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And The Winner Is…

Which subjects garnered the most reads in 2017? Which of those trends will continue into 2018?

popularity

Finding out what resonates with our readers is important, so each year I look back through the list of the best-read articles for the channels that I write for. While this simple strategy does favor articles published during the early part of the year, the fact that our readership continues to grow, partially offsets this bias. For example, in Low Power/High Performance (LPHP) a quarter of the top articles were published in October or later, and half of the top articles for System-Level Design (SLD) were in the second half of the year.

Within SLD and LPHP one trend is very clear. Readers liked articles about machine learning, AI and CNNs. Within SLD, 11 of the top 20, and 8 of the top 10 articles talked about this subject. A couple also appeared in the top 20 for LPHP and an article I published just last week is very quickly gaining ground on the top twenty. The top position for SLD goes to Ed Sperling for his special report, entitled The Great Machine Learning Race. My top articles in this category included Machine Learning Meets IC Design and CCIX Enables Machine Learning. Other top articles included discussions about RISC-V, SW-defined hardware, accelerators, embedded FPGAs, and photonics.

Turning our attention to LPHP, Ann Steffora Mutschler claimed the top spot with How Reliable Are FinFETs? I took second place with New Memories And Architectures Ahead. Attention within LPHP was a lot more varied, but readers did congregate around articles about 10/7nm technologies. An article written by Mark LaPedus — The Race to 10/7nm — for Manufacturing and Process Technology, was the top article for the entire site. Other popular subjects included those focused on application areas such as IoT Myth Busting, plus articles about clocks, analog, memory interfaces and body biasing.

One surprising aspect is how these articles compared with the bread and butter of system-level design and verification. The upcoming Portable Stimulus Standard is a big deal in this sector, and user interest in its progress through the committee is high. Reader numbers may be an indication that verification practitioners are not as interested in future technologies as much as designers seem to be, or that they are more interested in how-to types of articles that tend to require longer descriptions than the typical readership of Semiconductor Engineering. If anyone has any insights into this I would like to hear your thoughts. That said, we don’t live entirely by story views. Just because the reader traffic isn’t as high as for machine learning, it certainly appears that we’re reaching the right readers with valuable information.

Automotive started slowly, but it is beginning to pick up steam. This reflects what is going on in the semiconductor industry as a whole, where the race is on to electrify cars and add in features that can assist and ultimately guide a vehicle without human intervention.

What will continue to be hot?
I expect machine learning to continue to be a hot topic for 2018 given that recent articles are quickly rising in the charts. I also expect more interest related to heterogeneous processing and other trends that are driven by segments other than mobile phones. Of course, articles about emerging technologies, especially those associated with manufacturing, will always be popular, and I suspect we will see articles about 5nm garnering the most attention. eFPGA and system interconnects also will be technologies finding their way into a greater number of chips.

Having been involved with verification technology for a number of years, I would like to predict an upshift in this area. Hopefully “machine learning helps verification” could turn the tide. Time will tell.



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