tag: AI

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

HBM3 Memory: Break Through To Greater Bandwidth
By Rambus - 06 Oct, 2021 - Comments: 0

AI/ML’s demands for greater bandwidth are insatiable driving rapid improvements in every aspect of computing hardware and software. HBM memory is the ideal solution for the high bandwidth requirements of AI/ML training, but it entails additional design considerations given its 2.5D architecture. Now we’re on the verge of a new generation of HBM that will raise memory and capacity to new hei... » 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

EDA Vendors Widen Use Of AI
By Ed Sperling - 29 Sep, 2021 - Comments: 0

EDA vendors are widening the use of AI and machine learning to incorporate multiple tools, providing continuity and access to consistent data at multiple points in the semiconductor design flow. While gaps remain, early results from a number of EDA tools providers point to significant improvements in performance, power, and time to market. AI/ML has been deployed for some time in EDA. Still,... » 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

Optimization Driving Changes In Microarchitectures
By Ann Mutschler - 23 Sep, 2021 - Comments: 0

The semiconductor ecosystem is at a turning point for how to best architect the CPU based on the explosion of data, the increased usage of AI, and the need for differentiation and customization in leading-edge applications. In the past, much of this would have been accomplished by moving to the next process node. But with the benefits from scaling diminishing at each new node, the focus is s... » 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

Building Complex Chips That Last Longer
By Ed Sperling - 23 Sep, 2021 - Comments: 0

Semiconductor Engineering sat down to talk about design challenges in advanced packages and nodes with John Lee, vice president and general manager for semiconductors at Ansys; Shankar Krishnamoorthy, general manager of Synopsys' Design Group; Simon Burke, distinguished engineer at Xilinx; and Andrew Kahng, professor of CSE and ECE at UC San Diego. This discussion was held at the Ansys IDEAS co... » 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

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