AI Inference Memory System Tradeoffs

By Geoff Tate - 01 Aug, 2019 - Comments: 1

When companies describe their AI inference chip they typically give TOPS but don’t talk about their memory system, which is equally important. What is TOPS? It means Trillions or Tera Operations per Second. It is primarily a measure of the maximum achievable throughput but not a measure of actual throughput. Most operations are MACs (multiply/accumulates), so TOPS = (number of MAC units) x... » read more

Building An Efficient Inferencing Engine In A Car

By Ed Sperling - 05 Jun, 2019 - Comments: 0

David Fritz, who heads corporate strategic alliances at Mentor, a Siemens Business, talks about how to speed up inferencing by taking the input from sensors and quickly classifying the output, but also doing that with low power. » read more

Power/Performance Bits: April 16

By Jesse Allen - 16 Apr, 2019 - Comments: 0

Faster CNN training Researchers at North Carolina State University developed a technique that reduces training time for deep learning networks by more than 60% without sacrificing accuracy. Convolutional neural networks (CNN) divide images into blocks, which are then run through a series of computational filters. In training, this needs to be repeated for the thousands to millions of images... » read more

Combining SLAM And CNN For High-Performance Augmented Reality

By Gordon Cooper - 04 Apr, 2019 - Comments: 0

Robotics and headsets or goggles are the most common hardware devices requiring AR/VR/mixed reality, and AR is coming to mobile phones, tablets, and automobiles as well. For hardware devices to see the world around them and add to that reality with inserted graphics or images, they need to determine their position in space and map the surrounding environment. Simultaneous localization and ma... » read more

The Automation Of AI

By Brian Bailey - 28 Mar, 2019 - Comments: 0

Semiconductor Engineering sat down to discuss the role that EDA has in automating artificial intelligence and machine learning with Doug Letcher, president and CEO of Metrics; Daniel Hansson, CEO of Verifyter; Harry Foster, chief scientist verification for Mentor, a Siemens Business; Larry Melling, product management director for Cadence; Manish Pandey, Synopsys fellow; and Raik Brinkmann, CEO ... » read more

The Winograd Transformation

By Ed Sperling - 07 Mar, 2019 - Comments: 0

Cheng Wang, senior vice president of engineering at Flex Logix, explains how the Winograd Transformation applies to convolutional neural networks. https://youtu.be/E7QJUby9x-I » read more

Impact Of IP On AI SoCs

By Ron Lowman - 09 Aug, 2018 - Comments: 2

The combination of mathematics and processing capability has set in motion a new generation of technology advancements with an entire new world of possibilities related to Artificial Intelligence. AI mimics human behavior using deep learning algorithms. Neural networks are what we define as deep learning, which is a subset of machine learning, which is yet a subset of AI, as shown in Figure 1. ... » read more

The Week In Review: Manufacturing

By Mark LaPedus - 06 Apr, 2018 - Comments: 0

Trade wars China and the United States are in the midst of a trade war. Click here for the latest from CNN. Meanwhile, click here for a list of the winners and losers so far. Display Supply Chain Consultants, a research firm, provides more insights from a hi-tech perspective. Gary Shapiro, president and CEO of the U.S.-based Consumer Technology Association (CTA), issued a statement abo... » read more

Low-Power Deep Learning Implementation For Automotive ICs

By Gordon Cooper - 01 Mar, 2018 - Comments: 0

Examples of automotive applications abound where high-performance, low-power embedded vision processors are used, from in-car driver drowsiness detection, to a self-driving car ‘seeing’ the road ahead with pedestrians, oncoming cars, or the occasional animal crossing the road. Implementing deep learning in these types of applications requires a lot of processing power with the lowest possib... » read more

Predictions: Manufacturing, Devices And Companies

By Brian Bailey - 18 Jan, 2018 - Comments: 0

Some predictions are just wishful thinking, but most of these are a lot more thoughtful. They project what needs to happen for various markets or products to become successful. Those far reaching predictions may not fully happen within 2018, but we give everyone the chance to note the progress made towards their predictions at the end of the year. (See Reflection On 2017: Design And EDA and Man... » 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

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