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UFS or NVMe in Smartphone? See Apple’s answer!

UFS or NVMe in Smartphone? See Apple’s answer!
by Eric Esteve on 10-08-2015 at 7:00 am

There should be a link between iPhone H/W architecture and the incredible success of the product? Let’s assume and claim that this architecture, based on the internally developed ARM based A9 application processor, is simply the best on the market today…

Apple has implemented SSD in MacBook based on NVM Express (NVMe) protocol. It appears that Apple has adapted the NVMe controller developed for the MacBook to iPhone architecture (the red arrow on the picture below) and we will see that using SSD NVMe (instead of UFS) provide strong differentiation. I have found very exciting information from AnandTech, especially about the way Apple has implemented SSD control.

We need to take a look at above picture, presented by Sandisk during the last Flash Memory summit. Apple is present in three segments: High-End PC (MacBook), Productivity Tablets (iPad) and Flagship Smart Phone (iPhone 6). In the last segment, storage was based on eMMC until recently and now most of the OEM is implementing MIPI Universal Flash Storage (UFS) specification. Except Apple…

Let’s take a look at benchmark results: the two graphics at the top are for SSD sequential Read and Write, the other two are for random Read and Write.

Before explaining why sequential accesses are almost 2X more efficient than for the competition, let’s see the impact of such performance. Sequential read/write is what’s happen when you download/upload a very large file, like for example a movie, the faster, the better it is for user experience!

Another benefit is not as obvious. Improvement in performance also results in increased battery life: once the task is completed, the device can go back to idle state faster, positively impacting the power consumption.

Now we will have to understand why using NVM Express (based on PCI Express protocol) provides better user experience than UFS, based on Advanced Host Controller Interface (AHCI) which has been defined to support SATA. Once again a slide extracted from Sandisk presentation will help. According with Sandisk, NVMe has superior S/W stack than UFS, as you can see below. Other facts are supporting Sandisk position: the biggest advantage of NVMe is its lower latency (2.8 us compared with 6 us for AHCI based protocol). Another important improvement is support for multiple queues and higher queue depths. Multiple queues ensure that the CPU can be used to its full potential and that the IOPS is not bottlenecked by single core limitation.

At this point, we must clarify two points. First, Sandisk is clearly pushing NVMe adoption in flagship smartphone application and not MIPI UFS. The second point is that NVMe usage in smartphone is (most probably) still based on one MIPI specification, as the physical level MIPI M-PHY is selected and not PCIe PHY. It could be synthesized by:

NVM (Application) –> PCI Express (Transport) –> MIPI M-PHY (Physical Layer)

Using NVM Express protocol in smartphone application allows benefiting from the many advantages offered by MIPI M-PHY like reduced EMI or lower power consumption compared with other high speed PHY (USB 3.x or PCIe 2.0). One real advantage being that the SoC integrator has to buy (or develop), integrate and maintain a single PHY IP (the MIPI M-PHY) instead of several complexes PHY IP.

This decision from Apple to integrate NVMe instead of UFS in the iPhone 6s and 6s Plus, leading to better performances in term of Flash memory access and better user experience, is very important as it indicates that PCI Express has been adopted in this key industry sector. In fact, PCIe is used for a while in smartphone, to support the interface between the WiFi device and the AP. It was the reason why the MIPI Alliance and the PCI-SIG have jointly defined Mobile Express (or M-PCIe).

PCI Express has been initially defined (in 2004) to support the interface between the CPU and the GPU in the PC. Seeing PCIe protocol pervasion in mobile phone is a strong indication of technology merge between applications as different as PC and smartphone. Which work in one direction could also work in the reverse direction, ARM CPU, present in almost every smartphones, could start pervasion of the PC application…

Article from AnandTech can be found here

Sandisk presentation here

Eric Esteve from IPNEST


Dinner with the Man who is Reshaping the Semiconductor Industry!

Dinner with the Man who is Reshaping the Semiconductor Industry!
by Daniel Nenni on 10-07-2015 at 4:00 pm

The recent mega acquisition of Broadcom Corp by Avago can be traced all the way back to Silicon Valley stalwart Hewlett Packard (founded in a two car Palo Alto garage in 1939). Even more interesting is the man behind the acquisition and how he got to where he is today.Avago began as the semiconductor products division of HP in 1961, supplying parts to internal HP products. In 1999 HP spun off the division as part of Agilent technologies. In 2005 private equity firms KKR and Silver Lake Technologies acquired Agilent for $2.6B and formed Avago. In March 2006 Hock Tan joined Avago as CEO and director. Prior to that, Hock served as chairman of IDT, CEO of Integrated Circuit Systems, VP of Finance at Comodore International, and had senior management positions at Pepsi Co. and General Motors. He also has ties to the investment world in Singapore and Malaysia. Hock’s education is just as diverse as his experience with a BS/MS degree from MIT and an MBA from Harvard. Avago has an impressive 50 year history. You can see examples of their technology leadership and business milestones HERE. Not only does the Broadcom acquisition bring more products and customers under the Avago roof, it also brings the Broadcom name to the company that Hock will now run as Chief Executive. Hock’s other major acquisition for Avago was LSI Logic for $6.6B in 2014. The new Broadcom will be the number three semiconductor company behind Intel and Qualcomm I believe. It should also make Broadcom TSMC’s number one fabless customer (Apple is a systems company in my definition and QCOM is straddling Samsung and TSMC). My first Hock Tan sighting was at TSMC’s 2015 North American Technology Symposium. Hock was guest speaker and he struck me as a no nonsense type of guy who says it like it is. I’m also told he runs a VERY tight ship and has a VERY close relationship with TSMC and other manufacturing partners. In my quest to learn more about the man who is reshaping our industry I will be attending the annual CASPA conference and dinner banquet “Pioneering Technologies – Year 2020 in the Making” on October 24[SUP]th[/SUP] at the Santa Clara Convention Center. Hock Tan will be giving the executive keynote. It was a full house last year so you had better get your tickets quick!Registration: hereAnnual Conference Agenda:

  • 12:00-1:00pm, Registration & Networking
  • 1:00-1:30pm, CASPA Board of Director Election (first 200 voters receive gift)
  • 1:30-1:40pm, Welcome from CASPA
  • 1:40-2:15pm, M2M: The Embedded Revolution

—- Stephen DiFranco, Senior VP, Broadcom

  • 2:15-2:50pm, Memory Technologies for 2020, Broader Market Survey & Roadmap

—- Charlie Cheng, CEO, Kilopass Technology

  • 2:50-3:25pm, Global Mega Trends and the New Semiconductor Pioneers

—- Stuart Ching, Senior VP, ARM

  • 3:25-3:40pm, prize drawing
  • 3:40-4:50pm, Panel: Leaders in the Making – How to Transform from Engineers to Executives

—- Larry Chang, Executive Advisor at Ascend—- Buck Gee, Member of Committee of 100—- Thi La, COO of Corsair Memory

  • 4:50 ¨C 5:00pm BOD Election Announcement & Prizes Drawing (Apple Watch)

Dinner Banquet Agenda:

  • 5:00-6:15pm, Registration & Networking
  • 6:15-7:00pm, Banquet Seating & Dinner
  • 7:00-7:15pm, Retiring Board of Directors Service Recognition Awards
  • 7:15-7:45pm, CASPA 2015-2016 Presidential Transition
  • 7:45-8:15pm, Executive Keynote: Hock Tan, CEO, Avago Technologies

My beautiful wife and I will be there and we hope to see you then!Founded in 1991, CASPA has developed into the largest Chinese American semiconductor professional organization worldwide. CASPA consists of individual members, corporate sponsors, board of directors, board of advisors, board of volunteers, and honorary advisors. Headquartered in Silicon Valley, California, CASPA has 9 local chapters worldwide: Austin & Dallas Texas; Phoenix Arizona; Portland Oregon; HsinChu Taiwan, Pearl River Delta (Hong Kong, ShenZhen), Shanghai, Beijing and Singapore. CASPA also forms alliance with other associations to promote welfare of its members.


Coventor prepping MEMS for CMOS integration

Coventor prepping MEMS for CMOS integration
by Don Dingee on 10-07-2015 at 12:00 pm

About 11 months ago, I wrote a piece titled “Money for data and your MEMS for free.” In that, I took on the thinking that TSMC is just going to ride into town, fab trillions of IoT sensors, and they all will be 2.6 cents ten years from now. Good headline, but the technology and economics are not that simple. This may be the semiconductor version of putting a man on the moon by 1970, but instead of one big rocket, we are building little things.

My view is three basic classes of “sensors” are likely to emerge on that 10-year horizon: the RFID-like passive tag at something around 2 cents, the mass-market accelerometer at maybe 50 cents, and the high-performance RF switch or spectrometer at $5. The first category will have everything from printed electronics to integrated CMOS tags from TSMC and others. The last category will remain territory for boutique MEMS fabs.

In the middle, there is room for debate and innovation.

I also noted recent discussion in our “Inside the iPhone 6s” thread. In that, our Tom Simon noted two different accelerometers from different suppliers on the BOM, and reader @nick_rb replied that one is a high precision, higher power 6-axis IMU (Invensense), and the other a basic 3-axis unit (Bosch). That is a very revealing fact about the state of MEMS sensors today: performance isn’t cheap, in either BOM cost or power.

The problem in the middle, and the biggest barrier to the TSMC vision, is the MEMS process itself and the integration challenges with CMOS logic. Coventor draws on the Chipworks teardown of the Apple Watch for a compelling example:


The Apple S1 is not just a chip. It is a system on module, with 30 die integrated in a single package. It has everything from the processor to the touch sensor to the Bluetooth and Wi-Fi controller and more. Everything, that is, except the MEMS components, a 6-axis ST motion sensor and a Knowles microphone.

Ample IoT opportunity exists, even when one tones down the hype of trillions of units. Better CMOS process integration would certainly create more design flexibility and open the potential for lower costs – at least for some MEMS sensor types. The question: how do we do this? The current CMOS and MEMS processes are at direct odds, from EDA tools and design rules to physical construction:


Coventor has collaborated with X-FAB to launch MEMS+ 6.0, the latest version of their MEMS EDA tool with all new capability for process design kits (MEMS PDKs). Rather than leaving MEMS design up to handcrafted microbrewing, the idea centers on a library of simplified high-order finite elements for faster simulation and smoother exporting into a CMOS EDA flow. By enforcing process constraints and design rules, the generic MEMS library components can be customized to meet many requirements without breaking everything.

MEMS+ 6.0 also improves the flow for the experienced MEMS designer. Its model reduction capability exports in MathWorks Simulink or Verilog-A, with automated reduced-order models providing higher accuracy and faster results. These models abstract design details, so they can be provided to third parties without exposing the secret sauce – again, critical for integration. There is also a notion of design hierarchy and sub-structures for improved schematic reuse and faster model changes.

The resulting EDA flow with MEMS+ 6.0 looks like this, using Cadence as an example:


Coventor has done two things with MEMS+ 6.0. They have lowered the traditional wall between the MEMS designer working in the microstructure domain and the CMOS designer working in a typical mixed-signal EDA flow. If we are going to create and build more IoT devices quickly, this is a big step – similar to the improvements in mixed-signal EDA tools just a few years ago.

The second has bigger implications. CMOS foundries can now offer a level of mainstream MEMS fab capability, reliably modeled and compatible with their flow. MEMS purists will probably point out this won’t tackle every MEMS sensor type or precision requirements, and I don’t expect it to put the boutiques out of business. TSMC is probably in the “see, I told you this was happening” camp. I’d go back to something I’ve said before: we don’t have 2 cent MCUs for a reason. Never confuse technology with economic feasibility, especially for consumer space.

This type of development could open up what I’ll call the sub-$1 integrated MEMS segment for now. One aspect to watch is who else adopts Coventor MEMS+ 6.0 for on what process. (From the announced partnership, I’m assuming we can count X-FAB in.) TSMC, Intel, and others are pushing the big wafer start and advanced node story for digital SoC design. Wearable and IoT parts may very well be built on a generation or two back – remember, ARM recently came out with a strong focus on TSMC 55ULP.

It is good to see energy applied toward solving this for MEMS and the IoT. Full press release:

Coventor Announces MEMS+ 6.0 Platform for MEMS/IoT Integration

More articles from Don…


12 Reasons to Attend this Annual User Group Meeting for Transistor-level IC Designers

12 Reasons to Attend this Annual User Group Meeting for Transistor-level IC Designers
by Daniel Payne on 10-07-2015 at 7:00 am

My first job out of college was transistor-level circuit design of DRAMs at Intel, so I’ve continued to be fascinated with both the craft and science of designing, optimizing, verifying and debugging custom ICs. Last October I traveled to Munich, Germany to attend a two day user group meeting for engineers using tools from EDA vendor MunEDA. This year the MunEDA User Group Meeting is again a two day event held onOctober 27th and 28th in Munich Germany.


Munich, Germany

12 Reasons
You probably need some reasons to convince your manager that this two day user group meeting will be worth your time, so here are 12 good reasons on why you should attend and learn more about relevant topics like:

[LIST=1]

  • Custom circuit design migration and IP porting
  • Low-power optimization of custom IC designs
  • Advanced node designs (FinFET, FD-SOI)
  • Ultra high sigma and yield analysis and optimization
  • Memory design (SRAM, DRAM, Flash, FPGA, FTP, PCM)
  • Standard cell and I/O library design
  • Circuit and process modeling and model characterization
  • Reliability, aging and degradation based design
  • Circuit robustness verification and sign-off
  • Multiple topologies exploration
  • Smart power applications in general
  • High power designs (BCD technologies)

    These are the typical topics with presentations from actual tool users, and yes there’ll be a few presentations from MunEDA and I found them to be quite technical and detailed. Last year I watched presentations from companies like: SMIC, Lantiq, Novatek, STMicroelectronics, Infineon, Sapienza University in Rome, Altera, HLMC, Fraunhofer, University of Frankfurt and ARP Microsystems. Attendees receive a binder with all of the presentations, so if you like to take notes on the paper slides then it’s ideal. There was quite the range of process nodes talked about in the presentations from mature 180 nm AMS nodes to bleeding-edge FinFET nodes and everything in between.

    In addition to the technical aspects of a user group meeting, there was plenty of time to network and socialize. My favorite social event was the dinner on the first night at a historic beer hall where we had a private room, great food, beer for the drinkers (water for me), and time to get better acquainted with key people from MunEDA. This user group meeting is kind of unique because of how close you get to know other attendees.

    EDA Tools
    The product family from MunEDA is called WiCkeD and it’s a collection of EDA tools that allow a circuit designer to do five major tasks more easily and efficiently for custom IC designs:

    • Design Migration
    • Modelling
    • Verification and Optimization
    • Design Centering
    • Statistical Design Analysis


    Monte Carlo Analysis

    Summary

    User group meetings like this one are a great place to meet other circuit designers, learn something new, and even talk directly with the development team to learn how to get the best results of your MunEDAtools. Get more information and register here.

    Related


  • A FinFET BSIM-CMG model update from UC-Berkeley

    A FinFET BSIM-CMG model update from UC-Berkeley
    by Tom Dillinger on 10-06-2015 at 4:00 pm

    Every designer relies upon an underlying “compact” device model for circuit simulations – these models are the lifeblood of the IC industry. Designers may not be aware that there is an organization that qualifies models – the Compact Model Coalition – which operates under the umbrella of the Si2 Consortium: http://www.si2.org/cmc_index.php .

    This model qualification is a key milestone, as it enables EDA vendors to adapt their circuit simulation tools accordingly, with the knowledge that foundries will provide corresponding technology process parameters for this model in their process design kit (PDK) releases. (Foundries may add a software layer on top of these underlying models, to provide additional functionality – e.g, TSMC’s Technology Model Interface, or TMI.)

    The initial FinFET process technology model endorsed by the CMC was the BSIM-CMG format in March, 2012, from the theoretical device modeling team at the University of California-Berkeley (CMG = Common Multi-Gate FinFET topology):http://www-device.eecs.berkeley.edu/bsim/?page=BSIMCMG

    This site includes the current model documentation and source code.

    The existing model made some simplifying assumptions when solving field/charge distribution equations, most notably that the fin cross-sections were rectangular. The initial fins from the fabs were most definitely not rectangular:

    The BSIM modeling team at UC-B has developed an enhanced FinFET model format, to support an arbitrary fin profile, as described in their recent VLSI Technology Symposium technical paper:

    Khandelwal., S., et al, “New Industry Standard FinFET Compact Model for Future Technology Nodes”, 2015 Symposium on VLSI Technology, paper 6-4, pages T62-63.

    Rather than rectangular measures of fin height and thickness as inputs, the new field/charge model formulation uses the fin area, perimeter, and gate-to-channel capacitance to describe the (arbitrary) fin profile.

    This new model also incorporates additional features, in anticipation of new fin materials and/or different device construction (e.g., for the 5nm process node):

    • a pFET fin channel comprised of Germanium (requiring unique mobility modeling support)
    • an nFET fin channel comprised of a III-V semiconductor (with unique mobility modeling for InGaAs)
    • a new model formulation for the “density-of-states” energy levels and free carrier occupation
    • new model support for a gate-all-around (GAA, or “nanowire”) device topology

    Note that the electric field-dependent carrier mobility equations are significantly different for Germanium and (especially) III-V materials from Silicon.

    Also, at very small dimensions, the density of free (electron/hole) states in the channel at the (conduction/valence) band edges is limited – a unique carrier density versus energy calculation is required. The net result is the device currents are reduced.

    The expectations for this new model are better fitting accuracy to silicon, and better preparation for future process nodes, whether extending traditional fin technology with new materials, or the introduction of nanowires. The technical paper highlights examples of the improved fitting, both for 14nm FinFET’s and (early) GAA devices:

    Of course, model accuracy is important, but not at the expense of the circuit simulation runtime, as a significant percentage of the calculations are within device models. The UC-B team profiled model performance and has also significantly enhanced the throughput with this new model.

    The figure shows runtime comparisons between the current and proposed models for field/charge calculations, the temperature- and voltage-dependent equations, and the total execution time. (Runtime results for both bulk FinFET’s and FinFET’s fabricated on an SOI layer are shown.)

    The CMC qualification and EDA vendor simulation plus foundry PDK techfile support for this new, increased accuracy model is still in flight. Ideally, the impact of this transition to designers will be as straightforward as installing a new release. (It wouldn’t hurt to contact your CMC council representative to encourage a prompt review of this new model, as the performance improvements alone are compelling.)

    To be sure, there are still plenty of model development challenges ahead.

    The (mature) BSIM models for planar FET devices include current-modifying parameters representing layout-dependent and materials stress effects. The related layout widths and spacings around the modeled devices as included as base BSIM model parameters:

    http://www-device.eecs.berkeley.edu/bsim/Files/BSIM6/BSIM6.1.1/BSIM6.1.1_Technical_Manual.pdf (Chapters 16 and 19)

    FinFET’s add the complication of “N fins per layout finger”, where layout-dependent effects (LDE’s) may modulate the behavior of edge fins relative to internal fins.

    That level of maturity is not yet reflected in the BSIM-CMG model. For example, LDE’s must currently be supported as part of the foundry’s software algorithms, which then invoke the underlying BSIM-CMG code.

    Kudos to the BSIM-CMG model development team for their recent breakthrough!

    Look for ongoing enhancements from the team to this new “arbitrary fin profile” model. And, look for announcements from the CMC, both for their endorsement of this latest model format, and approval of a (relatively new) initiative for a standard application programming interface for the foundry’s software layer that invokes the BSIM-CMG model.

    -chipguy


    Secured SAM A5D4 MCU for Industrial, Fitness or IoT Display

    Secured SAM A5D4 MCU for Industrial, Fitness or IoT Display
    by Eric Esteve on 10-06-2015 at 12:00 pm

    The new SAMA5D4, ARM Cortex-A5-based, expands the SAMA5 microprocessors family, adding a 720p resolution hardware video decoder to target Human Machine Interface (HMI), control panel and IoT applications when high performance display capability are required. Cortex-A5 offers raw performance of 945 DMIPS (@ 600 MHz) completed by ARM NEON 128-bit SIMD (single instruction, multiple data) DSP architecture extension. To target applications like home automation, surveillance camera, control panels for security or industrial and residential gateways, high DMIPS computing is not enough. To make the difference, on top of dedicated video decoder (H264, VP8, MPEG4) in hardware, you need the most complete set of security features.

    Whether for home automation purpose or for industrial HMI, you want your system to be safeguarded from hackers and also your investment to be protected against counterfeiting. You have the option to select 16-b DDR2 interface, or 32-b if you need better performance, but security is not anymore an option. Designing with Atmel SAMA5D4 will guarantee secure boot, include ARM Trust Zone, encrypted DDR bus, tamper detection pins and secure data storage. The SAMA5D4 also integrates hardware encryption engines supporting such as AES (Advanced Encryption Standard)/3DES (Triple Data Encryption Standard), RSA (Rivest-Shamir-Adleman), ECC (Elliptic Curves Cryptography), as well as SHA (Secure Hash Algorithm) and TRNG (True Random Number Generator).

    If you design fitness equipment, such as treadmills and exercise machines, you may be more sensitive to connectivity and user interface functions than to security features, even if it’s important to feel safe in respect with counterfeiting. Connectivity includes Gigabit and 10/100 Ethernet and up to two High-Speed USB ports (configurable as two hosts or one host and one device port) and one High Speed Inter-Chip Interface (HSIC) port, several SDIO/SD/MMC, dual CAN, Etc. Because the SAMA5D4 is intended to support industrial, consumer or IoT application requiring efficient display capabilities, it integrates LCD controllers with graphics accelerator, resistive touchscreen controller, camera interface and the above mentioned 720p 30 fps video decoder.

    The MCU market is very competitive, most of the products are developed around the same ARM based family of cores (from Cortex-M series to Cortex-A5), so the key importance of differentiation. Performance is an important differentiation factor, and the SAM A5D4 is the highest performing MPUs in the Atmel ARM Cortex-A5 based MPU family, offering up to 945 DMIPS (@ 600 MHz) completed by DSP extension ARM NEON 128-bit SIMD (single instruction, multiple data). Using safety and security on top of performance to augment differentiation is certainly an efficient architecture choice. As you can see in the block diagram below, the part features the ARM TrustZone system-wide approach to security, completed by advanced security features to protect the application software from counterfeiting, like encrypted DDR bus, tamper detection pins and secure data storage. But that’s not enough and the MCU also integrates hardware encryption engines supporting such as AES/3DES, RSA, ECC, as well as SHA and TRNG.

    The SAMA5 series target industrial or fitness applications where safety is also a differentiating factor. If security helps protecting the software asset and makes the system robust against hacking, safety directly protects the user. The user can be the woman on the treadmills above pictured, or it can be the various machines connected to the display that SAMA5 MCU pilots. The SAMA5 series includes functions that ease the implementation of safety standards such as IEC61508. These include a main crystal oscillator clock with failure detector, POR (power-on reset), independent watchdog timers, write protection register, etc.

    Cortex A5 Atmel’s SMART SAM A5D4 is a medium-heavier processor and well suited for IoT, Control Panels, HMI, and the like, differentiating from other Atmel’s MCU by the means of performance and security (and safety). The ARM Cortex-A5 based MCU delivers up to 945 DMIPS when running at 600 MHz, completed by DSP architecture extension ARM NEON 128-bit SIMD. The most important factor differentiating SAM A5D4 is probably the many security features implemented, from ARM TrustZone to encrypted DDR bus, tamper detection pins, secure data storage and various hardware encryption engines (AES/3DES, RSA, ECC, SHA and TRNG). These security features protects OEM software investment from counterfeiting, user privacy against hacking and safety features make the SAM A5D4 ideal for industrial, fitness or IoT applications.

    From Eric Esteve from IPNEST


    Nine Cost Considerations to Keep IP Relevant –Part2

    Nine Cost Considerations to Keep IP Relevant –Part2
    by Pawan Fangaria on 10-06-2015 at 7:00 am

    In the first part of this article I wrote about four types of costs which must be considered when an IP goes through design differentiation, customization, characterization, and selection and evaluation for acquisition. In this part of the article, I will discuss about the other five types of costs which must be considered to enhance the value of IP and keep the IP-based SoC business model growing. In general these costs are known by their simple terminology; however they need to be better understood in the modern context of IP so that the right level of investment in the IP can be justified from both sides – the IP provider and the SoC integrator. Let’s analyze these in their right perspective here.

    Cost of Qualification – The quality of IP, specifically design IP is a big question mark today. As you obtain the third-party IP blocks from different regions (which may have different quality culture) of the world, it’s imperative that they must be qualified in the premises of the SoC integrator before they can enter into the works. A preliminary assessment and evaluation of an IP must have been done as part of acquisition, but its actual qualification from quality and security perspective according to its intended use in the actual SoC environment must be done in-house by the SoC vendor. For example, an IP for automotive applications must be tested in the SoC environment under the intended temperature ranges and possible electromigration effects. This is essential to ensure the IP is bug-free to avoid resolving the IP bugs at the system-level which can be very unworthy and extremely costly. It’s not a complete verification of the IP or system; I will talk about verification in detail in a subsequent section. It’s a quick qualification of the IP in focus. Fractal Technologieshas a tool called Crossfire which has an option to quickly qualify your IP with all formats and the SoC environment in which the IP is intended to be used. Similarly there is IP Kit from Atrenta (now Synopsys) available at TSMCfor partners to qualify their soft IP against Atrenta’s SpyGlass provided checks. There may be other commercial or internal tools as well to assist in this acute need of qualifying the IP before its use.

    Cost of Integration – Although the cost of integration of an IP into an SoC falls into the purview of the SoC vendor, the onus of integration may come on the IP provider who needs to make sure the IP or subsystem along with the software bring-up works properly in the SoC environment. The matter of the fact is that the SoC integrator does not understand all of the IP that are going to be integrated into the SoC; so the SoC vendor has to hire domain experts in different areas. The IP provider in most cases has to work at the subsystem level when integrating an IP into an SoC.

    For an IP provider it’s like envisioning the system requirements and making provisions for those while working at the IP level. For example, in case of an interface IP the whole channel has to be modeled as per the system requirements; for a physical IP, the PPA has to be modeled with right level of trade-off according to the system requirements. The PHY has to be programmed to make a trade-off between PPA. In modern age, the range of PPA can be very wide in which case the IP has to be segmented into high-range for performance critical applications, mid-range to save power, and low-range to save cost. Again, for an IP with FinFET and smaller geometries, you may need to increase the area to spread the heat. Also the FinFET process varies between foundries, so if you are sourcing an IP from two different foundries, then you will also have to spend in unifying those characteristics to keep the final SoCs uniform. As an example Applesourced A9 SoCs for its iPhones 6s and 6s Plus from TSMC 16nm as well as Samsung 14nm foundries. So, at the system level their characteristics have to be matched to keep the power and performance uniform for all phones.

    Another level of complexity comes when you integrate analog with digital on the chip. The analog portion needs confirmation from the foundry, so it’s advisable to keep the analog content as less as possible. However moving things from analog to digital can be another complexity and will surely incur cost.

    Considering an IP from system perspective, it’s important that the package aspects are taken into account. This includes effects such as noise, signal integrity, ESD, and so on.

    More and more of system companies prefer team integration with the IP vendors where the IP team can work with the system team and contribute in SoC roadmap development for future innovative technologies. This is a smart move for giving a lead time to future technologies, provided confidentiality is maintained. These days we are also seeing full merger of IP companies into SoC companies. A flip side to these mergers is that a sustained continuation of such mergers may defeat the purpose of IP-based business model in the longer run.

    While integrating an IP into an SoC and optimizing it within the cost parameters for a particular target segment, the integration has to go through several trials to obtain the best optimized architecture. To save the cost of these trials, the IP and SoC industry is gearing towards automating this effort.


    ARMhas already developed tools for such automation. In the picture above there is ARM[SUP]®[/SUP] Socrates[SUP]TM[/SUP]design environment along with CoreLink[SUP]TM[/SUP] Creatorfor interconnect optimization and CoreSight[SUP]TM[/SUP] Creatorfor debugging. Read the article, “New Tool Suite to Accelerate SoC Integration” for more details on the “ARM IP Tooling Suite”.

    Cost of Verification – This is the most significant cost in an SoC, almost 2/3[SUP]rd[/SUP] of the total cost of the SoC. There are multiple verification engines for simulation, emulation, formal verification, virtual prototyping, FPGA prototyping, and post-silicon verification at different stages of an SoC design. The key idea is verification closure through complete coverage of the overall SoC. It’s in general very difficult and hard problem to get complete coverage of an SoC. These days the SoC vendors bring up the whole system and run applications on full chip through emulation, or validate the SoC through FPGA prototyping which has its own limitations. There is no way to guarantee complete verification other than the verification coverage metrics, so coverage driven verification gained importance where coverage obtained through different verification methods gets added up.

    With the expansion of SoC’s size and complexity including hardware, software, and firmware, the verification space of SoC also has expanded enormously. In such as scenario, imagine a configurable IP getting added up. How do you ensure all of its configurations are validated? It expands the verification space further, multiplied by the number of configurations. This keeps the cost of verification increasing.

    In the IP-based business model, along with the design IP, the idea of verification IP (VIP) also came with the sole intention of verification automation and reuse of test plan, test bench, and test suite across multiple designs to boost verification productivity. Similarly, standard verification methodologies came into practice for verification automation and testbench reuse, UVM (Unified Verification Methodology) being the most popular. However, UVM is good for IP and at most subsystem level. The system level test is the bottleneck and that is where the verification space blows up. At the system level, as we have seen, there are multiple verification engines in work and there are multiple IP and subsystems. There is no automated methodology and reuse of tests and testbench across these multiple design levels and engines. This increases the cost of verification exponentially.

    To automate verification and reuse at the system level, key initiatives are going on to establish software driven methodology based on use-cases and test scenarios. Accellerahas initiated a Portable Stimulus Working Group (PSWG) to establish a common standard of test and stimulus which can be used by a variety of users across different levels of design hierarchy (IP, subsystem, and system) under different execution platforms (simulation, emulation, FPGA prototyping, post-silicon, or any other) using different verification tools. Cadence, Mentor, and Brekerhave developed tools for system level verification; and they along with other PSWG contributors are working on establishing the common test standard and making their tools compliant with this standard. This can definitely start a new chapter in verification from system-level and reduce the burden of cost of verification by a large extent through test automation and reuse across multiple design hierarchies as well as verification engines. However, this methodology is yet to be established and needs semiconductor industry level investment, effort, and time. Read the article “Moving up Verification to Scenario Driven Methodology” for more details on this initiative.

    Cost of Learning – As the complexity of SoCs keeps growing the verification space is always open for new learning. In the last section, we talked about the use-case based verification methodology which is being explored for verification at the system-level. Even after this methodology is established, there will be a cost involved in training the verification engineers on this new methodology.

    In verification space newer formats, protocols, and standards keep emerging, especially in IoT, mobile, and automotive segments. This needs budget, time and effort set aside for design and verification engineers to learn. Moreover, the verification engineers need to have complete knowledge about the system and the environment or market segment in which the system is going to operate.

    Apart from the system and design, the learning has to happen at the process and foundry level as well. The advanced process nodes such as FinFET nodes are distinct with foundries and hence the learning effort gets multiplied. The design, verification, and process engineers need to work closely to understand the new process and its associated rules. The process engineers may need to work in the actual foundry environment to learn about the advanced technology aspects and impart that knowledge to the design and verification engineers for them to incorporate the same in the design and its verification.

    Cost of Redundancy – A peculiar scenario arises when you configure an IP to serve multiple requirements for different market segments. Not all the segments are served at the same time, so there are unused portions in the design and those can vary in different situations. This brings redundancy along with configurability. The redundant circuit may also consume power unnecessarily if not architected well enough to remain shut when not in use. Such wastage of power may not be completely eliminated through multi-mode operation of the SoC. Another case of redundancy comes when an IP characterized for a particular technology node is no longer reusable for another technology node through the use of automated technology migration tools; the IP needs a fresh architecture and rework. In such cases, a proper ROI analysis must be done for the IP to remain profitable in single use.

    Summary – There are methodologies being explored to reduce different types of costs through automation. However, it depends on the specific methodology and the type of cost that can be reduced. Moreover, the automation methodologies such as system-level synthesis and verification need to be established before they can be explored for wider use. Intermediaries such as eSilicon have come up that provide IP services for SoC vendors to do a pre-evaluation of IP integration into their SoCs before buying it. The eSilicon business model is very flexible where they can be paid for an IP either after pre-silicon evaluation or after production. The semiconductor ecosystem is trying to establish a series of drivers that can keep the IP costs in control and the IP-based SoC development model afloat.

    First part of this article is HERE.

    Pawan Kumar Fangaria
    Founder & President at www.fangarias.com


    Moore’s law limitations and gravitational collapse at lower process nodes

    Moore’s law limitations and gravitational collapse at lower process nodes
    by Vaibbhav Taraate on 10-05-2015 at 4:00 pm

    As stated in my previous article, about the complexity of the SOC with billions of transistors. It is essential to consider the real practical scenario for the two dimensional verses three dimensional structure of the chip. Although the new technological changes and evolution for the shrinking process node can create ease for the design of SOC still there is limitation due to fundamental laws.

    At the lower process node there is limit due to Einstein’s relativity theory. As none of the particle can travel through the material with more than speed of light ( Mainly affected due to dielectric constants). So the reality is the uneven distribution of power density at Tera Hertz of frequency. Even if the three dimensional routing architecture is also used then it will give birth to the variation of electric field across the surface of interconnect and it creates issues for the interconnect modeling and interconnect test validation. So this area need to be evolved. The 2 dimensional architecture of any chip can have variation in the form of ( x,y,p,v,t) but for the three dimensional chip architecture has always variation in the form of (x,y,z,p,v,t,E and power density) so it really involves the eight dimensional analysis below 14nm process node.

    According to uncertainty principle published during 1925-1927 by Heisenberge ” The more precisely the position is determined, the less precisely the momentum is known in this instant, and vice versa.” So for the 3 dimensional chip architecture it involves the tight relationship between the energy , time and even space and time. Due to shrinkage as atomic spacing reduces it creates the vertical and horizontal components at the surface of conductor and it leads to the power losses across the surface and can affect on the overall data convergence. For billion transistor SOC at Giga Hertz or Tera Hertz the performance is real bottleneck due to the atomic spacing and the speed of data transfer between the carriers.

    According to Landauer’s principle” There is minimum possible amount of energy required to erase one-bit of information and called as Landauer’s limit.” So according to Landauer’s principle if observer looses the information then it loses the ability to extract work. So for SOC at the lower process nodes it has greater impact in the data transfer from one node to the billion of nodes.

    According to Bekenstein the black holes should have well defined entropy. And even if we consider the variation of the temperature across the chip then according to the Bekenstein bound, ” There is maximum amount of information can be stored in the space which has finite energy” By considering this for the 3-dimensional SOCs the real issue is the decay of the data transfer at the higher speed due to the losses across the surface of interconnect and even it can lead to the gravitational collapse due to uneven distribution of the power density at lower process node at higher speed .

    So below 14 nano-meter for billion density SOC the performance and life of SOC is the real challenge for any chip designer and due to that shrinkage will have limitation even with the three dimensional architecture of the chip. The effect of the data transfer from one of the node to billions of nodes and gravitational collapse can be much higher below 10 nano-meter process node.

    In such scenario the doubling of transistor in Integrated Circuit will affect heavily and it will take much more time to double the transistors. So according to my mathematical calculations and analysis using the fundamental laws, “For billion transistor SOC below 10 nano-meter will take 36 to 38 months to double the transistors with the required improved performance.”.

    So at the lower process node there is requirement of the real evolution of the manufacturing processes and even design flows. So the universal modification in the Moore’s law is very much required. And the modified Moore’s law can be stated as ” The number of transistors in dense Integrated Circuit has to be doubled in approximately 36 to 38 months”. Even this will have greater impact on Rock’s law and manufacturing processes for three dimensional integrated circuits!

    Also read: Moore’s law observations and the analysis for year 2019


    Solidly Across the Chasm

    Solidly Across the Chasm
    by Paul McLellan on 10-05-2015 at 12:00 pm

    Last week I wrote about EDA companies crossing the chasm, with Jim Hogan (who needs no introduction) and Amit Gupta, CEO of Solido. So how did those rules work out for Solido?

    See also Getting EDA Across the Chasm: 15 Rules Before and 5 After

    The founding team of Solido:

    • discovered process variation for analog was a problem as companies moved to more advanced nodes
    • validated with 3 major accounts
    • raised $9M in VC funding
    • hired team, developed initial variation for analog products
    • innovated technology, and captured in 15 patents
    • partnered with Synopsys, Mentor, Cadence, Agilent for flow integration
    • Established the business licensing model
    • Iterated with lead customers to develop minimum viable product and establish product-market fit
    • generated first POs
    • survived the 2008 downturn when evals were canceled and customer budgets froze

    Post-chasm (now):

    • broadened product to address custom digital, standard cell and memory markets
    • iterated on sales recipe until found a winning formula
    • over 30 customers, over 1000 users
    • growing 60% year-on-year revenue, margin growth over 90% YoY, generating cash (so no need for further capital)
    • adding new product to leverage existing infrastructure

    As for that third phase for Solido, (exit aka liquidity event) they are still private so it hasn’t happened yet. But maybe the Hogan Midas touch will strike again: appear on Hogan’s small company stage one evening, get acquired (or in the case of Jasper, don’t even make it to the stage first).

    One part of the secret sauce of Solido (and also of Amit’s previous foray into founding EDA companies, Analog Design Automation) is that it is based mostly in Canada. Not even in a hipster city like Montréal or Vancouver, they are in Saskatoon, Saskatchewan. Outside of the city itself, there is a lot of farming all around, and not much else. Plus there is not even wheat around for a lot of the year, just snow.

    There are several advantages to being in Canada. An engineer (masters degree in CS or EE) is paid $C50-80K (that is $40-60K at the current exchange rate although the US dollar is unusually strong right now). However, the Canadian government provides R&D refundable tax credits and the loaded cost of an engineer ends up being about $20K/year. This is equivalent to India but with a much more convenient time-zone (they are due north of Denver).

    These credits apply anywhere in Canada, and not just for EDA. As a result there are startup ecosystems in a few cities such as Vancouver and Toronto. But there is more competition for hiring, leading to higher salaries (costs) and more issues with turnover than in Saskatoon.

    There is also Canadian investment money available from sources such as Golden Opportunities or BDC Venture Capital, the VC arm of the Business Development Bank of Canada.

    People who live in Saskatoon have a reason to be there, typically family. EDA is cool there, unlike in Silicon Valley, and there are limited hi-tech alternatives. There is no Facebook or Uber. As a result it is relatively easy to attract and retain talent. The University of Saskatchewan is there with Masters and PhD programs in electrical engineering, and another university not far away in Regina.

    Most exits are cross-border. The company is founded in Canada but gets acquired by a US company. Amit’s previous company, Analog Design Automation, was acquired by Synopsys, for example. If a company in Canada exits then there is one nice perk. In order to make it easy for farmers to pass their farm on to their children without having to break it up, Canada has a one-time capital gains tax exemption of $C750K. But it applies to everything, not just land transfer.

    Oh, and you remember that part from last week about selling the company as well as the product. You just got sold to. Probably not relevant, you are almost certainly not going to buy a company, but Wall Street types and CFOs read SemiWiki too. You never know when the right serendipitous conatct will come by. When I was at VaST we did a sizable deal with Intel because a random engineer wandered by our booth at DAC and wondered (the other meaning of wandered) what we did.


    What NoCs with virtual channels really do for SoCs

    What NoCs with virtual channels really do for SoCs
    by Don Dingee on 10-05-2015 at 7:00 am

    Most of us understand the basic concept of a virtual channel: mapping multiple channels of traffic, possibly of mixed priority, to a single physical link. Where priority varies, quality of service (QoS) settings can help ensure higher priority traffic flows unimpeded. SoC designers can capture the benefits of virtual channels inside a chip with network-on-chip (NoC) strategies. Continue reading “What NoCs with virtual channels really do for SoCs”