tag: machine learning

New Ways To Improve EDA Productivity
By Ann Mutschler - 24 Apr, 2025 - Comments: 0

EDA vendors are taking aim at new ways to improve the productivity of design and verification engineers, who are struggling to keep pace with exponential increases in chip complexity in tight time-to-market windows and with constrained engineering talent pipelines. In the past, progress often was as straightforward as improving algorithms or parallelizing computations in a linear flow. But w... » read more

Discovering Digital Twins: A Complete Guide
By Ansys - 09 Apr, 2025 - Comments: 0

As artificial intelligence (AI) and machine learning (ML) continue to revolutionize industries, their integration with simulation is amplifying the capabilities of digital twins. AI/ML, simulation, and reduced-order modeling (ROM) technologies combine to create hybrid digital twins—virtual replicas that blend data-driven insights with the accuracy of physics-based models. This powerful approa... » read more

GenAI for Analog IC Design (McMaster University)
By Technical Paper Link - 08 Apr, 2025 - Comments: 0

A new technical paper titled "Generative AI for Analog Integrated Circuit Design: Methodologies and Applications" was published by researchers at McMaster University. Abstract "Electronic Design Automation (EDA) in analog Integrated Circuits (ICs) has been the focus of extensive research; however, unlike its digital counterpart, it has not achieved widespread adoption. In this systematic re... » read more

The Optical Implementation of Backpropagation (Oxford, Lumai)
By Technical Paper Link - 07 Mar, 2025 - Comments: 0

A technical paper titled "Training neural networks with end-to-end optical backpropagation" was published by researchers at University of Oxford and Lumai Ltd. Abstract "Optics is an exciting route for the next generation of computing hardware for machine learning, promising several orders of magnitude enhancement in both computational speed and energy efficiency. However, reaching the full... » read more

What Scares Chip Engineers About Generative AI
By Adam Kovac - 26 Feb, 2025 - Comments: 0

Experts At The Table: LLMs and other generative AI programs are a long way away from being able to design entire chips on their own from scratch, but the emergence of the tech has still raised some genuine concerns. Semiconductor Engineering sat down with a panel of experts, which included Rod Metcalfe, product management group director at Cadence; Syrus Ziai, vice-president of engineering at E... » read more

Machine Learning-Based IR Drop Prediction Approach
By Technical Paper Link - 25 Feb, 2025 - Comments: 0

A new technical paper titled "Estimating Voltage Drop: Models, Features and Data Representation Towards a Neural Surrogate" was published by researchers at KTH Royal Institute of Technology and Ericsson Research. ABSTRACT "Accurate estimation of voltage drop (IR drop) in modern Application-Specific Integrated Circuits (ASICs) is highly time and resource demanding, due to the growing complex... » read more

EUV’s Future Looks Even Brighter
By Gregory Haley - 20 Feb, 2025 - Comments: 1

The rapidly increasing demand for advanced-node chips to support everything-AI is putting pressure on the industry's ability to meet demand. The need for cutting-edge semiconductors is accelerating in applications ranging from hyperscale data centers powering large language models to edge AI in smartphones, IoT devices, and autonomous systems. But manufacturing those chips relies heavily on ... » read more

IC Equipment Communication Standards Struggle As Data Volumes Grow
By Anne Meixner - 11 Feb, 2025 - Comments: 0

The tsunami of data produced during wafer fabrication cannot be effectively leveraged without standards. They determine how data is accessed from equipment, which users need data access and when, and how fast it can be delivered. On top of that, best practices in data governance and data quality are needed to effectively interpret collected data and transfer results. When fab automation and ... » read more

Using AI In Semiconductor Inspection
By Ed Sperling - 05 Feb, 2025 - Comments: 0

AI is exceptionally good at spotting anomalies in semiconductor inspection. The challenge is training different models for different inspection tools and topographies, and knowing which model to use at any particular time. Different textures in backgrounds are difficult for traditional algorithms, for example. But once machine learning models are trained properly, they have proven effective in ... » read more

AI In Data Management Has Limits
By Adam Kovac - 03 Feb, 2025 - Comments: 0

AI algorithms are being integrated into a growing number of EDA tools to automate different aspects of data management, but they also are forcing discussions about just how much decision-making should be turned over to machines and when that should happen. The ability of AI to sort through enormous amounts of design data to find patterns, both good and bad, is well recognized at this point. ... » read more

← Older posts

  • Sponsors

About

Navigation

Connect With Us

Copyright ©2013-2025 SMG   |  Terms of Service  |  Privacy Policy