tag: machine learning

Improving Medical Image Processing With AI
By Susan Rambo - 04 Nov, 2021 - Comments: 0

Machine learning is being integrated with medical image processing, one of the most useful technologies for medical diagnosis and surgery, greatly expanding the amount of useful information that can be gleaned from scan or MRI. For the most part, ML is being used to augment manual processes that medical personnel use today. While the goal is to automate many of these functions, it's not clea... » read more

ML-based Routing Congestion And Delay Estimation In Vivado ML Edition
By Xilinx - 03 Nov, 2021 - Comments: 0

The FPGA physical design flow offers a compelling opportunity for Machine Learning for CAD (MLCAD) for the following reasons: • An ML solution can be applied wholesale to a device family. • There is a vast data farm that can be harvested from device models and design data from broad applications. • There is a single streamlined design flow that an be instrumented, annotated, and quer... » read more

Competing Auto Sensor Fusion Approaches
By Bryon Moyer - 07 Oct, 2021 - Comments: 0

As today’s internal-combustion engines are replaced by electric/electronic vehicles, mechanical-system sensors will be supplanted by numerous electronic sensors both for efficient operation and for achieving various levels of autonomy. Some of these new sensors will operate alone, but many prominent ones will need their outputs combined — or “fused” — with the outputs of other sensor... » read more

Fan-Out And Packaging Challenges
By Mark LaPedus - 06 Oct, 2021 - Comments: 2

Semiconductor Engineering sat down to discuss various IC packaging technologies, wafer-level and panel-level approaches, and the need for new materials with William Chen, a fellow at ASE; Michael Kelly, vice president of advanced packaging development and integration at Amkor; Richard Otte, president and CEO of Promex, the parent company of QP Technologies; Michael Liu, senior director of globa... » read more

Optimizing AI Systems
By Ed Sperling - 29 Sep, 2021 - Comments: 0

Inserting AI and machine learning into chips adds a whole new dimension of complexity, and creates a variety of potential problems, including deadlocks, loss of performance, and difficulty in achieving closure on many fronts. Gajinder Panesar, fellow at Siemens EDA, talks with Semiconductor Engineering about what’s changed and how to optimize these new devices and systems by monitoring them f... » read more

Software-Hardware Co-Design Becomes Real
By Brian Bailey - 27 Sep, 2021 - Comments: 1

For the past 20 years, the industry has sought to deploy hardware/software co-design concepts. While it is making progress, software/hardware co-design appears to have a much brighter future. In order to understand the distinction between the two approaches, it is important to define some of the basics. Hardware/software co-design is essentially a bottom-up process, where hardware is deve... » read more

Microelectronics And The AI Revolution
By Frank Schirrmeister - 23 Sep, 2021 - Comments: 0

It is no secret that artificial intelligence and machine learning (AI/ML) are critical drivers for growth in electronics, and particularly, for semiconductors. The recent AI Hardware Summit showcased trends in AI/ML, both in enabling and using it in various application domains, including EDA. As part of the summit, Imec had organized a panel on “Advanced Microelectronics Technologies Driving ... » read more

Using ML In EDA
By Ed Sperling - 20 Sep, 2021 - Comments: 0

Machine learning is becoming essential for designing chips due to the growing volume of data stemming from increasing density and complexity. Nick Ni, director of product marketing for AI at Xilinx, examines why machine learning is gaining traction at advanced nodes, where it’s being used today and how it will be used in the future, how quality of results compare with and without ML, and what... » read more

Deploying Artificial Intelligence At The Edge
By Pushkar Apte - 16 Sep, 2021 - Comments: 0

By Pushkar Apte and Tom Salmon Rapid advances in artificial intelligence (AI) have made this technology important for many industries, including finance, energy, healthcare, and microelectronics. AI is driving a multi-trillion-dollar global market while helping to solve some tough societal problems such as tracking the current pandemic and predicting the severity of climate-driven events lik... » read more

Fabs Drive Deeper Into Machine Learning
By Anne Meixner - 07 Sep, 2021 - Comments: 0

Advanced machine learning is beginning to make inroads into yield enhancement methodology as fabs and equipment makers seek to identify defectivity patterns in wafer images with greater accuracy and speed. Each month a wafer fabrication factory produces tens of millions of wafer-level images from inspection, metrology, and test. Engineers must analyze that data to improve yield and to reject... » read more

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