AI/ML algorithms and applications in VLSI design and technology
An evident challenge ahead for the integrated circuit (IC) industry is the investigation and
development of methods to reduce the design complexity ensuing from growing process …
development of methods to reduce the design complexity ensuing from growing process …
Power-intent systolic array using modified parallel multiplier for machine learning acceleration
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 …
to their efficiency in performing matrix multiplication that is a key primitive in modern ML …
SimuNN: A pre-RTL inference, simulation and evaluation framework for neural networks
Neural networks have been widely deployed in a number of applications due to their strong
learning and feature extraction ability. To meet the ever increasing accuracy requirements …
learning and feature extraction ability. To meet the ever increasing accuracy requirements …
[PDF][PDF] Robust computing for machine learning-based systems
Machine learning (ML) has emerged as the principal tool for performing complex tasks
which are impractical (if not impossible) to code by humans. ML techniques provide …
which are impractical (if not impossible) to code by humans. ML techniques provide …
Exploring an FPGA-Based Edge Computing Solution for Smart Manufacturing Monitoring: A Case Study on Droplet Recognition
C Liu, M Luo - International conference on the Efficiency and …, 2023 - Springer
This study presents a novel droplet recognition method based on Field Programmable Gate
Array (FPGA). Unlike traditional droplet image recognition techniques, this approach offers …
Array (FPGA). Unlike traditional droplet image recognition techniques, this approach offers …