System Bits: Nov. 28

By Ann Mutschler - 28 Nov, 2017 - Comments: 0

Better absorbing materials  University of Illinois bioengineers have taken a new look at an old tool to help characterize a class of materials called metal organic frameworks (MOFs), used to detect, purify and store gases. The team believes these could help solve some of the world's most challenging energy, environmental and pharmaceutical challenges – and even pull water molecules straigh... » read more

System Bits: Nov. 21

By Ann Mutschler - 21 Nov, 2017 - Comments: 0

MIT-Lamborghini to develop electric car Members of the MIT community were recently treated to a glimpse of the future as they passed through the Stata Center courtyard as the Lamborghini Terzo Millenio (Third Millennium) was in view, which is an automobile prototype for the third millennium. [caption id="attachment_429209" align="alignnone" width="300"] Lamborghini is relying on MIT to make i... » read more

Power/Performance Bits: Nov. 7

By Jesse Allen - 07 Nov, 2017 - Comments: 0

Speeding up MRAM Researchers at UC Berkeley and UC Riverside developed an ultrafast method for electrically controlling magnetism in certain metals, which could lead to increased performance for magnetic RAM. While the nonvolatility of MRAM is a boon, speeding up the writing of a single bit of information to less than 10 nanoseconds has been a challenge. “The development of a non-volatile... » read more

Power/Performance Bits: Oct. 31

By Jesse Allen - 31 Oct, 2017 - Comments: 0

Battery material supplies Researchers at MIT, the University of California at Berkeley, and the Rochester Institute of Technology conducted an analysis of whether there are enough raw materials to support increased lithium-ion battery production, expected to grow significantly due to electric vehicles and grid-connected battery systems. They conclude that while in the near future there shou... » read more

Deep Learning Robust Grasps with Synthetic Point Clouds & Analytic Grasp Metrics (UC Berkeley)

By Technical Paper Link - 28 Jun, 2017 - Comments: 0

Source: The research was the work of Jeffrey Mahler, Jacky Liang, Sherdil Niyaz, Michael Laskey, Richard Doan, Xinyu Liu, Juan Aparicio Ojea, and Ken Goldberg with support from the AUTOLAB team at UC Berkeley. Nimble-fingered robots enabled by deep learning Grabbing awkwardly shaped items that humans regularly pick up daily is not so easy for robots, as they don’t know where to apply grip... » read more

System Bits: June 13

By Ann Mutschler - 13 Jun, 2017 - Comments: 0

Nimble-fingered robots enabled by deep learning Grabbing awkwardly shaped items that humans regularly pick up daily is not so easy for robots, as they don’t know where to apply grip. To overcome this, UC Berkeley researchers have a built a robot that can pick up and move unfamiliar, real-world objects with a 99% success rate. Berkeley professor Ken Goldberg, postdoctoral researcher Jeff M... » read more

RISC-V Pros And Cons

By Ann Mutschler - 29 May, 2017 - Comments: 7

Simpler, faster, lower-power hardware with a free, open, simple instruction set architecture? While it sounds too good to be true, efforts are underway to do just that with RISC-V, the instruction-set architecture (ISA) developed by UC Berkeley engineers and now administered by a foundation. It has been known for some time that with [getkc id="74" comment="Moore's Law"] not offering the same... » read more

Speeding Up Neural Networks

By Ed Sperling - 27 Apr, 2017 - Comments: 2

Neural networking is gaining traction as the best way of collecting and moving critical data from the physical world and processing it in the digital world. Now the question is how to speed up this whole process. But it isn't a straightforward engineering challenge. Neural networking itself is in a state of almost constant flux and development, which makes it something of a moving target. Th... » read more

System Bits: March 14

By Ann Mutschler - 14 Mar, 2017 - Comments: 0

Neuromorphic computing While for five decades, Moore’s law held up pretty well, today, transistors and other electronic components are so small they’re beginning to bump up against fundamental physical limits on their size, and because Moore’s law has reached its end, it’s going to take something different to meet the need for computing that is ever faster, cheaper and more efficient. ... » read more

What Does An AI Chip Look Like?

By Ed Sperling - 01 Mar, 2017 - Comments: 5

Depending upon your point of reference, artificial intelligence will be the next big thing or it will play a major role in all of the next big things. This explains the frenzy of activity in this sector over the past 18 months. Big companies are paying billions of dollars to acquire startup companies, and even more for R&D. In addition, governments around the globe are pouring additional... » 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.

by Bryon Moyer

tag: UC Berkeley