AI At The Edge: Optimizing AI Algorithms Without Sacrificing Accuracy

By Ron Lowman - 07 Jul, 2022 - Comments: 0

The ultimate measure of success for AI will be how much it increases productivity in our daily lives. However, the industry has huge challenges in evaluating progress. The vast number of AI applications is in constant churn: finding the right algorithm, optimizing the algorithm, and finding the right tools. In addition, complex hardware engineering is rapidly being updated with many different s... » read more

Brain-Inspired Computing Device That Programs/RePrograms HW On Demand With Electrical Pulses

By Technical Paper Link - 06 Jul, 2022 - Comments: 0

Multiple academic and government institutions jointly developed a new computer device that can "program and program computer hardware on demand through electrical pulses," according to this Argonne National Lab news release. The device's key materials are neodymium, nickel and oxygen and is referred to as a perovskite nickelate. This new research paper titled "Reconfigurable perovskite nicke... » read more

Active Learning: Integrating Natural Intelligence Into Artificial Intelligence

By Oliver Gnepper - 09 Jun, 2022 - Comments: 0

Today, very few people would likely deny the fact that data can present major added value for companies. But analyzing data from production processes reveals the incompleteness of data collection and the associated reduced potential of the data that can be leveraged. Typical shortcomings include: Incomplete representation of processes in the dataspace, Inadequate connection of processes... » read more

AI-Powered Verification

By Brian Bailey - 01 Jun, 2022 - Comments: 1

With functional verification consuming more time and effort than design, the chip industry is looking at every possible way to make the verification process more effective and more efficient. Artificial intelligence (AI) and machine learning (ML) are being tested to see how big an impact they can have. While there is progress, it still appears to be just touching the periphery of the problem... » read more

Is AI Improving A Broken Process?

By Brian Bailey - 26 May, 2022 - Comments: 0

Verification is fundamentally comparing two models, each derived independently, to find out if there are any different behaviors expressed between the two models. One of those models represents the intended design, and the other is part of the testbench. In an ideal flow, the design model would be derived from the specification, and each stage of the design process would be adding other deta... » read more

Improving PPA With AI

By John Koon - 12 May, 2022 - Comments: 0

AI/ML/DL is starting to show up in EDA tools for a variety of steps in the semiconductor design flow, many of them aimed at improving performance, reducing power, and speeding time to market by catching errors that humans might overlook. It's unlikely that complex SoCs, or heterogeneous integration in advanced packages, ever will be perfect at first silicon. Still, the number of common error... » read more

Survey: 2022 Deep Learning Applications

By eBeam Initiative - 16 Mar, 2022 - Comments: 0

The 2022 member list of deep learning projects and products that eBeam members are working on in photomask to wafer semiconductor manufacturing. Participating companies include Advantest, ASML, Canon, CEA-LETI, D2S, Fraunhofer IPMS, Hitachi High-Tech Corporation, imec, NuFlare Technology, Siemens Industries Software, Inc.; Siemens EDA, STMicroelectronics, and TASMIT. Click here to see the su... » read more

Image Processing For Vision AI

By Renesas - 23 Feb, 2022 - Comments: 0

Recent years have seen an increasing need for Vision AI applications using AI to enable real-time image recognition. Vision AI, which substitutes AI for human visual recognition, requires optimal image processing. Renesas has released RZ/V2M as mid-class, and RZ/V2L as an entry class, Vision AI microprocessors (MPUs). Both products are equipped with DRP-AI which is Dynamically Reconfigurable Pr... » read more

Enhancing Datasets For Artificial Intelligence Through Model-Based Methods

By Dirk Mayer - 10 Feb, 2022 - Comments: 0

By Dirk Mayer and Ulf Wetzker Industrial plants and processes are now digitized and networked, and AI can be used to evaluate the data generated by those facilities to increase productivity and quality. Machine learning (ML) methods can be applied to: Product quality classification in complex production processes. Condition monitoring of technical systems, which is used, for examp... » read more

AI Everywhere: Accelerating Chip Design At Every Node

By Geetha Rangarajan - 10 Feb, 2022 - Comments: 0

Over the last few years, artificial Intelligence (AI) has increasingly played a significant role in the chip development process. But, when people talk about AI-designed chips, it is usually in the context of the latest, cutting-edge designs manufactured at advanced process nodes (7/5nm and smaller) and for good reason. Such designs constantly push the bounds of power, performance, and area (PP... » read more

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Entities, people and technologies explored

Shift Left Is The Tip Of The Iceberg

A transformative change is underway for semiconductor design and EDA. New languages, models, and abstractions will need to be created.

by Brian Bailey

Partitioning In The Chiplet Era

Understanding how chiplets interact under different workloads is critical to ensuring signal integrity and optimal performance in heterogeneous designs.

by Ann Mutschler

3.5D: The Great Compromise

Pros and cons of a middle-ground chiplet assembly that combines 2.5D and 3D-IC.

by Ed Sperling

AI’s Role In Chip Design Widens, Drawing In New Startups

Focus is on letting engineers do much more with the same or fewer resources — and less drudgery.

by Karen Heyman

Key Technologies To Extend EUV To 14 Angstroms

Alongside high-NA EUV will be better-performing photoresists, reduced roughness using passivation and etch, and lateral etching to reduce tip-to-tip dimensions.

by Laura Peters

Memory Fundamentals For Engineers

eBook: Nearly everything you need to know about memory, including detailed explanations of the different types of memory; how and where these are used today; what's changing, which memories are successful and which ones might be in the future; and the limitations of each memory type.

by The SE Staff

What Comes After HBM For Chiplets

The standard for high-bandwidth memory limits design freedom at many levels, but that is required for interoperability. What freedoms can be taken from other functions to make chiplets possible?