Using AI To Close Coverage Gaps

By Ed Sperling - 26 Jul, 2023 - Comments: 0

Verification of complex, heterogeneous chips is becoming much more difficult and time-consuming. There are more corner cases, and devices have to last longer and behave according to spec throughout their lifetimes. This is where AI fits in. It can help identify redundancy and provide information about why a particular device or block may not be able to be fully covered, and it can do it in less... » read more

Will Markets For ML Models Materialize?

By Bryon Moyer - 02 Dec, 2021 - Comments: 0

Developers are spending increasing amounts of time and effort in creating machine-learning (ML) models for use in a wide variety of applications. While this will continue as the market matures, at some point some of these efforts might be seen as reinventing models over and over. Will developers of successful models ever have a marketplace in which they can sell those models as IP to other d... » read more

Easier And Faster Ways To Train AI

By Bryon Moyer - 04 Nov, 2021 - Comments: 0

Training an AI model takes an extraordinary amount of effort and data. Leveraging existing training can save time and money, accelerating the release of new products that use the model. But there are a few ways this can be done, most notably through transfer and incremental learning, and each of them has its applications and tradeoffs. Transfer learning and incremental learning both take pre... » read more

AI In Chip Manufacturing

By Ed Sperling - 10 Jan, 2019 - Comments: 0

Ira Leventhal, New Concept Product Initiative vice president at Advantest, talks with Semiconductor Engineering about using analysis and deep learning to make test more efficient and more effective. https://youtu.be/3VVG4JVnjHo » read more

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Entities, people and technologies explored

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

Legacy Process Nodes Going Strong

The critical, and growing, significance of mature node chips and processes.

by Bryon Moyer

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?

by Brian Bailey

Why Small Fab And Assembly Houses Are Thriving

Megafabs churning out the most advanced processors are not the only game in town.

by Bryon Moyer

tag: transfer learning

Using AI To Close Coverage Gaps

Will Markets For ML Models Materialize?

Easier And Faster Ways To Train AI

AI In Chip Manufacturing

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