning. However,
their high complexity and energy consumption make them challenging to embed in mobile …