Silicon Valley SOI Symposium a Huge Success. Key Takeaways (Part 1) Here.

Silicon Valley SOI Symposium a Huge Success. Key Takeaways (Part 1) Here.

Takeaway #1: As NXP VP Ron Martino noted in his opening keynote at the recent SOI Symposium in San Jose, FD-SOI is the technology platform for enabling edge computing, and ultra-low power is the sweet spot. 

Organized by the SOI Consortium with support from our members, the recent SOI Symposium in Silicon Valley was an enormous success. Close to 300 decision makers signed up – more than double what we saw just a couple years ago. Attendees spanned the ecosystem: from end-users to design to foundries and right up to the investment community. The presentations and panel discussions were absolutely terrific, and almost all are now freely available – click here to get them.

The focus was heavily on FD-SOI this time, but some very interesting RF-SOI talks were given as well. This was a day packed with presentations by players from across the SOI ecosystem. In this post, we’ll only cover a few. But the others will follow quickly, so watch this page. And now without further ado, let’s dive in.

NXP: In the Sweet Spot

NXP VP Ron Martino presenting at the 2019 SOI Symposium in San Jose.

NXP is designing FD-SOI into many new products, said Martino, GM of the i.MX Processor Application Product Line. There’s a new wave of products – generically you could call them IoT but in fact they’re found throughout the industry. It’s about interacting with the cloud, so edge processing is critical. His presentation, Embedded Processors for Future Applications, is now freely available for downloading from our website.

The new i.MX7ULP is a great example of ULP in the sweet spot. From a design standpoint, it leverages IP, power optimization, and what he described as “starter biasing”. That gets them the long battery life with 2D & 3D graphics they need for wearables and portables in consumer and industrial applications.

NXP slide 10, SOI Symposium, San Jose ’19 (Courtesy: NXP)

Having deepened their expertise in biasing, NXP has now moved on to “advanced biasing” for the next generation of products. For example, the i.MX RT ULP (real-time, ultra-low-power) series are “cross-over” processors, which Martino says are the “new normal”. They deal with a high number of sensor inputs. The i.MX RT 1100 MCUs, which have been qualified for automotive and industrial applications, are breaking the gigahertz performance barrier with a low-power, 28nm FD-SOI process.

Another new product leveraging advanced biasing is the i.MX RT 600. They’ve done hardware acceleration on specific functions and optimized around visionand voice integration at low cost and power.

As shown at Embedded World ’19, automotive app for NXP’x i.MX 8, which is on 28nm FD-SOI. (Courtesy: NXP)

Likewise for the i.MX 8 and 8X subsystems for automotive and industrial applications. At Embedded World, they showed it driving advanced OLED screens, cameras (for parking, for example), V2X, audio, user monitoring (like driver pupil tracking), and integration into the windshield in a heads-up system. This is the high end of the capability of 28nm FD-SOI, he said. It’s a 6 CPU core system with multiple operating systems, about which he said: “It’s the dashboard…it’s amazing.”

BTW, in another presentation, CoreAVI, which builds avionics, automotive and industrial products on NXP’s i.MX 8, addressed safety. You can get that here.

FD-SOI enables a scalable solution for real-time and general compute with the lowest leakage memory, the best dynamic and static power, Martino concluded. NXP’s leadership in body biasing is enabling edge compute, and we can expect to see more content coming soon.

In another NXP presentation later in the day, Stefano Pietri, Technical Director of the company’s Microcontrollers Analog Design Team caught a lot of people’s attention. A wave of cameras went up to capture each of his slides in Analog Techniques for Low Power, High Performance MPU in FD-SOI – but you can get the whole thing now from our website. It’s a very technical presentation, in which he details the many ways FD-SOI makes the analog team’s job easier, enabling them to get performance not available from bulk technologies. They developed a lot of in-house expertise and IP (see slide 16 for a catalog of the IP).

Samsung: Enabling LP Endpoint Products

Tim Dry, Samsung Foundry Director of Edge & Endpoint, SOI Symposium, San Jose ’19

Tim Dry, Director of Foundry Marketing: Edge and End Point presented Samsung’s FDS with MRAM: Enabling Today’s Innovative Low Power Endpoint Products. In a telling first, Samsung has made this presentation available on our website.

FD-SOI covers the wide range of requirements for intelligent IoT, he explained: from high to low processing loads; and active to dormant processing duty cycles. That includes chips that will last for ten years, and need to be able to wake up fast and kick right into high performance. These products are 50% analog, and packaging is part of the solution (especially for the RF component).

Samsung has been shipping 28nm FD-SOI (which they call 28FDS) since 2015, first in IoT/wearables, then in automotive/industrial and consumer. Yields are fully mature. In March 2019, they announced mass production of eMRAM on 28FDS. It’s a BEOL process, adding only 3 masks. It cuts chip-level power by 65% and RF power by 76% over 40nm bulk with external memory. Beyond the fact that it’s 1000x faster than eFlash, eMRAM also has other advantages that make it especially good for over-the-air updates, for example.

Samsung Foundry FD-SOI IP slide, SOI Symposium, San Jose ’19 (Source: Samsung Foundry Keynote at SOI Symposium 2019, USA)

Samsung also has RF and 5G mmWave products shipping in 28FDS. The company has a fantastic ecosystem of partners helping here, said Dry. In AI at the endpoint, they’re shipping IoT products for video surveillance cameras: some are high speed, but some are also low speed – it depends on the detection use case. And most importantly for the design ecosystem, the IP is all ready.

Next up for Samsung is 18FDS, which will ship this year with RF, then in 2020 with eMRAM. 18FDS, Dry said, is optimized for power reduction. Compared to 28FDS, it’s got 55% lower power consumption, 25% less area and 17% better performance at the same power. You’ll hear more about it as well as their design services if you’re at the Samsung Foundry Forum in May (registration info here).

ARM’s Biased Views

Kelvin Low, VP of Marketing for Arm’s Physical Design Group (PDG) gave a presentation entitled Biased Views on the Industry’s Broadest FDSOI Physical IP Solution. By way of background, Arm and Samsung Foundry recently announced a comprehensive, foundry-sponsored physical IP platform, including an eMRAM compiler for 18FDS. In case you missed it, at the time Arm Senior Product Marketing Manager Umang Doshi described the offering in an Arm Community / Developer physical IP blog, which Arm graciously agreed to share with ASN readers.

Slide 9 from Arm’s presentation, Silicon Valley SOI Symposium 2019.

At the SOI Symposium, Low emphasized to the audience that Arm now has the broadest range of FD-SOI + IP solutions. It addresses mobile, consumer, IoT, automotive and AI/ML.

There are 18FDS POP (processor optimized pipe) packages for Arm Cortex-A55, Cortex-R52 and Cortex-M33 processors. IP integrates biasing and a number of standard PVTs (corners). And since the Samsung platform is foundry-sponsored, it’s free.

Slides 6 and 11 from Arm’s presentation, Silicon Valley SOI Symposium 2019. The goal of POP IP is to enable partners to implement and tapeout Arm cores with the fastest turn-around time and best-in-class PPA while maximizing the benefits of process technology.

Arm did a test chip with eMRAM, which they’ve just gotten back. It’s functional (some details are available in slide 14 of their presentation), and the company is now preparing a demo board that they’ll be showing shortly. Watch this page!

That’s all for this post. The next post — part 2, covering presentations by Synaptics, GlobalFoundries, STMicroelectronics, Dolphin Integration and Anokiwave — is now available. Click here to read on.

About the author

Adele Hars editor