Selective Removal For Stronger Fins

By Matt Cogorno - 21 Mar, 2019 - Comments: 0

By Matt Cogorno and Toshihiko Miyashita Remember when we could charge our mobile phones on a Sunday and not even think about it again until the next weekend? There was a time when battery life wasn’t even in the top ten concerns when purchasing a mobile phone. Today however, smartphones are constantly being used for computing, gaming, video streaming and other power-hungry applications, so... » read more

Multiple Approaches To Memory Challenges

By Ryan Gibson - 21 Feb, 2019 - Comments: 0

As we enter the era of Big Data and Artificial Intelligence (AI), it is amazing to think about the possibilities for a truly seismic shift in the changing requirements for memory solutions. The massive amount of data humans generate every year is astounding and yet is expected to increase five-fold in the next few years from machine-generated data. Further compounding this growth is the emergin... » read more

Keeping Up Power And Performance With Cobalt

By Mehul Naik - 24 Jan, 2019 - Comments: 0

Chip designers require simultaneous improvements in “PPAC”: power, performance and area/cost (Fig. 1). Achieving these improvements is becoming increasingly difficult as classic Moore's Law scaling slows. What's needed is a new playbook for the industry consisting of new materials, new architectures, new 3D structures within the chip, new methods to shrink feature geometries, and advanced p... » read more

What’s Changing In Memory

By Gill Lee - 17 Dec, 2018 - Comments: 0

As emerging big data and artificial intelligence (AI) applications, including machine learning, drive innovations across many industries, the issue of how to advance memory technologies to meet evolving computing requirements presents several challenges for the industry. The mainstream memory technologies, DRAM and NAND flash, have long been reliable industry workhorses, each optimized for s... » read more

A VC View Of The AI Landscape

By Michael Stewart - 15 Nov, 2018 - Comments: 0

In this blog post, I’ll highlight my takeaways from the recent AI Hardware Summit where I participated as a panelist. The conference’s focus on developing hardware accelerators for neural networks and computer vision attracted companies from across the ecosystem – AI chip startups, semiconductor companies, system vendors/OEMs, data center providers, financial services companies and VCs,... » read more

Looking For The Next Big Innovation

By Buvna Ayyagari-Sangamalli - 18 Oct, 2018 - Comments: 0

Never has there been more demand for “The Big Innovation” — one that moves the needle for performance, power and area-cost (PPAC) in a big way — as there is in the current era of AI and machine learning (ML). As summarized in Why AI Workloads Require New Computing Architectures, AI workloads require new architectures to process data. These workloads also call for heterogeneous comp... » read more

A New Type Of Switch

By David Thompson - 20 Sep, 2018 - Comments: 0

Back in July, Applied Materials announced that we’d been selected by the Defense Advanced Research Projects Agency (DARPA) to develop technology for AI. While Applied is engaged on the development of many disruptive technologies, it’s not often that we’re in a position to discuss them in early development. Thanks to the vision of DARPA’s Electronics Resurgence Initiative and their ... » read more

The Materials Side Of AI

By Jonathan Bakke - 16 Aug, 2018 - Comments: 0

As we enter the foundry 7nm and below technology nodes, tungsten fill for contacts has reached the physical limits of scaling and copper used in the lowest level interconnects is facing challenges on multiple fronts. Solving these issues will require a new conducting material, namely cobalt. This transition can enable continued device scaling and less power consumption per computation. Follo... » read more

The Role Of Cobalt In Enabling AI

By Jonathan Bakke - 19 Jul, 2018 - Comments: 0

We are on the cusp of the biggest computing wave yet — the AI era driven by Big Data. Enabling this era will require significant enhancements in processor performance and in the capacity and latency of memory. These requirements are coming at a time when the industry is being increasingly challenged by a slowdown in classic Moore’s Law scaling. What’s needed to continue driving the indust... » read more

What Else Is In A Node?

By Sundeep Bajikar - 21 Jun, 2018 - Comments: 0

In part one of this blog, I reported on the 2018 Industry Strategy Symposium (ISS) where Dan Hutcheson of VLSI Research led a panel with representatives of Synopsys, NVIDIA, Intel, ASML and Applied Materials. The participants discussed how the industry is focused on simultaneously squeezing more capabilities from leading-nodes, inter-nodes and trailing-nodes to drive advances in computing. I to... » 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

NAND Flash Targets 1,000 Layers

New techniques go beyond improved deposition and etching, but challenges stack up, too.

by Bryon Moyer

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

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

New AI Processors Architectures Balance Speed With Efficiency

Hot Chips 24: Large language models ratchet up pressure for sustainable computing and heterogeneous integration; data management becomes key differentiator.

by Ed Sperling

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