Nature

FPGA-Based Acceleration of Deep Learning Networks

Field programmable gate arrays (FPGAs) have emerged as flexible hardware platforms for accelerating deep learning networks, offering high energy efficiency, low latency and reconfigurable parallelism.
Electropages

SoM board powers vision, sensor, edge and AI applications

CrossLinkU-NX SoM board from Lattice Semiconductor. The SoM Board is optimised for resource‑constrained vision, sensor, edge, ...
Network World

Altera targets low-latency AI edge applications with new FPGA products

Agilex 3 FPGAs also support smart factory cameras to improve defect detection by using fine-grained parallel processing and Convolutional Neural Networks (CNNs) trained for object recognition to ...
InfoWorld

The most popular neural network styles and how they work

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
Semiconductor Engineering

CNN Hardware Architecture With Weights Generator Module That Alleviates Impact Of The Memory Wall

A technical paper titled “Mitigating Memory Wall Effects in CNN Engines with On-the-Fly Weights Generation” was published by researchers at Samsung AI Center and University of Cambridge. “The ...