Note to our readers: Semiwiki Founder Dan Nenni recently wrote an excellent piece on the importance of the Synopsys investment in automotive IP for GlobalFoundries’ 22FDX (FD-SOI) technology. He graciously has given us permission to reprint it here in ASN.
IP vendors have always had the inside track on the status of new process nodes and what customers are planning for their next designs. This is even more apparent now that systems companies are successfully doing their own chips by leveraging the massive amounts of commercial IP available today. Proving once again that IP really is the foundation of modern semiconductor design.
Automotive is one of those market segments where systems companies are doing their own chips. We see this first hand on SemiWiki as we track automotive related blogs and the domains that read them. To date we have published 354 automotive blogs that have been viewed close to 1.5M times by more than 1k different domains.
The recent press release by Synopsys and GLOBALFOUNDRIES didn’t get the coverage it deserved in my opinion and the coverage it got clearly missed the point. Synopsys, being the #1 EDA and #1 IP provider, has the semiconductor inside track like no other. For Synopsys to make such a big investment in FD-SOI (GF FDX) for automotive grade 1 IP is a huge testament to both the technology and the market segment, absolutely.
I talked to John Koeter, Vice President of Marketing for IP, Services and System Level Solutions. John is a friend and one of the IP experts I trust. 3 years ago Synopsys got into automotive grade IP and racked up 25 different customer engagements just last year. The aftermarket electronics for adding intelligence (autonomous-like capabilities, cameras, lane and collision detection, etc…) to older vehicles is also heating up, especially in China.
I also talked to Mark Granger, Vice President of Automotive Product Line Management at GLOBALFOUNDRIES. Mark has been at GF for two years, prior to that he was with NVIDIA working on autonomous chips with deep learning and artificial intelligence. According to Mark, GF’s automotive experience started with the Singapore fabs acquired from Chartered in 2010. The next generation automotive chips will come from the Dresden FDX fabs which are right next door to the German automakers including my favorite, Porsche.
One thing we talked about is the topology of the automotive silicon inside a car and the difference between central processing and edge chips. Remember, some of these chips will be on glass or mirrors or inside your powertrain. The edge chips are much more sensitive to power and cost so FDX is a great fit.
Mark provided a GF link for more information:
Here is the link to our Automotive resources:
One thing Mark, John, and I agree on is that truly autonomous cars for the masses is still a ways out but we as an industry are working very hard to get there, absolutely.
Here is the press release:
Synopsys and GLOBALFOUNDRIES Collaborate to Develop Industry’s First Automotive Grade 1 IP for 22FDX Process
Synopsys’ Portfolio of DesignWare Foundation, Analog, and Interface IP Accelerate ISO 26262 Qualification for ADAS, Powertrain, 5G, and Radar Automotive SoCs
MOUNTAIN VIEW, Calif., and SANTA CLARA, Calif., Feb. 21, 2019 /PRNewswire/ —
Synopsys, Inc. (Nasdaq: SNPS) and GLOBALFOUNDRIES (GF) today announced a collaboration to develop a portfolio of automotive Grade 1 temperature (-40ºC to +150ºC junction) DesignWare® Foundation, Analog, and Interface IP for the GF 22-nanometer (nm) Fully-Depleted Silicon-On-Insulator (22FDX®) process. By providing IP that is designed for high-temperature operation on 22FDX, Synopsys enables designers to reduce their design effort and accelerate AEC-Q100 qualification of system-on-chips (SoCs) for automotive applications such as eMobility, 5G connectivity, advanced driver assistance systems (ADAS), and infotainment. The Synopsys DesignWare IP implements additional automotive design rules for the GF 22FDX process to meet stringent reliability and operation requirements. This latest collaboration complements Synopsys’ broad portfolio of automotive-grade IP that provides ISO 26262 ASIL B Ready or ASIL D Ready certification, AEC-Q100 testing, and quality management.
“Arbe’s ultra-high-resolution radar is leveraging this cutting-edge technology that enabled us to create a unique radar solution and provide the missing link for autonomous vehicles and safe driver assistance,” said Avi Bauer, vice president of R&D at Arbe. “We need to work with leading companies who can support our technology innovation. GF’s 22FDX technology, with Synopsys automotive-grade DesignWare IP, will help us meet automotive reliability and operation requirements and is critical to our success.”
“GF’s close, collaborative relationships with leading automotive suppliers and ecosystem partners such as Synopsys have enabled advanced process technology solutions for a broad range of driving system applications,” said Mark Ireland, vice president of ecosystem partnerships at GF. “The combination of our 22FDX process with Synopsys’ DesignWare IP enables our mutual customers to speed the development and certification of their automotive SoCs, while meeting their performance, power, and area targets.”
“Synopsys’ extensive investment in developing automotive-qualified IP for advanced processes, such as GF’s 22FDX, helps designers accelerate their SoC-level qualifications for functional safety, reliability, and automotive quality,” said John Koeter, vice president of marketing for IP at Synopsys. “Our close collaboration with GF mitigates risks for designers integrating DesignWare Foundation, Analog, and Interface IP into low-power, high-performance automotive SoCs on the 22FDX process.”
For more information on Synopsys DesignWare IP for automotive Grade 1 temperature operation on GF’s 22FDX process:
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About the Author
Daniel Nenni has worked in Silicon Valley for over 35 years with computer manufacturers, electronic design automation software, and semiconductor intellectual property companies. He is the founder of SemiWiki.com (an open forum for semiconductor professionals) and the co-author and publisher of “Fabless: The Transformation of the Semiconductor Industry”, “Mobile Unleashed: The Origin and Evolution of ARM Processors in our Devices” and “Prototypical: The Emergence of Prototyping for SoC Design”. He is an internationally recognized business development professional for companies involved with the fabless semiconductor ecosystem.
ST Fellow Dr. Andreia Cathelin gave a terrific presentation at the recent CMP Annual Meeting. Now posted and freely available, Performance of Recent Outstanding 28nm FD-SOI Circuits Taped Out Through CMP highlighted eight examples – though she told ASN that she had easily over 50 from which to choose.
CMP is a Multi-Project Wafer (MPW) service organization in ICs, Photonic ICs and MEMS. They’ve been organizing prototyping and low volume production in cooperation with foundries for over 37 years. In partnership with ST since 1994, in the fall of 2012 they opened access to MPW runs in the 28nm FD-SOI process. More than 180 tape-outs have been fabricated since then using the process.
As Dr. Cathelin said, this lets ST show their industrial clients just how good the technology is. The chips she chose to cover in her presentation get “spectacular performance”, she said, especially for low-power or power-sensitive SoCs.
Here’s a quick recap of what she presented (some of which she co-authored), followed by some other SOI-related updates from the CMP meeting.
FD-SOI, said Dr. Cathelin, “…is unmatched for cost-sensitive markets requiring digital and Mixed Signal SoC integration and performance.” In the first dozen slides of her presentation, she gave the technical details on the advantages of FD-SOI in analog, RF/millimeter wave, Analog/Mixed-Signal and digital design. If you’re a designer, you’ll want to check those out.
Then she ran through eight great chips – all manufactured by ST on 28nm FD-SOI through CMP’s MPW services. Here they are. (You can click on the illustrations to see them in full screen.)
This chip was presented at ESSCIRC ’16 by a team from ISEN Lille, Professors Andreas Kaiser and Antoine Frappé (you can get the complete paper by I.Sourikopoulos et al on IEEE Xplore – click here.) As noted in the abstract, “Delay controllability has always been the major concern for the reliable implementation of circuits whose purpose is timing.” By leveraging body biasing in FD-SOI, this novel low-power design architecture for 60GHz receivers enables very high bandwidth together with fine-grain wide range delay flexibility, for implementing Delay Feedback Equalizer techniques in the Intermediate Frequency (IF) reception path. The results are state-of-the-art: ultra wide range, linear control, fs/mV sensitivity and energy efficient controllable delay cells.
Presented at RFIC ’17 by a team from the IMS Bordeaux lab, Professor Yann Deval and STMicroelectronics, this chip demonstrates the highest oscillation frequency attainable so far at the 28nm node, be it planar bulk or FD-SOI. (Click here to get the full paper by R. Guillaume et al from IEEE Xplore.) As noted in the abstract, solutions on silicon for mmW and sub-mmW applications have been demonstrated for high-speed wireless communications, compact medical and security imaging. The main challenges are for the signal generation at high frequencies, and this implementation demonstrates spectacular oscillation frequencies close to the transistor’s transition frequency (fT). In this chip, they used body bias tuning to optimize the phase noise, demonstrated very low on-wafer variability, and simulation methods that permit measurement prediction precision within 0.1%.
Extremely energy efficient SoCs are key for the IoT era – but SRAM gets very tricky at ultra-low voltages (ULV). Presented at ESSCIRC ’16 by B. Mohammadi et al (on IEEE Xplore here) from Professor Joachim Rodrigues’ team at the Lund University, this is a 128 kb ULV SRAM, based on a 7T bitcell. The minimum operating voltage VMIN is measured as just 240mV and the retention voltage is as low as 200mV. FD-SOI enabled them to overcome ULV performance and reliability challenges by letting the Lund U.-lead team selectively overdrive the bitline and wordline with a new single-cycle charge-pump. Plus they came up with a new scheme so it doesn’t need a sense amplifier, yet delivered 90MHz read speed at 300mV, dissipating 8.4 fJ/bit-access.
4. Matched Ultrasound Receiver in 28FDSOI
Presented at ISSCC ’17 (with an extended relative paper at JSSC ’17) by M-C Chen et al with Professor Boris Murmann’s team at Stanford, the full title of the paper about this chip is A Pixel Pitch-Matched Ultrasound Receiver for 3-D Photoacoustic Imaging With Integrated Delta-Sigma Beamformer in 28-nm UTBB FD-SOI. (Click here to get it on IEEE Xplore.) It’s a a proof-of-concept for a big ultrasound receiver: a “pixel pitch-matched readout chip for 3-D photoacoustic (PA) imaging.” PA is “…an emerging medical imaging modality based on optical excitation and acoustic detection.” It’s used in studying cancer progression in clinical research, for example. As noted in the paper abstract, “The overall subarray beamforming approach improves the area per channel by 7.4 times and the single-channel SNR by 8 dB compared to prior art with similar delay resolution and power dissipation.” One of the (many) advantages of FD-SOI in this context is for front-end signal conditioning in each pixel. This unique type of pixel pitch-matched architecture implementation is possible only in a 28nm (or less) node of an FD-SOI technology, as it is matched with the pitch sizing needed for the ultrasound transducers in order to generate signals for a 3-D reading.
5. SleepTalker – 28nm FDSOI ULV WSN Transmitter: RF-mixed signal-digital SoC
Presented at VLSI ’16 and JSSC ’17 by G. de Streel et al from Professor David Bol’s team at Université Catholique de Louvain la Neuve, the full title of the paper about this chip is SleepTalker: A ULV 802.15.4a IR-UWB Transmitter SoC in 28-nm FDSOI Achieving 14 pJ/b at 27 Mb/s With Channel Selection Based on Adaptive FBB and Digitally Programmable Pulse Shaping (get it on IEEE Xplore here). This chip tackles the IoT requirement for sensing functions that can operate in the ULV context. That means creating wireless sensor nodes (WSN) that can be powered on an energy harvesting power budget – and that’s a real challenge if you want to incorporate an RF component that can handle medium data rates (5-30 Mb/s) for vision or large distributed WSN networks. The energy efficiency has to be better than 100 pJ/b. To get there, the UCL-lead team used wide-range on-chip adaptive forward back biasing for “…threshold voltage reduction, PVT compensation, and tuning of both the carrier frequency and the output power. […] Operated at 0.55 V, it achieves a record energy efficiency of 14 pJ/b for the transmitter (TX) alone and 24 pJ/b for the complete SoC with embedded power management. The TX SoC occupies a core area of 0.93 mm2.”
This massive MIMO chip was presented at ISSCC ’17 by a team from Professors Liang Liu and Ove Edforss at the Lund University in a paper entitled 3.6 A 60pJ/b 300Mb/s 128×8 Massive MIMO precoder-detector in 28nm FD-SOI (H. Prabhu, et al; get it from IEEEE Xplore here). While Massive MIMO (MaMi) will be needed for next-gen communications, it can’t be achieved by just scaling MIMO – that would be too costly in terms of flexibility, area and power. As noted in the Lund U. team’s intro, “Algorithm optimizations and a highly flexible framework were evaluated on real measured channels. Extensive hardware time multiplexing lowered area cost, and leveraging on flexible FD-SOI body bias and clock gating resulted in an energy efficiency of 6.56nJ/QRD and 60pJ/b at 300Mb/s detection rate.”
7. ENVISION: A 0.26-to-10TOPS/W Subword-Parallel Dynamic-Voltage-Accuracy-Frequency-Scalable Convolutional Neural Network Processor in 28nm FDSOI
Today’s solutions for always-on visual recognition apps are an order of magnitude too power hungry for wearables. Running at 10’s to several 1OO’s of GOPS/W, they use classification algorithms called ConvNets, or Convolutional Neural Networks (CNN). The paper about this chip was presented at ISSCC ’17 by a team from professor Marian Verhelst at Katoliek Universiteit Leuven (B. Moons, et al, get it from IEEE Xplore here), and it changes everything. Leveraging FD-SOI and body-biasing, the KU Leuven team solved the power challenge with, “…the concept of hierarchical recognition processing, combined with the Envision platform: an energy-scalable ConvNet processor achieving efficiencies up to 10TOPS/W, while maintaining recognition rate and throughput. Envision hereby enables always-on visual recognition in wearable devices.”
As we learned at SOI Consortium FD-SOI Tutorial Day in SiValley last year, Professor Borivoje “Bora” Nikolic of UC Berkeley is known as one of the world’s top experts in body-biasing for digital logic (he and his team have designed more than ten chips in ST’s 28nm FD-SOI!) They presented the RISC-V chip here at ESSCIRC ’16 and JSSC ’17, in a paper entitled Sub-microsecond adaptive voltage scaling in a 28nm FD-SOI processor SoC (B.Keller, et al, on IEEE Xplore here). As they noted in the intro, a major challenge for mobile and IoT devices is that their workloads are highly variable, but they operate under very tight power budgets. If you apply adaptive voltage scaling (AVS), you can improve energy efficiency by scaling the voltage to match the workload. But in the current gen of SoCs, the AVS timescales of hundreds of microseconds is too slow. The chip the Berkeley team presented brought that down to sub-microseconds by aggressively applying body-biasing throughout the chip, including to workload measurement circuits and integrated power management units. The result is “… extremely fine-grained (<1μs) adaptive voltage scaling for mobile devices.” (BTW, they expand on some of the details in another paper published in 2017.) These design techniques are now taught at UC Berkeley, as this kind of implementation is the subject of a course in SoC design (including the RF part of transceivers); a first educational chip has already been taped-out and successfully measured. (BTW, Professor Nikolic will once again join Dr. Cathelin and other luminaries in teaching at the SOI Consortium’s FD-SOI Training Day in Silicon Valley, 27 April 2018 – click here for sign-up information.)
At the meeting, CMP also made a presentation on all their MPW offerings – you can get it here. On ST’s SOI (in addition to 28nm FD-SOI, of course), that includes the new 160nm SOIBCD8s: Bipolar-CMOS-DMOS Smart Power (for automotive sensor interface ICs, 3D ultrasound, MEMS & micro-mirror drivers); and 130nm H9-SOI-FEM: Front-End Module (for radio receiver/transceiver, cellular, WiFi, and automotive keyless systems).
CMP also provides tutorials that are used by institutions across the globe. A new update to the tutorial, RTL to GDS Digital Design Flow in 28nm FD-SOI Process is now available – you can see the presentation they did about that here. (It now includes LVS and DRC steps with Mentor/Calibre or Cadence/PVS.) Other services, like the 2-day, hands-on THINGS2DO FD-SOI training days at the end of March are always fully booked almost immediately, but don’t hesitate to inquire, as they’ll be adding more.
For some more examples of 28nm FD-SOI chips run through CMP over the years, see their website pages on Examples of Manufactured ICs. There are also some nice examples on pages 21 and 23 of their most recent annual report.
For those in the photonics world, CMP has teamed up with Leti to offer Si-310 PHMP2M, a 200mm CMOS SOI platform. CMP is cooperating with Tyndall for the photonics packaging – see that presentation here. Training kits and tutorials will be available in Q3 of this year.
And in partnership with MEMSCAP, CMP offers Multi-User MEMS Processes (aka MUMPs) for SOI-MEMS.
So lots of terrific SOI resources for CMP – check it out!
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Note: special thanks to Andreia Cathelin of ST and Kholdoun Torki of CMP for their help on this piece.
There’s a new memory IP specialist on board for the FDSOI ecosystem. Attopsemi Technology has joined GlobalFoundries’ FDXcelerator™ Partner Program (read the press release here). Attopsemi is ensuring that its scalable, non-volatile one-time programmable (OTP) memory IP is compatible with GF’s 22FDX® technology. Their leading-edge I-fuse™ OTP IP is a fuse-based OTP technology that can guarantee zero-program defect, and offers up to 100x reliability, 1/100 the cell size, and 1/10th the program current compared to traditional e-fuse technologies. This advanced OTP targets customers and designers working on harsh, demanding applications such as automotive, 3D IC, and IoT.
“Attopsemi’s new offering should benefit our 22FDX customers in all the key market segments we address, especially for IoT and processor intensive applications,” said Alain Mutricy, senior vice president of product management at GF. “Their commitment continues to demonstrate strong industry interest in GF’s FDXcelerator program and the 22FDX value proposition.”
12nm FD-SOI has now officially joined the GlobalFoundries’ roadmap, targeting intelligent, connected systems and beating 14/16nm FinFET on performance, power consumption (by 50%!) and cost (see press release here). Customer product tape-outs are expected to begin in the first half of 2019. GloFo also announced FDXcelerator™, an ecosystem designed to give 22FDX™ SoC design a boost and reduce time-to-market for its customers (press release here).
The news turned heads worldwide (hundreds of publications immediately picked up the news) – and especially in China. “We are excited about the GlobalFoundries 12FDX offering and the value it can provide to customers in China,” said Dr. Xi Wang, Director General, Academician of Chinese Academy of Sciences, Shanghai Institute of Microsystem and Information Technology. “Extending the FD-SOI roadmap will enable customers in markets such as mobile, IoT, and automotive to leverage the power efficiency and performance benefits of the FDX technologies to create competitive products.”
Wayne Dai, CEO of VeriSilicon (headquartered in Shanghai but designing for the world’s biggest names in the chip biz), added, “We look forward to extending our collaboration with GlobalFoundries on their 12FDX offering and providing high-quality, low-power and cost-effective solutions to our customers for the China market. The unique benefits of FD-SOI technologies enable us to differentiate in the automotive, IoT, mobility, and consumer market segments.”
The ultra-thin FD-SOI wafers are where it all starts, and they’re ready to go in high volume, says Paul Boudre, CEO of SOI wafer leader Soitec. “We are very pleased to see a strong momentum and a very solid adoption from fabless customers in 22FDX offering,” he adds. “Now this new 12FDX offering will further expand FD-SOI market adoption. This is an amazing opportunity for our industry just in time to support a big wave of new mobile and connected applications.”
GloFo’s 12FDXTM platform, which builds on the success of its 22FDXTM offering, is designed to enable the intelligent systems of tomorrow across a range of applications, from mobile computing and 5G connectivity to artificial intelligence and autonomous vehicles. Increased integration of intelligent components including wireless (RF) connectivity, non-volatile memory, and power management—all while driving ultra-low power consumption—are key 12FDX selling points that FinFETs can’t touch.
The technology also provides the industry’s widest range of dynamic voltage scaling and unmatched design flexibility via software-controlled transistors—capable of delivering peak performance when and where it is needed, while balancing static and dynamic power for the ultimate in energy efficiency.
“Some applications require the unsurpassed performance of FinFET transistors, but the vast majority of connected devices need high levels of integration and more flexibility for performance and power consumption, at costs FinFET cannot achieve,” said GLOBALFOUNDRIES CEO Sanjay Jha. “Our 22FDX and 12FDX technologies fill a gap in the industry’s roadmap by providing an alternative path for the next generation of connected intelligent systems. And with our FDX platforms, the cost of design is significantly lower, reopening the door for advanced node migration and spurring increased innovation across the ecosystem.”
Kudos came in from G. Dan Hutcheson, CEO of VLSI Research, IBS CEO Handel Jones, Linley Group Founder Linley Gwennap, Dasaradha Gude, CEO of IP/design specialists INVECAS, Leti CEO Marie Semeria and NXP VP Ron Martino (they’ve already started on 28nm FD-SOI for their i.MX line – read his superb explanations in ASN here).
Simultaneously to the 12FDX announcement, GloFo announced the FDXcelerator Partner Program. It creates an open framework under which selected Partners can integrate their products or services into a validated, plug and play catalog of design solutions. This level of integration allows customers to create high performance designs while minimizing development costs through access to a broad set of quality offerings, specific to 22FDX technology. The Partner ecosystem positions members and customers to take advantage of the broad adoption and accelerating growth of the FDX market.
Initial partners of the FDXcelerator Partner Program are: Synopsys (EDA), Cadence (EDA), INVECAS (IP and Design Solutions), VeriSilicon (ASIC), CEA Leti (services), Dreamchip (reference solutions) and Encore Semi (services). These companies have already initiated work to deliver advanced 22FDX SoC solutions and services.
Initial FDXcelerator Partners have committed a set of key offerings to the program, including:
Additional FDXcelerator members will be announced in the following months.
Dan Hutcheson, CEO of VLSIresearch, Inc. finally likes FD-SOI. That’s important, because he’s a really influential person in the chip world. Everybody who’s anybody in the chip biz pays attention to what VLSIresearch, Inc. has to say.
Dan recently gave a talk entitled “FD-SOI: Disruptive or Just Another Process?” to a packed-to-the-brim room during the FD-SOI Symposium in San Jose. (The ppt he used there is available on the SOI Consortium website – download it for free here).
Happily for those who didn’t make it to San Jose, Dan then went into the studio and made a video encore of his presentation for all to see – and it’s now posted on his weSRCH site. So you get not just his slides, but also his explanations and comments.
But for those of you who just want a quick recap, here are some of his key points.
Dan, as he’s always quick to point out, is an economist, albeit one extremely well-versed in chip technology. He always thought SOI was an elegant solution, but didn’t see cost savings in the fab as a driver. When asked to give a talk in San Jose, he decided to brush up a bit on what people were saying about FD-SOI. So he did an informal survey – and of course, being Dan, he can talk to just about anyone he wants.
In this case, he talked to decision makers from about a dozen top companies in the chip biz – enough to give him a 95% confidence level in his results. And the results are impressive: almost ¾ said they had FD-SOI designs underway or had already used it, while only about a third said they’ll stick firmly to bulk.
It turns out that there are companies out there doing both FinFETs and FD-SOI. Why? They’ve figured out the differentiable features, they told him. And some designers are now saying that FD-SOI is actually easier to design in than FinFETs, with one company reporting that design time in FD-SOI was half that of FinFETs.
Dan learned that the two biggest drivers of FD-SOI are IoT and automotive – IoT because those super power-stingy chips get enormous leverage out of back biasing, and automotive for reliability (and for both they get ease of analog integration).
But at the heart of it, it’s a business case: “It’s not about cost,” he says. “It’s about time-to-money.” With FD-SOI, TTM is significantly faster.
Those that go with FinFET are more often a big company (so they can afford the high NRE* costs) with a huge market, big die and a lot of digital. But if the market’s smaller, faster-moving and needs scaled-down NRE costs, then the people Dan talked to said they are turning to FD-SOI. They see it getting them to market faster, gives them lots of “knobs” and advantages in terms of power, reliability and analog integration, it’s easier to design in, and really enables product differentiation. In fact Dan had analog folks telling him that FD-SOI gave them back some of their favorite tricks and tools that they’d lost after the 130nm node.
Finally, Dan sees FD-SOI as a technology with both a long history and a long lifetime ahead. FD-SOI is not in itself disruptive, but is rather an enabler of disruption. The disruption, he says, is IoT. By all means check out his video if you want more detail on his perspective on IoT, automotive and the foundry offerings.
In conclusion, he urges users to strengthen the ecosystem’s momentum by disclosing their success stories – though he also sees how they might be reluctant to, as FD-SOI is the secret sauce that gives them a huge competitive advantage. But in the end rewards will be reaped, as driving volume up will drive costs down.
If you have a good FD-SOI design story you’d like to share, let us know here at ASN – we’ll be happy to consider it for publication, to help get the word around.
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*NRE = non-recurring engineering. In a fabless scenario, there are NRE for IP and design (engineering costs, up-front and royalty-based IP costs), NRE for masks and fabrication (mask costs, wafer prototype lots, tools costs, probe cards, load-boards and other one-time capital expenditures), and NRE for qualifications (ESD, latch-up and other industry-specific qualifications, as in automotives).
By Ronald M. Martino, Vice President, i.MX Applications Processor and Advanced Technology Adoption, NXP Semiconductors
At NXP, we’re very excited about the prospects for our new i.MX 7 and 8 series of applications processors, which we’re manufacturing on 28nm FD-SOI.
As noted in part 1 of this article series, the new i.MX 7 series, which leverages the 32-bit ARM v7-A core, is targeting the general embedded, e-reader, medical, wearable and IoT markets, where power efficiency is paramount. The i.MX 8 series leverages the 64-bit ARM v8-A series, targeting automotive applications, especially driver information systems, and well as high-performance general embedded and advanced graphics applications.
Choosing an FD-SOI solution gave our designers some specific tools that helped them to more easily and robustly deliver the features our customers are looking for. Here in part 2, we’ll look a little more deeply into the markets each of these chip families is targeting, and the role FD-SOI plays in helping us meet our specs.
Announced last June, the first members of our new 7 series — the i.MX 7Solo and i.MX 7Dual product families — will be hitting the market shortly. We’ve been shipping samples since last year, and the response has been tremendous. (You can read about the i.MX 7 IoT ecosystem we’re helping create for our customers here and support for wearable markets here.)
Our i.MX 7 customers are building products for power- and cost-sensitive markets. That of course includes a vast array of innovative IoT solutions and wearables, but also solutions for other parts of the embedded market like handheld point-of-sale (POS) and medical devices, smart home controls and industrial products. The i.MX 7 series also continues NXP’s industry leading support for the e-reader market via integration of an advanced, fourth-generation EPD controller.
For all these markets, excellent performance is very important, but both dynamic and static power figures are really key. When you’re creating a system with power efficient processing and low-power deep sleep modes, you enable a new tier of performance-on-demand, battery-operated devices that are lighter and cheaper, and in a virtuous cycle require smaller batteries.
The next members of the NXP i.MX 7 series combine ultra-low power (dynamically leveraging the reverse back biasing you can do with FD-SOI) and performance-on-demand architecture (boosted when needed with FD-SOI’s forward back-biasing). It’s the industry’s first general purpose microprocessor family to incorporate both the ARM® Cortex®-A7 and the ARM Cortex-M4 cores (customers can choose between single or dual A7 cores). These technologies, together with our new companion PF3000 power management IC, unleash the potential for dramatically innovative, secure and power efficient end-products for wearable computing and IoT applications.
The initial offering of i.MX 7 was designed (on 28nm bulk) with Cortex-A7 cores operating up to 1 GHz, while the Cortex-M4 core operates at up to 200 MHz. The Cortex-A7 and Cortex-M4 achieve processor core efficiency levels of 100 microWatts (μW) /MHz and 70 μW /MHz respectively.
A Low Power State Retention (LPSR), battery-saving mode can be improved by FD-SOI and consumes only 250 μW, representing a 3x improvement over our previous generation (on 40nm bulk). That’s almost 50% better than our competitors. Plus it minimizes wake up times without requiring Linux reboot, while supporting DDR self-refresh mode, GPIO wakeup, and memory state retention.
The next members of the i.MX 7 series, with FD-SOI dynamic back-biasing, enable different blocks to be reverse or forward back-biased on the fly to attain always-optimal power savings or performance. Additional power optimization features are enabled to achieve leadership power efficiency. We’ve optimized FD-SOI dynamic back-biasing to enable performance-on-demand architecture through which the i.MX 7 series meets the bursty, high-performance needs (this is when forward back-biasing kicks in) of running Linux, graphical user interfaces, high-security technologies like Elliptic Curve Cryptography, as well as wireless stacks or other high-bandwidth data transfers with one or multiple Cortex-A7 cores.
When high levels of processing are not needed, low-power modes kick in with reverse back biasing of the critical subsystems, and the ongoing, real-time work is carried on by the smaller, lower powered Cortex-M4.
All things considered, it’s perhaps no surprise that we expect i.MX 7 series solutions for cost-sensitive markets to be a key driver of our long-term i.MX portfolio expansion.
Our new i.MX 8 series portfolio, based on 28nm FD-SOI process technology, targets highly-advanced driver information systems and other multi-media intensive embedded applications. It incorporates those same key attributes as the i.MX 7, but extends them into realms the industry has never experienced. We believe the i.MX 8 series is poised to revolutionize interactivity in multimedia and display applications across all kinds of industries.
i.MX 8 incorporates innovations in the processor — complex graphics, vision, virtualization and safety to help revolutionize interactivity for a wide range of uses in many, many markets. The capabilities of this family is broad, but one of the places it’s going to be the biggest game-changer is in what is becoming the e-cockpit of your car.
For almost two decades, SOI has shone in the embedded processing world. In addition, NXP counts every major automotive maker in the world amongst its customers for our devices. Entering the new e-cockpit frontier, 28nm FD-SOI is the logical choice in making the i.MX 8 series meet and exceed the stringent requirements of top automotive OEMs for years to come.
The i.MX 8 series leverages ARM’s V8-A 64-bit architecture in a 10+ core complex that includes blocks of Cortex-A72s and Cortex-A53s. All the FD-SOI advantages discussed above for the i.MX 7 are also being brought to bear here (the power envelope for automotive designers being extremely strict). But in the hot and electrically noisy automotive environment, FD-SOI also plays an important role in ensuring robust operation.
The way we see it, your car’s multimedia centric e-cockpit will revolve around the i.MX 8, a single chip that drives all displays from infotainment to heads-up-displays (HUD) to instrument clusters. It’s optimized for the intelligent transfer of data and information management from multiple subsystems within the IC – as opposed to only delivering raw performance through one or two processing blocks.
For drivers and passengers alike, we’re looking at a very different world: one that includes the spread of advanced heads-up displays, intuitive gesture control, natural speech recognition, augmented reality, enhanced convenience and device connectivity. (I wrote a blog exploring the possibilities last fall – you can read it here.)
And of course, it will be secure from hackers, and fail-safe for critical systems.
From our customers’ standpoint, they can design a single hardware platform and scale it across multiple market segments with the unique approach to pin and software compatibility within the i.MX product families.
The i.MX family has been leveraged in over 35 million vehicles since it was first launched in vehicles in 2010. So with all these new features, and low-power and robust performance, we see a very bright future for FD-SOI and the i.MX 8 in automotive. It’s going to be a great ride.
By Ronald M. Martino, Vice President, i.MX Applications Processor and Advanced Technology Adoption, NXP Semiconductors
The latest generations of power efficient and full-featured applications processors in NXP’s very successful and broadly deployed i.MX platform are being manufactured on 28nm FD-SOI. The new i.MX 7 series leverages the 32-bit ARM v7-A core, targeting the general embedded, e-reader, medical, wearable and IoT markets, where power efficiency is paramount. The i.MX 8 series leverages the 64-bit ARM v8-A series, targeting automotive applications, especially driver information systems, as well as high-performance general embedded and advanced graphics applications.
Over 200 million i.MX SOCs have been shipped over six product generations since the i.MX line was first launched (by Freescale) in 2001. They’re in over 35 million vehicles today, are leaders in e-readers and pervasive in the general embedded space. But the landscape for the markets targeted by the i.MX 7 and i.MX 8 product lines are changing radically. While performance needs to be high, the real name of the game is power efficiency.
The bottom line in chip manufacturing is always cost. A move from 28nm HKMG to 14nm FinFET would entail up to a 50% cost increase. Would it be worth it? While FinFETs do boast impressive power-performance figures, for applications processors targeting IoT, embedded and automotive, we need to look beyond those figures, taking into account:
In fact, both NXP and the former Freescale have extremely deep SOI expertise. Freescale developed over 20 processors based on partially-depleted SOI over the last decade; and NXP, having pioneered SOI technology for high-voltage applications, has dozens of SOI-based product lines. So we all understand how SOI can help us strategically leverage power and performance. For us, FD-SOI is just the latest SOI technology, this time with a design flow almost identical to bulk, but on ultra-thin SOI wafers and some important additional perks like back-biasing.
When all the factors we care about for the new i.MX processor families are tallied up, FD-SOI comes out a clear winner for i.MX SOCs.
For our designers, here’s why FD-SOI is the right solution to the engineering challenges they faced in meeting evolving market needs.
In terms of power, you can lower the supply voltage (Vdd) – so you’re pulling less power from your energy source – and still get excellent performance. Add to that the dynamic back-biasing techniques (forward back-bias improves performance, while reverse back-bias reduces leakage) available with FD-SOI (but not with FinFETs), you get a very large dynamic operating range.
By dramatically reducing leakage, reverse back-biasing (RBB) gives you good power-performance at very low voltages and a wide range of temperatures. This is particularly important for IoT products, which will spend most of their time in very low-power standby mode followed by short bursts of performance-intense activity. We can meet the requirements for those high-performance instances with forward back-biasing (FBB) techniques. And because we can apply back-biasing dynamically, we can specify it to meet changing workload requirements on the fly. [Editor’s note: click here and here for helpful ASN articles with descriptions and discussions of back-biasing, which is also sometimes called body-biasing.]
Devices for IoT also have major analog and RF elements, which do not scale nearly so well as the digital parts of the chip. Furthermore analog and RF elements are very sensitive to voltage variations. It is important that the RF and analog blocks of the chip are not affected by the digital parts of a chip, which undergo strong, sudden signal switching. The major concerns for our analog/RF designers include gain, matching, variability, noise, power dissipation, and resistance. Traditionally they’ve used specialized techniques, but FD-SOI makes their job much easier and results in superior analog performance.
In terms of RF, FD-SOI greatly simplifies the integration of RF blocks for WiFi, Bluetooth or Zigbee, for example, into an SOC.
Soft error rates (SER)* are another important consideration, especially as the size and density of SOC memory arrays keep increasing. Bulk technology gets worse SER results with each technology node, while FD-SOI provides ever better SER reliability with each geometry shrink. In fact, 28nm FD-SOI provides 10 to 100 times better immunity to soft-errors than its bulk counterpart.
Our process development strategy has always been to leverage foundry standard technology and adapt it for our targeted applications, with a focus on differentiating technologies for performance and features. We typically reuse about 80% of our technology platform, and own our intellectual property (IP). Looking at the ease of porting existing platform technology and IP, and analyzing die size vs. die cost, again, FD-SOI came out the clear choice.
In terms of manufacturing, FD-SOI is a lower-risk solution. Integration is simpler, and turnaround time (TAT) is much faster. 28nm FD-SOI is a planar technology, so it’s lower complexity and extends our 28nm installed expertise base. Throughout the design cycle, we’ve worked closely with our foundry partner, Samsung. They provided outstanding support, and very quickly reached excellent yield levels, which is of course paramount for the rapid ramp we anticipate on these products.
In the second part of this article, we’ll take a look at the new i.MX product lines, and why FD-SOI is helping us make those game-changing plays for specific markets.
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* Soft errors occur when alpha or neutron particles hit memory cells and change their state, giving an incorrect read. These particles can either come from cosmic rays, or when radioactive atoms are released into the chips as materials decay.