From Cloud To Cloudlets

By Ed Sperling - 17 Aug, 2020 - Comments: 0

Cloudlets, or mini-clouds, are starting to roll out closer to the sources of data in an effort to reduce latency and improve overall processing performance. But as this approach gains steam, it also is creating some new challenges involving data distribution, storage and security. The growing popularity of distributed clouds is a recognition that the cloud model has limitations. Sending the ... » read more

Customization And Limitations At The Edge

By Ed Sperling - 10 Aug, 2020 - Comments: 0

Semiconductor Engineering sat down to discuss the edge constraints and the need for security with Jeff DeAngelis, managing director of the Industrial and Healthcare Business Unit at Maxim Integrated; Norman Chang, chief technologist at Ansys; Andrew Grant, senior director of artificial intelligence at Imagination Technologies; Thomas Ensergueix, senior director of the automotive and IoT line of... » read more

Virtualization In The Car

By Ann Mutschler - 06 Aug, 2020 - Comments: 1

As the automotive industry grapples with complexity due to electrification and increasing autonomy of vehicles, consolidation of ECUs within vehicles, more stringent safety and security requirements, automotive ecosystem players are looking to virtualization concepts in a number of ways to realize the vehicles of tomorrow. One way is with hardware virtualization; the ability of a device such... » read more

WiFi Evolves For The IoT

By Bryon Moyer - 06 Aug, 2020 - Comments: 0

WiFi is everywhere, and it’s the most prevalent of the communication protocols that use unlicensed spectrum. But as a common protocol for the Internet of Things (IoT), it faces challenges both because of congestion and the amount of energy it consumes. Two new approaches aim to address those concerns. One is to use multiple channels at once. The second involves the new 802.11ah HaLow stand... » read more

Big Changes In AI Design

By Ed Sperling And Susan Rambo - 06 Aug, 2020 - Comments: 0

Semiconductor Engineering sat down to discuss AI and its move to the edge with Steven Woo, vice president of enterprise solutions technology and distinguished inventor at Rambus; Kris Ardis, executive director at Maxim Integrated; Steve Roddy, vice president of Arm's Products Learning Group; and Vinay Mehta, inference technical marketing manager at Flex Logix. What follows are excerpts of that ... » read more

Startup Funding: July 2020

By Jesse Allen - 05 Aug, 2020 - Comments: 0

A number of semiconductor and design companies took in funding this month, from a mega round for a data center switch maker to seed grants for two Canadian companies and new funding for an IP marketplace. China continues to be a hot area for electric vehicles, with one company raising half a billion for its two models currently in production. For July, we highlight fifteen startups that raised ... » read more

Pivoting Toward Safety-Critical Verification In Cars

By Ann Mutschler - 31 Jul, 2020 - Comments: 1

The inclusion of AI chips in automotive and increasingly in avionics has put a spotlight on advanced-node designs that can meet all of the ASIL-D requirements for temperature and stress. How should designers approach this task, particularly when these devices need to last longer than the applications? Semiconductor Engineering sat down to discuss these issues with Kurt Shuler, vice president of... » read more

What’s After 5G

By Bryon Moyer - 20 Jul, 2020 - Comments: 1

This year’s IEEE Symposia on VLSI Technology and Circuits (VLSI 2020) included a presentation by NTT Docomo that looked far into the future of cellular communications, setting the stage for a broad industry shift in communication. This is far from trivial. 5G only just recently entered the commercial world, and — especially with the higher millimeter-wave (mmWave) frequencies — it has ... » read more

Why Safety-Critical Verification Is So Difficult

By Ann Mutschler - 15 Jul, 2020 - Comments: 0

Are Better Machine Training Approaches Ahead?

By Bryon Moyer - 01 Jul, 2020 - Comments: 1

We live in a time of unparalleled use of machine learning (ML), but it relies on one approach to training the models that are implemented in artificial neural networks (ANNs) — so named because they’re not neuromorphic. But other training approaches, some of which are more biomimetic than others, are being developed. The big question remains whether any of them will become commercially viab... » read more

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Knowledge Centers
Entities, people and technologies explored

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