Now in its third year, the 2015 IEEE S3S Conference has evolved into the premier venue for sharing the latest and most important findings in the areas of process integration, advanced materials & materials processing, and device and circuit design for SOI, 3D and low-voltage microelectronics. World-class leading experts in their fields will come to this year’s S3S Conference to present, discuss and debate the most recent breakthroughs in their research.
This year’s program includes:
The conference also features several events tailored for socialization and peer-to-peer discussions, such as the welcome reception, the cookout and the interactive Poster & Reception Session which is a great place to meet new colleagues and learn and exchange insights on technical topics. Enjoy a light snack and a beverage of your choice while meandering around to meet and discuss technical issues with long-time colleagues and make connections with new and influential experts and decision makers in your field.
Take time to visit the local attractions of Sonoma County. Sonoma is well known for outdoor recreation, spas, golf, night life, shopping, culinary activities, arts and music and wineries. It is truly my pleasure to serve as the General Chair of the 2015 Conference. —Bruce Doris
Download the Advance Program
Find all the details about the conference on our website: s3sconference
Click here to go directly to the IEEE S3S Conference registration page.
Click here for hotel information. To be sure of getting a room at the special conference rate book before 18 September 2015.
The DoubleTree by Hilton Sonoma Wine Country, One Doubletree Drive, Rohnert Park, CA 94928
October 5th thru 8th, 2015
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For the first time, IBM engineers have designed and tested a fully integrated wavelength multiplexed silicon photonics chip, which the company says will soon enable manufacturing of 100 Gb/s optical transceivers (read the press release here). This will allow datacenters to offer greater data rates and bandwidth for cloud computing and Big Data applications.
Early in the program (back in 2007), IBM contributed a piece to ASN about why their photonics program is on SOI – you can read that here. (Most all photonics — except the lasers — are on SOI. You can read more ASN photonics pieces from Intel and others here.)
Silicon photonics greatly reduces data bottlenecks inside of systems and between computing components, improving response times and delivering faster insights from Big Data. IBM’s breakthrough enables the integration of different optical components side-by-side with electrical circuits on a single silicon chip using sub-100nm semiconductor technology.
IBM’s silicon photonics chips uses four distinct colors of light travelling within an optical fiber, rather than traditional copper wiring, to transmit data in and around a computing system. In just one second, this new transceiver is estimated to be capable of digitally sharing 63 million tweets or six million images, or downloading an entire high-definition digital movie in just two seconds.
IBM presented details at the recent 2015 Conference on Lasers and Electro Optics.
The IEEE SOI-3D-Subthreshold Microelectronics Technology Unified Conference (IEEE S3S) is welcoming papers until May 18, 2015.
Last year, the second edition of the IEEE S3S conference, founded upon the co-location of the IEEE International SOI Conference and the IEEE Subthreshold Microelectronics Conference was a great success targetting key topics and attracting even more participants than in 2013.
While paper submissions are still accepted, the 2015 edition of the conference already promises a rich content of high-level presentations.
Geoffrey Yeap from Qualcomm will open the plenary session. He will give us a broad overview of the Ultra-Low Power SoC technologies.
Invited speakers from major industries (Intel, On Semiconductor, ST, Freescale, NXP, Soitec and more) and from many prestigious academic institutions will share with us their views of the ongoing technical challenges related to SOI, Sub-VT and 3D integration.
There will be two short courses again this year: One on SOI Application, and the other on Monolithic 3D.
There will also be a class on Logic devices for 28nm and beyond as well as a fundamentals class on Robust Subthreshold Ultra-low-voltage Design of Digital and Analog/RF Circuits.
The Hot Topics session will, this year, be about Ultra-Low Power.
During the Rump session we will debate about the What does IoT mean for semiconductor technology?
Scope of the conference:
The Committee will review papers submitted by May 18 in the three following focus areas of the conference:
Silicon On Insulator (SOI): Ever increasing demand and advances in SOI and related technologies make it essential to meet and discuss new gains and accomplishments in the field. For over 35 years our conference has been the premier meeting of engineers and scientists dedicated to current trends in Silicon-On-Insulator technology. Previously unpublished papers are solicited in all areas of SOI technology and related devices, circuits and applications.
Subthreshold Microelectronics: Ultra-low-power microelectronics will expand the technological capability of handheld and wireless devices by dramatically improving battery life and portability. Ubiquitous sensor networks, RFID tags, implanted medical devices, portable biosensors, handheld devices, and space-based applications are among those that would benefit from extremely low power circuits. One of the most promising methods of achieving ultra-low-power microelectronics is to reduce the operating voltage to below the transistor threshold voltage, which can result in energy savings of more than 90% compared to conventional low-power microelectronics. Papers describing original research and concepts in any subject of ultra-low-power microelectronics will be considered.
3D Integration, including monolithic 3D IC or sequential 3D IC, allows us to scale Integrated Circuits “orthogonally” in addition to classical 2D device and interconnect scaling. This session will address the unique features of such stacking with special emphasis on wafer level bonding as a reliable and cost effective method, similar to the creation of SOI wafers. We will cover fabrication techniques, bonding methods as well as design and test methodologies. Novel inter-strata interconnect schemes will also be discussed. Previously unpublished papers are solicited in all of the above areas related to 3D implementation.
Students are encouraged to submit papers and compete for the Best Student paper awards. Details on paper submission are given on the call for papers webpage.
Paper submission deadline: 18 May, 2015
Notification of acceptance: 07 June, 2015
Short course date: 5 October, 2015
Conference date: 5 – 8 October, 2015
More details are available on the S3S website.
There’s been a significant uptick in patents related to fully-depleted SOI, according to a new report by KnowMade (click here to get the report brochure). The report looks at both FD-SOI and SOI-FinFETs (both of which are fully depleted technologies). More than 740 patent families have been published to date, of which planar FD-SOI accounts for 340 families. Following a rush of activity about 10 years ago there was a dip, but activity over the last couple of years has once again been very strong.
The report provides a comprehensive overview, essential patent data for fully depleted SOI, plus a searchable database with links. It identifies more than 30 patent holders of FD-SOI related intellectual property, providing in-depth analysis of key technology segments and key players. “The major proponents of the FD-SOI technology have strong IP arms, but other unexpected players known as not supporting FDSOI [including TSMC and Intel] are also present,” notes the report.
The following in-depth analysis, an IBS study entitled How FD-SOI will Enable Innovation and Growth in Mobile Platform Sales, concludes that the benefits of FD-SOI are overwhelming for mobile platforms through Q4/2017 based on a number of key metrics. In fact, FD-SOI has the ability to support three technology nodes, which can mean a useful lifetime through 2020 and beyond for digital designs and through 2030 for mixed-signal designs. Here are some of the highlights from the study.
First, let’s consider the markets we’re addressing.
The unit volume of smartphones and tablet computers is projected to reach nearly 3B units in 2020 worldwide. These mobile platforms need to have access to low-cost and low-power semiconductor products, including application processors and modems. Performance must also be enhanced, but this needs to be done within the cost and power consumption constraints.
Mobile platforms need essentially the same performance as notebook computers, but have to rely on much smaller battery capacity. They also need to support high-performance graphics and ever-greater data rates, including the support of 1Gbps when the 5G protocol is tested in 2018. Better cameras demands high-performance image signal processing. 3-D imaging, now under development, will require multiple image sensors. All of this needs to be accommodated with lower power consumption and lower cost.
It is significant that a high percentage of smartphones and tablet computers will be manufactured byChinese companies. Semiconductor technologies that increase battery lifetime without incurring additional costs or potentially providing lower cost can be very attractive to smartphone vendors.
The market requirements are clear, and our detailed analysis of various technology options, including bulk CMOS at 28nm and 20nm and FinFET at 16/14nm, shows FD-SOI is the best option for supporting the requirements of high-volume mobile platforms.
FinFETs have the potential to be in high volume in the future: the key issue is timing. Our analysis indicates that FinFETs have high design costs, along with high product costs. It is not realistic to expect FinFETs to be effective for the low-cost and low-power modems, application processors, and other processor engines for mobile platforms in 2016 and 2017.
FinFETs need to go through two phases in the 2015 to 2016 time frame to reach the point where they are suitable for low power and low cost applications.
In the first phase, they will be used in high-performance products such as processors for servers, FPGAs, graphics accelerators, and other similar product categories. This approach was used in the past for new-generation process technologies, where price premiums were obtained from the initial products. The time frame for the high-performance phase of 16/14nm FinFETs within the foundry environment can be 2015, 2016, and potentially 2017.
The high-performance phase can allow extensive characterization of the 16/14nm process and provide a good understanding of various categories of parasitic so that product yields can become high. There is also the need to establish design flows so that new products can be brought to the market within short design windows. The high priced product phase can position 16/14nm FinFETs to be potentially used in high volume, low cost products at a future time.
The second FinFET phase comprises the ramp-up to high volumes for high end processor engines for mobile platforms. High-end mobile platforms, including tablet computers and smartphones, can provide relatively high volumes for FinFET products if costs are competitive. Modems, application processors, and graphics functionality will be suited to the 16/14nm FinFETs from the foundries in the 2017 to 2018 time frame.
This type of methodical approach in solving the manufacturing challenges at 16/14nm can be applied to 10nm and 7nm FinFETs. There is the need to establish design flows that can yield high gate utilization as well as the ability to obtain high parametric yields. The time frame for the high-volume, low-cost phase of FinFETs can potentially be 2017 or 2018.
With the delays in ramping 16/14nm FinFETs into high volume until potentially 2017 or 2018, an alternate technology is needed to support the next phase of the mobile platform IC product supply, which can give low power consumption and low cost.
FD-SOI: Competitive Positioning
To provide visibly into the options for technology selection, IBS has analyzed projected wafer costs and gate costs for bulk CMOS, FD-SOI, and FinFETs. Considerations include processing steps, masks, wafer costs, die shrink area, tool depreciation and parametric yield. The results are shown in the following figures.
Processed wafer cost comparison for FD-SOI, bulk CMOS and bulk FinFETs at the 28nm through 16/14nm nodes. (Source: IBS)
Gate cost comparison for FD-SOI, bulk CMOS and bulk FinFETs at the 28nm through 16/14nm nodes. (Source: IBS)
The low cost per gate of 28nm wafers in Q4/2016 and Q4/2017 allows this technology node to have a long lifetime. The performance of 28nm FD-SOI is 30% higher compared to 28nm bulk CMOS, with leakage also being 30% lower. There are, consequently, significant benefits in using 28nm FD-SOI compared to 28nm bulk CMOS for the high volume cost- and power-sensitive applications.
Furthermore, the performance of 28nm FD SOI is 15% better than 20nm bulk CMOS, giving 28nm FD-SOI a potentially even longer lifetime.
The gate cost of 20nm FD-SOI is 20% lower than 20nm bulk CMOS, while offering 40% lower power. and 40% higher performance. The higher cost per gate of 20nm bulk CMOS compared to 20nm FD-SOI is due to the higher number of processing and masking steps. There are also parametric yield penalties at 20nm because of difficulties in controlling leakage. Fabless companies that choose 20nm bulk CMOS over 20nm FD-SOI (called 14nm by STMicroelectronics) risk to find themselves with a noncompetitive platform.
14nm FD-SOI (called 10nm by STMicroelectronics) has an almost 30% lower cost per gate than 14nm FinFETs (including 16nm FinFETs) in Q4/2017, which is a major advantage in price-sensitive applications. Power consumption and performance are expected to be comparable between two technologies.
Why the hesitation in using FD-SOI?
While we clearly see that the benefits of FD-SOI, we also recognize that there is an expectation in the semiconductor industry that Intel sets the bar, so if Intel is doing FinFETs, everyone else should, too. The financial metrics of Intel are, however, different from those applicable to the fabless-foundry ecosystem. Intel is obtaining large revenues from its data center processors. And even though the company has promoted its 14nm and Tri-Gate processors for mobile platforms, Intel’s success in this arena has not been outstanding to date. Intel has, however, delayed the high-volume production of its 14nm Tri-Gate from Q4/2013 to H1/2015 because of low yields. The yield challenges that Intel is experiencing at 14nm should be a warning to fabless-foundry companies of the difficulties in ramping 16/14nm FinFETs within relatively short time frames.
Nonetheless, the manufacturing ecosystem is committed to making FinFET successful, so the resources that have been committed to FD-SOI have been limited. There is also reluctance to admit that the decision to adopt FinFET was premature and a thorough analysis of the cost penalties was not done. A similar perspective applies to 20nm bulk CMOS in following the industry pattern for not having a thorough review of the cost and performance impact.
FD-SOI for High-Volume Applications
The benefits of FD-SOI are clear, and as the yield and cost problems related to 20nm bulk CMOS and 16/14nm FinFETs become clearer, it is expected that there will be increased momentum to adopt FD-SOI at 28nm, 20nm (14nm by STMicroelectronics), and 14nm (10nm by STMicroelectronics).
To recap, FD-SOI provides the following benefits for high-volume mobile multimedia platforms:
At 28nm, 20nm, and 14nm technologies, IBS concludes that FD-SOI is superior to competitive offerings for smartphones and tablet computers, and the advantages of FD-SOI extend through Q4/2017. As the supply base for FD-SOI strengthens, FD-SOI is expected to become a key part of the semiconductor supply chain ecosystem for high-volume applications such as smartphones and tablet computers.
The ecosystem in the semiconductor industry should focus on the technologies that optimize the benefits for customers.
By Ali Khakifirooz (Spansion)
One of the unique features of the FD-SOI technology is the ability of using a wide range of body bias to modulate the transistor VT. Unlike bulk planar technology, where the maximum body bias is limited by p-n junction leakage and potential latch-up, in FD-SOI technology the full range of forward body bias (FBB) is available owing to oxide isolation and the use of flip-well structure .
While designers are familiar with the concept of body biasing and have been using it in different forms for many years in bulk CMOS technology, concerns are occasionally raised – often from non-designers – about the complexity and effectiveness of body biasing in advanced nodes.
Body biasing has been known for many years  and was in fact identified as a key technology enabler in sub-0.1µm era by industry leaders . Although ironically the recent move to the FinFET structure removed this gadget from the designers’ toolbox, the need for body biasing is still echoed .
Early studies demonstrated the effectiveness of body biasing in reducing leakage, improving performance, and reducing variability and thereby worst-case power consumption in complex circuits [5-7]. It was, however, pointed out that due to the competing effect of other leakage mechanisms, such as band-to-band tunneling, the effectiveness of reverse body bias (RBB) in managing leakage diminishes with technology scaling . Nonetheless Intel continued using body biasing at least down to 45nm node .
Static Body Biasing
Device variability is one of the key detractors of product yield. Historically, the desktop-driven semiconductor industry used product binning to turn this natural performance variability into profit. However, it is known that changes in market demand or process may lead to significant imbalance between the demand and inventory . Moreover, with the emergence of mobile applications as the dominant technology driver  and strict power requirements, binning is not effective anymore. With the desire to reduce VDD below 0.8V in order to reduce active power, managing the device variability becomes increasingly important.
Body biasing has been long considered as an effective and relatively easy way to compensate for some of the process variations. Not only does it lead to a tighter performance distribution and better yield, but also by mitigating the guardband requirements for process corners and temperature variation, it leads to better performance and faster design cycle.
For example, in a media processor design in 65nm technology a 20% reduction in the worst-case delay was achieved by using an embedded FBB circuit . While most body biasing designs are geared toward keeping VT constant, it has been shown that a combination of VT and drive current control leads to significantly tighter distribution (an 85% reduction in variation) and 25% reduction in total power . These numbers are well comparable to the power saving expected from scaling the design by one technology node. Given the concerns about the saturation of cost scaling beyond 28nm, an FD-SOI design with a wide range of body biasing is thus very appealing.
Dynamic Body Biasing
For applications with varied workload, a more elaborate use of body bias is to adjust the transistor performance based on the workload. This can be, of course, combined with other known low-power techniques such as dynamic voltage and frequency scaling (DVFS), sleep transistors, power gating, etc. In particular, when combined with DVFS, the optimum VT for each VDD can be used to minimize total power .
Design Complexity and Area Overhead
Potentially added design complexity and area overhead due to body bias generation circuits and routing is sometimes voiced as a concern. Static body biasing is relatively easy to implement. Depending on the level of sophistication it requires some sensing circuits (leakage, delay, skew, temperature, etc.), charge pump circuits to generate the body bias, and a network to distribute it across the chip. In typical designs, this does not impose more than 1-2% area overhead. The design complexity is actually reduced as less resources are needed to meet target performance across process and temperature corners. Notable bulk CMOS designs that used body bias to reduce variability include Samsung’s ExynosTM SoC in both 32nm and 28nm node [13-14], and Oracle’s SPARC processors in 40nm .
Dynamic body biasing, on the other hand, needs additional system and software development. However, we do not expect this to be more complex than implementing any other low-power technique such as dynamic voltage scaling. An example is TI’s 45nm OMAP SoC that used body bias as a part of their SmartReflex technology (Figure 1) .
Figure 1. Example of combined dynamic body bias and voltage scaling in TI’s 45nm SoC . Proper VDD and body bias is selected based on the power mode and process corner. (Courtesy: ISSCC, TI)
No Body Effect?
While many bulk CMOS designs used body bias in some form, on the other end of the spectrum are the designs that used PD-SOI technology, where majority of the devices do not have a body contact. The lack of body effect in PD-SOI devices was claimed to help stacked transistors and passgates, leading to 15-25% speed improvement . For designers that prefer a zero-body-effect style, the move to FinFET or a thick BOX FD-SOI structure seems more natural. However, for mainstream applications where power and parametric yield are the main drivers, thin BOX FD-SOI and use of body bias is more sensible.
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 D. Jacquet, et al., “A 3 GHz dual core processor ARM CortexTM-A9 in 28 nm UTBB FD-SOI CMOS with ultra-wide voltage range and energy efficiency optimization,” IEEE JSSC, p. 812, 2014.
 M. Kube, R. Hori, O. Minato, and K. Sato, “A threshold voltage controlling circuit for short channel MOS integrated circuits,” ISSCC, p. 54, 1976.
 S. Thompson, I. Young, J. Greason, and M. Bohr, “Dual threshold voltage and substrate bias: Keys to high performance, low power, 0.1 µm logic designs,” Symp. VLSI Tech., p. 69, 1997.
 G. Yeap, “Smart mobile SoCs driving the semiconductor industry: technology trend, challenges and opportunities,” IEDM Tech. Dig., p. 1.3.1, 2013.
 M. Miyazaki, et al., “A 1000-MIPS/W microprocessor using speed adaptive threshold-voltage CMOS with forward bias,” ISSCC, p. 420, 2000.
 S. Narendra, et al., “1.1V 1GHz communication router with on-chip body bias in 150nm CMOS,” ISSCC, p. 218, 2002.
 J. Tchanz, et al., “Adaptive body bias for reducing impact of die-to-die and within-die parameter variations on microprocessor frequency and leakage,” ISSCC, p. 422, 2002.
 A. Keshavarzi, et al., “Technology scaling behavior of optimum reverse body bias for standby leakage power reduction in CMOS IC’s,” ISLPED, p. 252, 1999.
 F. Hamzaoglu, et al., A 153Mb-SRAM design with dynamic stability enhancement and leakage reduction in 45nm high-k metal-gate CMOS technology,” ISSCC, p. 376, 2008.
 J.Y. Chen, “GPU technology trends and future requirements,” IEDM Tech. Dig., p. 3, 2009.
 S. Nomura, et al., “A 9.7mW AAC-decoding, 620mW H.264 720p 60fps decoding, 8-core media processor with embedded forward-body-biasing and power-gating circuit in 65nm CMOS technology,” ISSCC, p. 262, 2008.
 M. Sumita, et al., “Mixed body-bias technique with fixed Vt and Ids generation circuits,” ISSCC, p. 158, 2004.
 S.-H. Yang, et al., “A 32nm high-k metal gate application processor with GHz multi-core CPU,” ISSCC, p. 214, 2012.
 Y. Shin, et al., “28nm high-k metal-gate heterogeneous quad-core CPUs for high-performance and energy efficient mobile application processor,” ISSCC, p. 154, 2013.
 J.L. Shin, et al., “A 40nm 16-core 128-thread CMT SPARC SoC processor,” ISSCC, p. 98, 2010.
 G. Gammie, et al., “A 45nm 3.5G baseband-and-multimedia application processor sing adaptive body-bias and ultra-low-power techniques, ISSCC, p. 258, 2008.
 M. Canada, et al., “A 580MHz RISC microprocessor in SOI,” ISSCC, p. 430, 1999.
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“If GLOBALFOUNDRIES has the ability to economically research, develop, and produce parts on 20 nm FD-SOI, they could be hitting one out of the park,” said Josh Walrath (citing the baseball expression for a big home run) in a long PC Perspectives article last fall (Oct. ’13). “The industry is clamoring for a product that can match the power characteristics of Intel’s 22 nm process.” In the article, entitled Next Gen Graphics and Process Migration: 20 nm and Beyond, he contends that “The Really Good Times are Over” for the breakneck advances we got use to seeing in GPUs in years past. For his gamer audience, he clearly charts the evolutions in chip design, nodes and graphics performance. Citing the challenges at 20nm and below, he suggest that “…FD-SOI seems like it answers most of the issues that crop up with the 22/20 nm node. It does not require massive design rule changes, it can re-use a lot of bulk silicon manufacturing technology, and it runs perfectly fine with planar transistors at 22/20 nm. In a gate-last configuration, FD-SOI with planar transistors actually looks like it outperforms and scales significantly better than Intel’s 22 nm Tri-Gate process.” A recommended read.
“At 14nm FD-SOI is much cheaper, 30-40% cheaper, than Intel’s technology,” Asen Asenov told David Manners in a recent Electronics Weekly post (see full post here). Asenov is CEO and Founder of Gold Standard Simulations (GSS). The subject of the post was how TSMC has turned to GSS for statistical analysis tools. Professor Asenov is a fan of ST’s FD-SOI, noted Manners. The main challenge is building the ecosystem, he concluded.
The new IEEE S3S conference promised rich content, as it merged both The IEEE International SOI Conference and the IEEE Subthreshold Microelectronics Conference, completed by an additional track on 3D Integration.
The result was an excellent conference, with outstanding presentations from key players in each of the three topics covered. This quality was reflected in the increased attendance: almost 50% more than at the SOI conference last year.
The new triptych at the heart of the conference was well illustrated by the plenary session, which combined a presentation on ST’s FD-SOI technology by Laurent LePailleur (STMicroelectronics), one on Low Power Design, by Bob Bordersen (UC Berkeley), and one on monolithic integration by Zvi Or-Bach (MonolithIC 3D™).
Professor Bordersen’s presentation dealt with power efficiency, explaining how developing dedicated units with a high level of parallelism and a low frequency can boost the number of operations performed for 1nJ of expanded power. He illustrated his point by showing how an 802.11a Dedicated Design for Computational Photography can reach 50,000 OP/nJ while an advanced quadcore microprocessor will not even reach 1 OP/nJ. Such is the price of flexibility….but the speaker claims this can be overcome by using reconfigurable interconnects.
The “Best SOI Paper” award went to a GlobalFoundries/IBM paper entitled “FinWidth Scaling for Improved Short Channel Control and Performance in Aggressively Scaled Channel Length SOI FinFETs.” The presenter, Abhijeet Paul (GF) explained how narrower Fins can be used to improve short channel effects while actually giving more effective current without degrading the on-resistance. (See the DIBL and SS improvement on the chart.)
The”Best SOI Student Paper” award went to H. Niebojewski for a detailed theoretical investigation of the technical requirements enabling introduction of self-aligned contacts at the 10nm node without additional circuit delay. This work by ST, CEA-Leti and IEMN was presented during the extensive session on planar FD-SOI that started with Laurent Grenouillet’s (CEA-Leti) invited talk. Laurent first updated us on 14nm FD-SOI performance: Impressive static performance has been reported at 0.9V as well as ROs running at 11.5ps/stage at the very low IOFF=5nA/µm (0.9V & FO3). Then he presented potential boosters to reach the 10nm node targets (+20% speed or -25% power @ same speed). Those boosters include BOX thinning, possibly combined with dual STI integration, to improve electrostatics and take full advantage of back-biasing as well as strain introduction in the N channel (in-plane stressors or sSOI) combined with P-channel germanidation.
sSOI (strained SOI) was also the topic of Ali Khakifirooz’ (IBM) late news paper, who showed how this material enables more than 20% drive current enhancement in FinFETs scaled at a gate pitch of 64nm (at this pitch, conventional stressors usually become mostly inefficient).
An impressive hot topics session was dedicated to RF CMOS.
J. Young (Skyworks) explained the power management challenges as data rates increase (5x/3 years). Peak power to average power ratio has moved from 2:1 to 7:1 while going from 3G to LTE. Advanced power management techniques such as Envelope Tracking can be used to boost your system’s efficiency from 31% to 41% when transferring data (compared to Average Power Tracking techniques), thus saving battery life.
Paul Hurwitz (TowerJazz) showed how SOI has become the dominant RF switch technology, and is still on the rise, with predictions of close to 70% of market share in 2014.
The conference also had a strong educational track this year, with 2 short courses (SOI and 3DI) and 2 fundamentals classes (SOI and Sub-Vt).
The SOI short course was actually not SOI-restricted, since it was addressing the challenges of designing for a new device technology. P. Flatresse (ST) and T. Bednar (IBM) covered the SOI technology parts (FD-SOI and SOI FinFETs for ASICs respectively), while D. Somasekhar (Intel) gave concrete examples of how the change of N/P performance balance, the improvement of gate control or the introduction of Mandrels has affected design. Other aspects were also covered: Design for Manufacturing (PDF), IP librairies (ARM) and design tools (Cadence) for the 14nm node, to make this short course very comprehensive.
The rump session hosted a friendly discussion about expectations for the 7nm node. It was argued that future scaling could come from 3DI, either through the use of monolithic 3D integration or stacking and TSVs because traditional scaling is facing too many challenges. Of course, 3DI may not yet be economically viable for most applications, and since it is compatible with traditional scaling, we might well see both developed in parallel.
3D integration was also the topic of another joint hot topics session covering various fields of investigation, like co-integration of InGaAs and Ge devices (AIST), or 3D cache architectures (CEA-Leti & List). A nice example was given by P. Batra (IBM) of two stacked eDRAM cache cores, where the 16Mb cache on one layer is controlled by the BIST on the other layer and vice-versa with the same efficiency as in the 2D operation.
The first edition of this new conference was very successful, with a good attendance, two sessions running in parallel, extensive educational tracks, a large poster session and a lot of very high quality content. The two hot topics sessions generated a lot of enthusiasm in the audience.
Similar sessions will be repeated at the conference’s next edition, in the San Francisco area. It promises to offer outstanding content once more, and we already urge you to plan to submit papers and attend it.
“The performance and power results on ARM processors on 28 nm FD-SOI are outstanding,” writes Josh Walrath in PC Perspectives. In a piece looking at where graphics are headed, he goes on to say, “FD-SOI seems like it answers most of the issues that crop up with the 22/20 nm node. It does not require massive design rule changes, it can re-use a lot of bulk silicon manufacturing technology, and it runs perfectly fine with planar transistors at 22/20 nm. In a gate-last configuration, FD-SOI with planar transistors actually looks like it outperforms and scales significantly better than Intel’s 22 nm Tri-Gate process.”