A survey on neural network hardware accelerators

T Mohaidat, K Khalil - IEEE Transactions on Artificial …, 2024 - ieeexplore.ieee.org
Artificial intelligence (AI) hardware accelerator is an emerging research for several
applications and domains. The hardware accelerator's direction is to provide high …

Fully parallel stochastic computing hardware implementation of convolutional neural networks for edge computing applications

CF Frasser, P Linares-Serrano… - … on Neural Networks …, 2022 - ieeexplore.ieee.org
Edge artificial intelligence (AI) is receiving a tremendous amount of interest from the
machine learning community due to the ever-increasing popularization of the Internet of …

Power-intent systolic array using modified parallel multiplier for machine learning acceleration

K Inayat, FB Muslim, J Iqbal, SA Hassnain Mohsan… - Sensors, 2023 - mdpi.com
Systolic arrays are an integral part of many modern machine learning (ML) accelerators due
to their efficiency in performing matrix multiplication that is a key primitive in modern ML …

A high-performance pixel-level fully pipelined hardware accelerator for neural networks

Z Li, Z Zhang, J Hu, Q Meng, X Shi… - … on Neural Networks …, 2024 - ieeexplore.ieee.org
The design of convolutional neural network (CNN) hardware accelerators based on a single
computing engine (CE) architecture or multi-CE architecture has received widespread …

DCP-CNN: Efficient Acceleration of CNNs With Dynamic Computing Parallelism on FPGA

K Dai, Z ** of Downward Shortwave Radiation from GOES-R Using Gradient Boosting
S Ranjbar, D Losos, S Hoffman… - IEEE Journal of Selected …, 2024 - ieeexplore.ieee.org
This study investigates high-frequency map** of downward shortwave radiation (DSR) at
the Earth's surface using the advanced baseline imager (ABI) instrument mounted on …

Table-Lookup MAC: Scalable Processing of Quantised Neural Networks in FPGA Soft Logic

D Gerlinghoff, BCM Choong, RSM Goh… - Proceedings of the …, 2024 - dl.acm.org
Recent advancements in neural network quantisation have yielded remarkable outcomes,
with three-bit networks reaching state-of-the-art full-precision accuracy in complex tasks …

Fast inner-product algorithms and architectures for deep neural network accelerators

TE Pogue, N Nicolici - IEEE Transactions on Computers, 2023 - ieeexplore.ieee.org
We introduce a new algorithm called the Free-pipeline Fast Inner Product (FFIP) and its
hardware architecture that improve an under-explored fast inner-product algorithm (FIP) …

Accelerating Bayesian neural networks via algorithmic and hardware optimizations

H Fan, M Ferianc, Z Que, X Niu… - … on Parallel and …, 2022 - ieeexplore.ieee.org
Bayesian neural networks (BayesNNs) have demonstrated their advantages in various
safety-critical applications, such as autonomous driving or healthcare, due to their ability to …