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Netspeed and NSITEXE talk about automotive design trends at 55DAC

Netspeed and NSITEXE talk about automotive design trends at 55DAC
by Tom Simon on 08-02-2018 at 12:00 pm

DAC is where both sides of the design equation come together for discussion and learning. This is what makes attending DAC discussion panels so interesting; you are going to hear from providers of tools, methodologies and IP as well as those who need to use them to deliver working solutions. There are few places where the interplay between design activity and the tools necessary to accomplish it are more important than in the rapidly changing area of automotive electronics. For decades cars basically had coils and capacitors. Then came radios. But in just the last few years the complexity of automotive electronics has leapt to the upper end of the spectrum.

As usual power efficiency and performance are essential, however, in addition, safety has become a top line requirement. So, it was interesting to see the “fireside chat” hosted at DAC by Netspeed on the topic of “Design for Safety and Reliability – ADAS and Autonomous Vehicle SoCs”. Netspeed CEO Sundari Mitra interviewed Hideki Sugimoto from NSITEXE, the Japan based supplier of SOC IP for automotive autonomous driving systems.

Sundari started the session off by pointing out that the rapid growth in automotive semiconductors is fueled largely by the development of ADAS and autonomous driving systems. She asked what are the major trends and what are the needs and challenges that are created by them. Sugimoto replied that he has seen three major trends.

The top OEMs and Tier One vendors have very specific performance, safety and power goals. It used to be that ASSPs worked well enough, but off the shelf parts, even when tailored for specific markets, are not good enough anymore. So now all the players are involved in some way with ASIC development.

Now, within ASIC design, there has been a need for a shift from hand tuning each part of a chip to achieve performance goals. This was fine when the SOCs has fewer blocks, but now the better way to meet requirements is to start at the top level and map out requirements thoroughly. The requirements need to be specified in terms of end use-case performance or power goals.

The last trend is the move towards heterogeneous computing. The SOCs needed for ADAS or autonomous vehicles are extremely complex and their performance cannot be improved just by adding more CPUs or GPUs. The right way to carefully match up the right mix of the above and also add special purpose processors and accelerators for things like machine learning. Sugimoto’s company NSITEXE has a strong track record in this area, so these observations are borne out of direct experience.

Sundari followed with a question on the specifics of a requirements driven approach to putting chips together. Sugimoto cited the need to really look at the system level and not just focus on the chip itself at the outset.

The main performance factors are throughput, latency and end to end QoS. At the same time, all of this needs to be done without compromising safety. Sugimoto pointed out that you can’t bolt on the safety elements later and you also cannot achieve your performance goals without considering the safety requirements early in the process.

Sugimoto feels that there are three must have capabilities in an architectural design solution for automotive chips. They are (a) handling heterogeneous compute elements and coherency (b) delivering high QoS across all types of workloads and (c) ASIL-D and ISO 26262 certification. Every one of these affects safety security and reliability. The maximum amount of data must be extracted from the sensors. This means higher bandwidth and more processing. Sugimoto emphasized heterogeneous computing is really the only solution. However, this makes the chip architecture more complex. Sugimoto sees Network on Chip as a critical tool for managing this complexity and still being able to achieve design goals. NoCs can help provide determinism in these systems through the addition of memory coherency and QoS, for instance. Naturally the NoC will also have to comply with ISO 26262.

Looking at the conversation it is clear that automotive is now the killer app for advanced SOC design tools. This is where the greatest challenges are. The combination of the unique environmental, power, safety and functional factors make this a very interesting prospect. I have been covering Netspeed for some time now and can see how they are looking at the automotive market as a space where their NoC technology can make a big difference. Their website has more information on designing SOCs for automotive applications. It’s worth taking a look.


KLAC gets an EUV Kicker

KLAC gets an EUV Kicker
by Robert Maire on 08-02-2018 at 7:00 am

KLAC put up a great quarter coming in at revenues of $1.07B and EPS of $2.22. Guidance is for $1.03B to $1.1B with EPS of $2 to $2.32. Both reported and guided were at the high end of the range and above consensus. We had suggested in our preview notes that KLAC would be the least impacted of the big three (AMAT, LRCX & KLAC) semi equipment companies by the current memory volatility.

That has turned out to be the case as KLAC will likely see less than a 10% slow down in shipments and essentially zero impact on revenue and earnings versus the 25% drop in revenues expected by Lam along with an EPS drop below the low end of the range. We still predict that AMAT will fall somewhere between KLAC’s zero revenue impact and Lam’s 25% fall off probably coming in at a 10%-15% drop in revenues.

KLAC is obviously much less exposed to the more volatile memory sector and thus didn’t see as much of the sharp increase or sharp decline and has historically been a more consistent performer. KLAC reported record high shipments, revenues and EPS in the quarter and continues its juggernaut like roll. The company also was more forceful about its view of the December quarter calling for a “sharp snap back” rather than the more nebulous “positive trajectory” offered up by Lam.

We expect memory capex spending to continue to be quickly modulated by pricing and demand trends with either long or short term volatility and cyclicality as the industry keeps one foot on the accelerator and the other on the brakes. Having a very good balance and diversification that KLAC has will provide more consistent longer term performance and likely deserves a higher multiple,as compared to others, for the reduced volatility. We also expect ASML to have a similar performance to KLAC with minimal memory impact given its steadier long term history.

Market positioning remains very strong as the industry needs metrology and yield management tools to get the process fine tuned before they go out and buy the process tools that vary more with demand and output.

An EUV kicker
The transition to EUV is anything but easy. Aside from ASML who is the obvious beneficiary of the transition we think that KLAC could see if not as much benefit but perhaps even more especially in the current early stages of the transition where the problems are the greatest. ASML’s EUV revenue also replaces its DUV revenue so there is a bit of an offset which KLAC does not see.

This compares to dep and etch players who have nothing but downside as the number of overall dep and etch steps will without doubt be lower under EUV processes as compared to DUV processes. We think that KLA is another way to play the EUV transition for those who do not want to put all their eggs in ASML’s basket.

Financials are best in the industry
With industry leading gross and operating margins coupled with ATM machine like cash generation, whats not to like. The financials underscore the pricing power of being the market leader in the process control part fo the industry.

More diversification coming
The pending Orbotech acquisition will bring even more diversification to KLA’s model and further insulate it from volatile single end markets. We think this addition of SAM to an already strong base will further strengthen the story.

China exposure helps KLA
KLA is likely seeing more benefit than others from the growing China market as a lot of money is being spent in China by chip companies trying to come up to speed and perfect processes. Something that is almost impossible to be done without KLA tools. While China has more alternative sources for process tools there are really no alternatives to KLA tools which they have to keep buying in quantity.

The Stock
We continue to favor KLAC over both LRCX and AMAT. Not only are the financials way better but the risk is much lower as demonstrated by KLAC’s performance this quarter which barely registered a blip at KLAC but is causing heartburn elsewhere. The company well deserves a higher multiple for this more consistent performance along with better financials and diversity.

This more consistent performance may not be as flashy on the way up but avoids the near term pain and stock gyrations on the way down. In general we feel a lot safer in KLAC stock right now and probably for a couple of quarters until we get better visibility on memory. The near term factors are most aligned with KLAC right now and their stock should be a better performer.


Accelerating the PCB Design-Analysis Optimization Loop

Accelerating the PCB Design-Analysis Optimization Loop
by Tom Dillinger on 08-01-2018 at 12:00 pm

With the increasing complexity and diversity of the mechanical constraints and electrical requirements in electronic product development, printed circuit board designers are faced with a number of difficult challenges:

  • generating accurate (S-parameter) simulation models for critical interface elements of the design – i.e., connectors sockets, (twisted-pair) cables
  • developing comprehensive simulation/analysis models for entire packaging solutions – e.g., rigid-flex board topologies
  • accelerating the design optimization-analysis feedback loop

Given the aggressive schedules allocated to PCB development, typically dependent upon completion of key IP/SoC/module design milestones, the last challenge above is especially critical. The evaluation of interface compliance measures – e.g., timing/voltage margins, eye diagrams, bit error rate estimates – may necessitate board design updates, which then need to be re-analyzed. Minimizing the time and engineering resource (and the risk of an error) to close on implementation-extraction-analysis iterations is crucial.

I had the opportunity to chat with Brad Griffin, Product Manager Group Director at Cadence, about these challenges, and some of the features incorporated in the recent Sigrity 2018 release that will significantly alleviate them.

Brad indicated, “Bridging the gap between the mechanical model of interface components and the corresponding electrical model for power integrity and signal integrity simulation is a key addition to this latest release. The Sigrity 3D Workbench takes the physical Allegro board model as input, and applies full-wave field solver technology to derive the S-parameter model for simulation.”

The examples below illustrate the mechanical model of board-mount connector pins, which would be presented to 3D Workbench for S-parameter model generation. (The “breakout” of the board trace is included in the full-wave field solver input, to the point where a 2D hybrid solver analysis of the PCB trace can be applied.) The physical models of cables, connectors, and sockets are also analyzed by 3D Workbench.

An illustration of how 3D Workbench is used in a larger flow is depicted below. Brad said,“This 3D Workbench capability is a new component of existing flows, such as the Serial Link Compliance validation solution shown in the figure.”

Brad continued, “Our internal IP group develops high-speed SerDes and parallel interface (DDRx) offerings, verified to the compliance measurements associated with industry standards. The Allegro and Sigrity teams collaborated closely with the IP group on the functionality and testing of 3D Workbench and the Sigrity 2018 release.”

With regards to the growing utilization of rigid-flex technology, Brad noted, “There is a comprehensive connection between the rigid-flex design and analysis flows. Allegro is integrated with the extraction and simulation features of Sigrity PI/SI. Again, a mix of full-wave models(from 3D Workbench)and 2D hybrid solver models can be extracted, stitched, and simulated.”

The figure below illustrates a rigid-flex design with the corresponding visualization of the Sigrity PowerDC results. (Note the power distribution in the flex cable to the mezzanine card on the right results in significant losses.)

Speaking of the integration between Allegro and Sigrity, Brad was excited about the productivity gains this enables. SI/PI engineers can make their design changes in the Sigrity environment, re-extract and simulate – e.g., a specific via array pattern optimized to meet loss targets. Brad highlighted, “A key feature in this release is that updates made in the Sigrity platform are directly incorporated into the Allegro model, without the need to re-draw.”

The handoff of “markup” requests from the SI engineer to the physical design team is eliminated, improving the rate of design closure (and reducing errors) in the final optimization phase before release for PCB fabrication.

Future Challenges

I asked Brad about upcoming challenges for PCB (and rigid-flex) designers.

“I’ll point out two of the areas we’re working on.”, Brad said. “In the future, support will be provided to work with encrypted mechanical component models, for improved security of the component vendor’s intellectual property.”

“And, with the growing complexity of board designs, combined with the higher datarate defined for future interface IP standards, full wave model accuracy(out to multiple harmonics of the fundamental)will be required for a larger set of models. Full-wave mesh topologies will be denser, requiring greater compute resources. The methodology leveraging both full-wave and hybrid solvers for extraction and simulation will be distributed across multiple machines.”

The 3D model generation capabilities, the support for full system model PI/SI analysis with the combination of solvers (including intricate rigid-flex topologies), and the focus on improving the PCB design-analysis optimization loop are all part of the enhancements in the recent Sigrity 2018 release (link).

-chipguy


AMS Experts Share IC Design Stories at #55DAC

AMS Experts Share IC Design Stories at #55DAC
by Daniel Payne on 08-01-2018 at 7:00 am

At #55DAC in SFO the first day is always the busiest on the exhibit floor, so Monday by lunch time I was hungry and took a short walk to the Marriott hotel nearby to listen to AMS experts from several companies talk about their EDA tool use, hosted by Synopsys:

  • Samsung
  • Toshiba Memory Corp.
  • NVIDIA
  • Seagate
  • Numem
  • Esperanto

Continue reading “AMS Experts Share IC Design Stories at #55DAC”


Verification Importance in Academia

Verification Importance in Academia
by Alex Tan on 07-31-2018 at 12:00 pm

“Testing can only prove the presence of bugs, not their absence,” stated the famous computer scientist Edsger Dijkstra. That notion rings true to the many college participants of the Hack@DAC competition offered during DAC 2018 in San Francisco. The goal of this competition is to develop tools and methods for identifying security vulnerabilities in the SoC designs using both third-party IP (3PIP) and in-house cores. The trustworthiness of such SoCs can be undermined by security bugs that are unintentionally introduced during the integration of the IPs.

During a 6-hour final trial, the finalists are requested to identify and report security bugs from an SoC that is released to them at the start of the day. The teams mimic the role of a security research team at the SoC integrator, in trying to find the security vulnerabilities and quickly dispatch them back to the design team –so they can be addressed before the SoC goes to market. The bug submissions from the teams are then scored in real time by industry experts. The team with highest score is declared as winner.

At the end of the competition, both Hackin’ Aggies from Texas A&M University and The Last Mohicans from IIT Kharagpur were both declared as winners. I had a subsequent interview with Professor Michael Quinn from Texas A&M, who has been actively shepherding the school’s team to take part in the competition and also joined by the Cadence staff who are coordinating the university programs: Dr. Patrick Haspel, Cadence Global Program Director of Academic and University Programs and Steve Brown, Marketing Director of Verification Fabric Products. Some excerpts from the Q&A session are included in the second half of this article.

DAC and Verification Engineers

Based on DAC 2015-2017 statistics, about 38% of the attendees are engineering professionals and about 10% are academia as shown in figure 1. Although there are other venues such as IEEE sponsored events that involved the academia, their participation in the industry sponsored events such as DAC or DVCon could be viewed an indicator for how much participation or interest is given in the ecosystems. Based on a subset of the statistics, verification engineer attendance consistently ranks third after CAD/application and design engineers (see figure 2).

A well rounded verification engineer demands proficiency in both the design implementation aspects as well as the functional verification techniques. We are accustomed to college programs providing training to be design engineers, computer scientists and process engineers –but no so much tailored for a verification engineer. This prompts the question on how we should prepare these professional candidates to be more adaptable to the industry requirements?

Cadence Academic Ties
Aside from their own R&D dollars, EDA companies innovate through the various synergistic partnerships among its ecosystems’ members, including their customers and the academia. Being at the forefront of the EDA ecosystem, Cadence has actively fostered a strong relationship with the academia through the Cadence® Academic Network program, which facilitates the exchange of knowledge by co-organizing educational events or trainings and providing access to the latest Cadence technologies. There are several notable subprograms related to this venture as tabulated here:

Interview with Professor Michael Quinn

Texas A&M University has been part of Cadence Academic Network Program and ranks first in Texas in term of student size. The university launches the 25-by-25 initiative, which targets an engineering enrollment of 25,000 by 2025 and this year boasts largest freshman female engineering class in the country. Its electrical and computer engineering programs recently were ranked 12th and 10th among public universities.

The following excerpts are from Q&A session with Professor Quinn:

Could you comment on current research emphasis in the area simulation/verification?
“From the verification standpoint, the biggest area getting looked at is associated with security. Texas A&M has a whole new department that has grown up for the past few years, very well endowed and it’s about security design, architecture and also verification. I think their biggest push in these area is in formal. Formal based approaches, not so much functional,” Prof. Quinn said. “By the way, we did (the contest) without using the formal tool,” he quipped.

Which Cadence tools do you use?
“My class uses all the simulation and visualization tools such as Xcelium. It starts just as an engineering verification job, with a specification planning using Cadence VPlanner. The students start developing the verification environment using Cadence UVM based methodology, which is superb as it supports the current IP design methodology,“ said Prof. Quinn. It also allows the students to incrementally do a bottom-up verification and integration works, starting with low-level IP and progressing to the SOC level. A key strength of such approach is the ability to seamlessly reuse of works previously applied at the lower-level. Subsequent verification and debug involves running random testings and the use of Vmanagerto tie various aspects of planning, testing, tracking and analysis together. And finally Indago, to efficiently manage debugging process.

Should the school program be geared towards software development mastery, hardware design proficiency or hands-on applications for EE candidates?
He believes we need all the above. A more well rounded designer is being looked for by companies and can be transitioned to different projects. Along this end, he aspires of having more courses that are inter-disciplinary, experiential in nature –and are based on multi-faceted curriculum that put together logic designers, architect plus software folks– would greatly enhance the learning experience.

What is the current state of engagements with Cadence?
Since its start in 2016 when only a handful of verification engineers entered into the industry from Texas A&M, the program has now contributed 100 or more. “It’s a win-win solution,” he said. Relating to his Drexel almamater, he believes the value of having a co-op program as good training ground for the incoming graduates. His wish is to be able to continue the efforts further and share his instructional works with an expanded network.

According to Dr. Haspel, part of the Cadence Academic Network team responsibilities is to connect the industry need of trained engineers and to enable students to not only learn but to be valuable also to the prospective employers. This is achieved through working with university on curriculum aligning, partnering with school that have the right mindsets to collaborate and arm them as the recruiting targets. Furthermore, he said “Sometimes it is the pipeline thing, but it is also the responsibility of the ecosystem…”

What is your impression on DAC presentations with respect to HW design?
Prof. Quinn is intrigued by the conference advising EDA vendors to pay more attention to big data, machine learning, security and data analytics. He concurs that it is the right feedback. He anticipates that post-silicon is able to contribute in the verification, which previously was not possible as data does not stop at tapeout. One may need a coverage monitoring –possibly at customer site by doing workload monitoring and feedback the simulation process. It is a big close-loop.

As the famous quote goes –“Tell me and I forget, teach me and I may remember, involve me and I learn.”– at DAC 2018 the Texas A&M team had demonstrated a slice of the fruitful outcomes from the EDA industry collaboration with academia. Kudo to Cadence and the Aeggis! Experiential learning really makes a difference.


Webinar: Differential Energy Analysis for Improved Performance/Watt in Mobile GPU

Webinar: Differential Energy Analysis for Improved Performance/Watt in Mobile GPU
by Bernard Murphy on 07-31-2018 at 7:00 am

May want to listen up; Qualcomm are going to be sharing how they do this. There is a constant battle in designing for low power; you don’t accurately know what the power consumption is going to be until you build it, but by the time you’ve built it, it’s too late to change the design. So you have to find methods to estimate power early on, while using that information in a way that won’t compromise your design choices because you were judging their impact based on eyeballed numbers.

This can appear difficult, particularly for RTL-based power estimation, which typically shows variance of around 15% on final gate-level estimates. Surely judging optimizations based on such coarse estimates would be very challenging unless the changes deliver massive advantages, greater than that margin of uncertainty?

In fact the picture is much better if you do differential analysis – comparing the difference in predicted power savings for different optimizations. While absolute power estimates carry that larger level of uncertainty, differences between estimates can be much more accurate for a fairly obvious reason. Differences subtract out many of the unknowns in absolute RTL power estimates: detailed cell and designware mapping, placement, routing, clock tree details and so on. What you’re left with can be much closer to equivalent differences based on signoff power numbers.

The people who build mobile solutions know more than almost all of us about squeezing out every last pico-watt of power. Apple isn’t likely to tell you what they do, but Qualcomm is just as good for learning about best practices in this domain.

Register HERE to learn more in this webinar on August 23[SUP]rd[/SUP] at 9am PDT

Summary:
Mobile devices demand high performance in a very constrained environment. As a leader in perf/watt, Qualcomm® Adreno™ GPUs, a product of Qualcomm Technologies, Inc., leverages many effective methods to improve power efficiency. In this regard, Qualcomm has developed a differential energy analysis methodology based on ANSYS PowerArtist to identify the power optimization opportunity in GPU. This methodology can help to locate the inefficient part that needs further optimization in the pre-silicon stage. Experimental results based on identifying unnecessary register toggles demonstrate the effectiveness of this proposed methodology.

Speakers:
Preeti Gupta, is head of RTL product management, for the ANSYS semiconductor business unit.

Yadong Wang is currently a staff engineer in the GPU system power team at Qualcomm Technologies, Inc., San Diego, California. He has about 10 years of ASIC low-power design experience. At Qualcomm, he is responsible for power modeling and analysis of Adreno™ GPUs, and explores and develops many effective methods to improve power efficiency. Before joining Qualcomm, he worked as a hardware power engineer at NVIDIA. Yadong earned an M.S. degree in electrical engineering from Tongji University (Shanghai, China) in 2009.

About ANSYS
If you’ve ever seen a rocket launch, flown on an airplane, driven a car, used a computer, touched a mobile device, crossed a bridge, or put on wearable technology, chances are you’ve used a product where ANSYS software played a critical role in its creation. ANSYS is the global leader in engineering simulation. We help the world’s most innovative companies deliver radically better products to their customers. By offering the best and broadest portfolio of engineering simulation software, we help them solve the most complex design challenges and engineer products limited only by imagination.


Machine Learning Meets Scan Diagnosis for Improved Yield Analysis

Machine Learning Meets Scan Diagnosis for Improved Yield Analysis
by Tom Simon on 07-30-2018 at 12:00 pm

Naturally, chips that fail test are a curse, however with the advent of Scan Logic Diagnosis these failures can become a blessing in disguise. Through this technique information gleaned from multiple tester runs can help pin down the locations of defects. Initially tools that did Scan Logic Diagnosis relied on the netlist to filter locations for various faults. This made it possible to exclude a number of potential locations. In the push to improve the so called “resolution” of the diagnosis, the tools started considering layout information. This went a long way toward narrowing down the list of potential fault locations.

When layout information was added to the mix, there was enough information to use the same data for yield analysis. However, even with the improved resolution in the number of suspects, the results from the diagnosis-driven yield analysis were not good enough. The engineers at Mentor realized that there was more information to be gleaned from the root cause analysis that comes from the test data and the design itself. What normally happens is that a number of potential root causes are identified and the probability of each one is reported. Each different failure will have a unique distribution of these potential root causes.

Mentor developed a technique called Root Cause Deconvolution (RCD) to help improve the fault location prediction. Mentor has a white paper on how RCD works and what kind of results it can provide. For a baseline, they conducted a simulated experiment to show how effective root cause prediction normally is. They injected two different types of single defects in different locations in a total of 470 devices. Without RCD the predicted root causes included 49 types of faults. Even the prediction of the second most probable root cause was not correct. They saw 47 probable root causes that did not correspond to any actual root cause.

When they ran with RCD the predictions narrowed dramatically down to just three root causes. This is a pretty significant improvement. RCD uses critical area information and then examines the design in detail to come up with probable root causes and their defect distributions. This data is then used to compare observed defects with the statistical information computed from the design. For realistic numbers of actual root causes the computation needed can rapidly explode. When using direct computation, even when considering only a few hundred root causes, the computational needs approach infinity. However, Mentor realized that machine learning can be used to help determine the number of relevant defect distributions that are worth looking at. It should be pointed out that machine learning is continuously finding new applications in the EDA space. This is not the first time that Mentor has decided to rely on machine learning to solve tough problems to deliver breakthrough results.

What is most interesting about RCD, as incorporated into their Tessent Diagnosis and Tessent YieldInsight, is that no additional data is required beyond what is normally needed for layout aware diagnosis. Also, in cases where diagnosis reports are encoded to protect proprietary information, the flow still works. Whenever RCD is used there are fewer probable root causes to look at, making resolving yield issues a much faster process. Because RCD’s design analysis actually can predict failure distributions in advance of failure analysis, it can open doors to more proactive yield enhancement. To learn more about how the entire process works, read the white paper entitled Leveraging Volume Scan Diagnosis Data for Yield Analysis that is available from the Mentor website.


Deep learning fueling the AI revolution with Interlaken IP Subsystem

Deep learning fueling the AI revolution with Interlaken IP Subsystem
by Daniel Nenni on 07-30-2018 at 7:00 am

AI is revolutionizing and transforming virtually every industry in the digital world. Advances in computing power and deep learning have enabled AI to reach a tipping point toward major disruption and rapid advancement. However, these applications require much higher performance and bandwidth requiring new kinds of IP and that brings us to Open-Silicon and the Interlaken IP.

Open-Silicon, a founding member of the Interlaken Alliance formed in 2007, launched the 8[SUP]th[/SUP]generation of Interlaken IP core supporting up to 1.2 Tbps bandwidth last year. This high-speed chip-to-chip interface IP features an architecture that is fully flexible, configurable and scalable.

The Interlaken IP subsystem originally developed for networking applications is enabling high speed chip to chip interface for deep learning SoCs. Open-Silicon’s eighth-generation Interlaken IP supports up to 1.2Tbps high-bandwidth performance and up to 56 Gbps SerDes rates with Forward Error Correction (FEC). Interlaken IP is a scalable, high-speed chip-to-chip interface protocol that builds on the channelization and per-channel flow control features of SPI4.2, while reducing the number of chip I/O pins by using high-speed SerDes technology, similar to XAUI. Open-Silicon’s ILKN FEC IP core meet the requirements Interlaken protocol to significantly improve bandwidth by enabling high speed SerDes integration. The FEC can easily achieve a BER (Bit Error Rate) of 10-15, which is required by most electrical interface standards using high speed SerDes built upon a flexible and robust architecture.

The updated Interlaken specification is capable of supporting SerDes beyond 30Gbps and up to 58Gbps—this was mainly because of the introduction of the peer-to-peer service, which allows sending more data on fewer lines. This led to development of Open-Silicon’s eighth generation Interlaken IP core, supporting up to 1.2 Tbps high performance and up to 56 Gbps SerDes rates with Forward Error Correction (FEC) https://www.open-silicon.com/open-silicon-ips/interlaken-controller-ip/

Key Features:

  • Fully-programmable SerDes lane mapping
  • Interlaken-LA 4-channel protocol
  • Up to 56 Gbps SerDes support
  • 1.2 Tbps high-bandwidth performance
  • Interlaken Retransmit Extension support

Standard Features:
In addition to the key features highlighted with the latest release, the Open-Silicon Interlaken IP also provides the following feature set as part of the standard IP functionality:

  • Support for 256 logical channels
  • 8-bit channel extension for up to 64K channels
  • Independent SerDes lane enable/disable
  • Support for SerDes speeds from 3.125Gbps to 56 Gbps
  • Configurable number of lanes from 1 to 48
  • Flexible user interface options:
    • 128b: 1x128b, 2x128b, 4x128b, or 8x128b
    • 256b: 1x256b, 2x256b, 4×256, or 8x256b
  • Programmable BURSTMAX from 64 bytes – 512 bytes
  • Programmable BURSTMIN from 32 bytes – 256 bytes
  • Simultaneous In-band and Out-of-Band flow control
  • Programmable calendar
  • Built-in error detection and interrupt structures
  • Configurable error injection mechanisms for test-ability

“Open-Silicon’s Interlaken IP Subsystem delivers the bandwidth scalability and performance we require for various artificial intelligence applications that require high speed inter-node connectivity. The Interlaken IP subsystem is extremely configurable and robust, which enables the high-bandwidth efficiencies required for deep learning SoCs.”-Open-Silicon Customer

Since 2007 Open-Silicon’s Interlaken IP has been deployed in several different tier-1 networking and computing customer products. Many of these products are shipping in production today in the latest technology nodes in multiple foundries. The unique flexibility and configurability built into Open-Silicon’s Interlaken core meets not only today’s technological requirements, but remains fully compatible with older designs.

Want to get a budgetary quote for Interlaken ASIC? Please fill out the Design Requirements Form.

About Open-Silicon
Open-Silicon is a system-optimized ASIC solution provider that innovates at every stage of design to deliver fully tested IP, silicon and platforms. To learn more, please visit www.open-silicon.com


Samsung Memory is easy come easy go but for how low?

Samsung Memory is easy come easy go but for how low?
by Robert Maire on 07-29-2018 at 8:00 am

Lam Research (LRCX) reported a great June quarter coming in at $3.126B in revenues and $5.31 in EPS easily beating the street’s $3.06B and EPS of $4.94. However no one will care as guidance for the September quarter is for $2.3B in revs and EPS of $3.20, way, well below the already downward revised estimates of $2.77B and $3.88.

As we had suggested in our preview notes, most analysts had underestimated the extent of the down turn in business. Guidance is well below even the lowest estimate on the street of $2.55B in revs and EPS of $3.53. We had projected a 25% decline which is exactly what management is guiding to.

At this point our thoughts turn to how long the down cycle will last and how much further down it will go?

This begs the question as to whether the slow down started by Samsung will spread to other memory makers and if foundry/logic will recover?

We think that most analysts will again underestimate the length of the down turn. In our years watching the industry we can’t think of very many downturns that were only one quarter or two quarters in length which suggests that we won’t get a recovery until 2019 at best. We highly doubt that Samsung would hit the breaks so hard for only a one or two quarter delay as the underlying issues are longer than that.

We would imagine that other memory makers will be wondering about their capex spending as well. We are in an uncertain period with many variables many of which are negative.

September low point or trough?
Management stated that it viewed the September quarter as the low point for the year. We are somewhat dubious of this given the history of the industry and our view that it seems strange for Samsung to hit the brakes so hard if they were just going to start spending again in a quarter or two.

Perhaps business from other customers can be pulled in such that some of the Samsung shortfall is made up. Management was careful not to predict timing of an uptick or length of the downturn.

How long the down turn?
If September is the “trough” the next question is how long do we stay at the trough? Its clear that there were push outs out of the September quarter and push outs out of 2018 into 2019.

We could be looking at a flat December quarter versus September with a recovery some time in 2019.
One issue we have is that logic/foundry has not been strong and in fact has been weak and not likely to make up for any memory weakness.

We listened very closely to the call and management carefully avoided suggesting an up December quarter but instead talked about long term generic positive platitudes.

There is no specific evidence that points to a recovery at this point but management has planted a flag in the ground to “call” a bottom (if only for 2018).

Single digit WFE growth
It now looks like 2018 WFE capex growth will be in the single digits. Much of this number will be determined by H2 performance which is obviously down in September but unknown beyond that. Its still too early to call 2019 and management also refrained from that prediction.

The stocks
We could see a relief rally as management’s spin is that the worst is behind us. We would caution that just as this downturn was a surprise so could we be surprised by either another leg down or a longer than expected time to recovery.

We are very dubious about those that will suggest that this is only a one quarter blip that we will quickly recover from as that is not anywhere near the norm for the industry and seems to belie the sharpness of the downturn.

We remain cautious on the group in general and more specifically memory related stocks. If we saw a big jump in the stock price we might take some money off the table before the euphoria subsides and reality kicks back in….


Daniel’s #55DAC Trip Report

Daniel’s #55DAC Trip Report
by Daniel Payne on 07-29-2018 at 7:00 am

Another year, another DAC, and last month it was #55DAC in SFO and the first thing that I noticed was that the event was no longer located in the traditional North or South Halls, rather we were in the smaller, Moscone West on two floors, almost like a 3D FinFET. Checkin to get my badge was highly automated and oh so fast, well done.
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