tag: AI

Is Programmable Overhead Worth The Cost?
By Brian Bailey - 13 Jan, 2022 - Comments: 0

Programmability has fueled the growth of most semiconductor products, but how much does it actually cost? And is that cost worth it? The answer is more complicated than a simple efficiency formula. It can vary by application, by maturity of technology in a particular market, and in the context of much larger systems. What's considered important for one design may be very different for anothe... » read more

AI Goes Ultra Low Power — Part 1
By Fraunhofer IIS/EAS - 12 Jan, 2022 - Comments: 0

Based on the concept of the new Federal Agency for Jump Innovations (PSRIN-D), the BMBF initiated three pilot innovation competitions. One of them presented the participants with the task of developing the most energy-efficient AI system possible as a hardware implementation on an ASIC or FPGA. With this, a stack of hundreds of two-minute long ECG signals should be analyzed with a minimum of en... » read more

A Practical Approach To DFT For Large SoCs And AI Architectures, Part I
By Rahul Singhal - 11 Jan, 2022 - Comments: 0

The traditional processors designed for general-purpose applications struggle to meet the computing demands and power budgets of artificial intelligence (AI) or machine leaning (ML) applications. Several semiconductor design companies are now developing dedicated AI/ML accelerators that are optimized for specific workloads such that they deliver much higher processing capabilities with much low... » read more

Manufacturing Bits: Jan. 10
By Mark LaPedus - 10 Jan, 2022 - Comments: 2

Finding new materials with inverse design The Singapore-MIT Alliance for Research and Technology (SMART) has found a new way to perform general inverse design, a technique that can accelerate the discovery of new materials. The concept of inverse design is simple. Let’s say you want to develop products with select materials. In a computer, you input the desired materials and the propertie... » read more

How Inferencing Differs From Training in Machine Learning Applications
By Sam Fuller - 06 Jan, 2022 - Comments: 0

Machine learning (ML)-based approaches to system development employ a fundamentally different style of programming than historically used in computer science. This approach uses example data to train a model to enable the machine to learn how to perform a task. ML training is highly iterative with each new piece of training data generating trillions of operations. The iterative nature of the tr... » read more

Manufacturing Shifts To AI Of Things
By John Koon - 06 Jan, 2022 - Comments: 0

AI is being infused into the Internet of Things, setting the stage for significant improvements in manufacturing productivity, improved uptime, and reduced costs — regardless of market segment. The traditional approach to improving manufacturing equipment reliability and efficiency is regular scheduled maintenance. While that is an improvement over just fixing or replacing equipment when i... » read more

Industry Transforming In Ways Previously Unimaginable
By Brian Bailey - 30 Dec, 2021 - Comments: 0

Early in the year, everyone expected that the availability of COVID vaccines would signal the start of a return to normal, but that has certainly not been the case. Now the industry is taking a longer-term view about how to transform business, what is necessary for people to maintain their mental health, and how to create robust hybrid work environments for the future that do not discard the po... » read more

Always-On DSPs
By Ed Sperling - 28 Dec, 2021 - Comments: 0

There are tradeoffs between powering circuits down to save power and waking them up to respond to voice and visual commands. Prakash Madhvapathy, director of product marketing and product management at Cadence, talks about the best ways to deploy digital signal processors, why multiple DSPs are often better than just one, and what penalties there are for various approaches. » read more

The High But Often Unnecessary Cost Of Coherence
By Brian Bailey - 22 Dec, 2021 - Comments: 4

Cache coherency, a common technique for improving performance in chips, is becoming less useful as general-purpose processors are supplemented with, and sometimes supplanted by, highly specialized accelerators and other processing elements. While cache coherency won't disappear anytime soon, it is increasingly being viewed as a luxury necessary to preserve a long-standing programming paradig... » read more

Flexible USB4-Based Interface IP Solution For AI At The Edge
By Synopsys - 21 Dec, 2021 - Comments: 0

Consumers have become accustomed to smart devices that are powered by advances in artificial intelligence (AI). To expand the devices’ total addressable market, innovative device designers build edge AI accelerators and edge AI SoCs that support multiple use cases and integration options. This white paper describes a flexible USB4-based IP solution for edge AI accelerators and SoCs. The IP so... » read more

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