Nature

Neural architecture search for in-memory computing-based deep learning accelerators

The rapid growth of artificial intelligence and the increasing complexity of neural network models are driving demand for efficient hardware architectures that can address power-constrained and ...
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.
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 ...