The Next Big Chip Companies

By Ed Sperling - 05 Oct, 2018 - Comments: 1

Rambus’ Mike Noonen looks at why putting everything on a single die no longer works, what comes after Moore’s Law, and what the new business model looks like for chipmakers. https://youtu.be/X6Kca8Vm-wA » read more

Intel’s Next Move

By Ed Sperling - 11 Sep, 2018 - Comments: 0

Gadi Singer, vice president and general manager of Intel's Artificial Intelligence Products Group, sat down with Semiconductor Engineering to talk about Intel's vision for deep learning and why the company is looking well beyond the x86 architecture and one-chip solutions. SE: What's changing on the processor side? Singer: The biggest change is the addition of deep learning and neural ne... » read more

Scalable, Cloud-Ready IC Validator Solution For Advanced DRC Nodes

By Synopsys - 08 Aug, 2018 - Comments: 0

As we move to a data-centric world, semiconductor companies across the globe are working at a furious pace to develop and manufacture Artificial Intelligent [AI] chips. AI is all about an algorithm that mimics a human’s ability to learn and decide. For example, AI can be used to interpret and understand an image that helps a doctor make a better diagnosis for a patient. This requires chips to... » read more

Architecting For AI

By Ann Mutschler - 17 Jul, 2018 - Comments: 0

Semiconductor Engineering sat down to talk about what is needed today to enable artificial intelligence training and inferencing with Manoj Roge, vice president, strategic planning at Achronix; Ty Garibay, CTO at Arteris IP; Chris Rowen, CEO of Babblelabs; David White, distinguished engineer at Cadence; Cheng Wang, senior VP engineering at Flex Logix; and Raik Brinkmann, president and CEO of O... » read more

Machine Learning’s Limits

By Ed Sperling - 03 Jul, 2018 - Comments: 0

Semiconductor Engineering sat down with Rob Aitken, an Arm fellow; Raik Brinkmann, CEO of OneSpin Solutions; Patrick Soheili, vice president of business and corporate development at eSilicon; and Chris Rowen, CEO of Babblelabs. What follows are excerpts of that conversation. To view part one, click here. SE: How much of what goes wrong in machine learning depends on the algorithm being wrong... » read more

IBM Takes AI In Different Directions

By Ed Sperling - 06 Jun, 2018 - Comments: 3

Jeff Welser, vice president and lab director at IBM Research Almaden, sat down with Semiconductor Engineering to discuss what's changing in artificial intelligence and what challenges still remain. What follows are excerpts of that conversation. SE: What's changing in AI and why? Welser: The most interesting thing in AI right now is that we've moved from narrow AI, where we've proven you... » read more

Where The Rubber Hits The Road: Implementing Machine Learning On Silicon

By Dave Pursley - 10 May, 2018 - Comments: 0

Machine learning (ML) is everywhere these days. The common thread between advanced driver-assistance systems (ADAS) vision applications in our cars and the voice (and now facial) recognition applications in our phones is that ML algorithms are doing the heavy lifting, or more accurately, the inferencing. In fact, neural networks (NN) can even be used in application spaces such as file compressi... » read more

When AI Goes Awry

By Ed Sperling - 26 Mar, 2018 - Comments: 0

The race is on to develop intelligent systems that can drive cars, diagnose and treat complex medical conditions, and even train other machines. The problem is that no one is quite sure how to diagnose latent or less-obvious flaws in these systems—or better yet, to prevent them from occurring in the first place. While machines can do some things very well, it's still up to humans to devise... » read more

What’s Next In Neuromorphic Computing

By Katherine Derbyshire - 15 Feb, 2018 - Comments: 2

To integrate devices into functioning systems, it's necessary to consider what those systems are actually supposed to do. Regardless of the application, [getkc id="305" kc_name="machine learning"] tasks involve a training phase and an inference phase. In the training phase, the system is presented with a large dataset and learns how to "correctly" analyze it. In supervised learning, the data... » read more

Customizing Power And Performance

By Ed Sperling - 08 Feb, 2018 - Comments: 0

Designing chips is getting more difficult, and not just for the obvious technical reasons. The bigger issue revolves around what these chips going to be used for-and how will they be used, both by the end user and in the context of other electronics. This was a pretty simple decision when hardware was developed somewhat independently of software, such as in the PC era. Technology generally d... » read more

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Knowledge Centers
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

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

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

Why Small Fab And Assembly Houses Are Thriving

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

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tag: inferencing