Each year, TSMC hosts two major events for customers – the Technology Symposium in the spring, and the Open Innovation Platform Ecosystem Forum in the fall. The Technology Symposium provides updates from TSMC on:
Continue reading “Top 10 Highlights from the TSMC Open Innovation Platform Ecosystem Forum”
Coverage is a common metric with many manifestation. During the ‘90s, both fault and test coverage were mainstream DFT (Design For Testability) terminologies used to indicate the percentage of a design being observable or tested. Its pervasive use was then spilled over into other design segments such as code coverage, formal coverage, STA timing analysis coverage, etc.
Motivation of having a code coverage
While the term coverage may provide the management team with a sense of how much testing was done on a targeted code or design, to the code developers or system designers it offers an additional measure on how stable are their incepted codes –to be fully realized or used in the production mode. In software development domain, code coverage measures the percentage of source code being exercised during test using a collection of test suites –the underlying axiom here is that a high percentage value indicates a lower chance of undetected bugs.
The primary code coverage criteria include function coverage (measures frequency of a program function is called); statement coverage or line coverage (measures the number of statements that are executed); branch coverage (measures the amount of branches being executed, such as if-else constructs) and condition coverage or predicate coverage (measures whether the Boolean sub-expression has been assessed either true and false).
Although it is hard to achieve a full coverage and the relationship between an attained code coverage level versus probability of a program being bug-free is non-linear, code coverage data offers many benefits. This includes improving the completeness and robustness of the existing test suites (such as to guide generation of missing test cases, to minimize a test suite for runtime reduction, to guide fuzz testing, etc.) and enhancing regression sensitivity of a test suite.
SoC design, HLS and Catapult
Emerging applications such as 5G, automotive and IoT have introduced more embedded sensors, specialized processors and communication blocks such as visual processing, AI neural networks and high-speed communication units. In order to speed-up and lower the inception cost of such products, more system designers are migrating their code abstraction from RTL to high level synthesis (HLS) as shown in figure 1. The overall development time can be cut by half with higher level synthesis. While traditional software coverage tools can be run on the C++ source code, the generated results are inaccurate and may mislead designers for a good coverage as discussed in more details in the next paragraph.
Mentor’s Catapult® HLS Platform provides a complete C++/SystemC verification solution that interfaces with Questa® for RTL verification as shown in figure 2. The platform consists of a design checker (Catapult Design Checker or CDesign Checker), a coverage tool (Catapult Code Coverage or CCOV), a high-level synthesis (Catapult HLS) and a formal tool (Sequential Logic Equivalence Check).
To gain a better clarity of how these platform sub-components handshake, we should track the code as it is being processed. Initially, the code (containing Assert and Cover statements) is applied as input to CDesign Checker for linting and formal analysis to uncover any coding or language related bugs. A subsequent CCOV run is done on the checked code to provide hardware-aware coverage analysis. Once the code is cleanly analyzed, HLS can be performed to produce power-optimized and verification ready RTL. HLS propagates assertions and cover points to the output RTL and generates the infrastructure using SCVerify for RTL simulation using Questa –allowing the reuse of the original C++ testbench to verify the RTL. As a final step, SLEC-HLS formally verifies that the C++ exactly matches the generated RTL code.
Catapult vs traditional Code Coverage
Code coverage analysis in CCOV had been enhanced to be more hardware-context aware. The intent is to also enable designers to achieve the same coverage level for both high-level source code and post HLS RTL. The four main coverage techniques used to analyze the C++ code are statement, branch, focused expression, and toggle coverage. At first glance they look similar to those of the generic coverage tool version, but in actuality are not the same, as captured in the (left) table of figure 3. The right table shows differences between CCOV and traditional code coverage such as GCOV (Gnu Coverage).
Furthermore, mainstream software coverage tools are not hardware-context-aware in nature as highlighted below:
Using Catapult Code Coverage
A complete HLS to RTL coverage flow starts with stimulus preparation for HLS model in either C++ or SystemC. It is followed by running CCOV to assess if targeted coverage is met, otherwise more tests get added. Optionally, designer can exclude areas of the design from coverage analysis. CCOV captured all the coverage metrics into the UCDB and HLS is done to produce power-optimized RTL.
The generated coverage results captured in Questa Unified Coverage DataBase (UCDB), can later be used within the context of the proven Questa verification management tools as shown in figure 5. This CCOV integrated with the UCDB provides an assurance for a complete and accurate RTL coverage analysis.
If the Questa simulator is used with code coverage turned on, all coverage metrics are added into the UCDB. For those cases requiring further verification such as any unreachable code segment, designer can use Questa CoverCheck to help formally prove unreachability and apply the necessary directives to the simulator (or in UCDB) for its exclusion. Prior generated SCVerify settings and makefile can be used to simulate the RTL. The process gets iterated with more tests until RTL code coverage is reached.
In conclusion, migrating to HLS is a proven cost-savings and significantly shorten RTL development time. Mentor’s Catapult hardware-aware code coverage is a key metric in HLS flow and bridges coverage of higher abstraction codes (C++/SystemC) with RTL –enabling a fast convergence to verification sign-off.
For more details on Catapult HLS please check HERE.
EDA has been flirting with the cloud unsuccessfully for many years now and it really comes down to a familiar question: Who can afford to spend billions of dollars on data center security? Which is similar to the question that started the fabless transformation: Who can afford to spend billions of dollars on semiconductor manufacturing technology?
TSMC has partnered with cloud vendors Microsoft and Amazon to bring EDA into the 21st century. I have said it before, if anybody could do it TSMC could, which makes TSMC all that more sticky as a pure-play foundry. What other foundries have the ecosystem and trust of the semiconductor industry to do this?
The one issue that is still in process is the software business model. From what I am told EDA software licensing has not changed to a traditional pay-per-use cloud model yet. It really is uncharted territory so let’s look at how we got EDA licensing to where it is today.
We started with perpetual licenses that were locked to a specific machine (not good for EDA). Next was the WAN licensing that would let a perpetual license float around using a license server (good), followed by the flexible access model (FAM) which was a three year all-you-can-eat approach offered by a specific vendor (horribly not good). The software subscription licensing that we use today came next where you lease a software license for three years (very good). One company added a remix clause that allowed customers to change the license counts from one product to another (not good). The EDA company that I previously worked for added weekly tokens that can be used for peak simulation/verification times (very good). The token model worked quite well and added much more total revenue than previously thought and gave chip designers more time simulating and verifying. I feel that the pay-per-use cloud pricing would have a similar result, additional revenue above and beyond annual EDA budgets and better chips, absolutely.
The other thing that I want to point out is how important your relationship with the foundry is. I have made a career of it, helping emerging EDA and IP companies work with the foundries creating revenue streams inside the foundry and outside with the top foundry customers. It is interesting to note that Cadence and Synopsys are the two EDA partners TSMC chose to start with. I’m sure the others will follow but take note, Synopsys, the number one EDA and IP company, does not offer their own cloud, they are all-in with TSMC.
One of the keynotes at the TSMC OIP conference last week was Kushagra Vaid, GM and distinguished Engineer at Microsoft Azure (cloud). Before joining Microsoft in 2007 he spent 11+ years designing microprocessors at Intel. It is always nice to talk semiconductor design with someone who actually designed semiconductors. I spoke with Kushagra and Suk Lee after lunch and am convinced that, after numerous failed attempts, EDA is finally in the cloud and will stay there, my opinion.
“Microsoft Azure is pleased to be a TSMC premier partner in the OIP Cloud Alliance, and we’re honored to receive a 2018 partner of the year award from TSMC for our joint development of theVDE cloud solution,” said Kushagra Vaid, GM and Distinguished Engineer, Azure Hardware Infrastructure, Microsoft Corp. “Our collaboration with TSMC will help usher in modern silicon development that leverages the capabilities of the Azure cloud platform.”
“Synopsys has been a TSMC OIP Alliance member for EDA flows and IP for 11 years, and we have expanded our partnership with TSMC to enable IC design in the cloud,” said Deirdre Hanford, co-general manager, Synopsys Design Group. “We have collaborated with Amazon Web Services and Microsoft Azure to provide a secure and streamlined flow for TSMC VDE. The Synopsys Cloud Solution has passed the rigorous TSMC security and performance audits and is ready for our mutual customers to design in the cloud with TSMC collateral using Synopsys tools and IP.”
Synopsys Announces Availability of TSMC-certified IC Design Environment in the Cloud
TSMC Recognizes Synopsys with Four Partner Awards at the Open Innovation Platform Forum
Synopsys Design Platform Enabled for TSMC’s Multi-die 3D-IC Advanced Packaging Technologies
Synopsys and TSMC Collaborate to Develop Portfolio of DesignWare IP for TSMC N7+ FinFET Process
Synopsys Digital and Custom Design Platforms Certified on TSMC 5-nm EUV-based Process Technology
Synopsys Delivers Automotive-Grade IP in TSMC 7-nm Process for ADAS Designs
Recent talk of AMD vs Intel market share share is misguided, the real race for superiority is TSMC vs Intel underlying that, tech dominance between US & China.
There has been much discussion of late about market share between Intel and AMD and how much market share AMD will gain at Intel’s expense due to Intel’s very late 10NM technology node. On the surface this may be the minor symptoms of a deeper conflict between Intel and TSMC and ultimately between the US and China for technology dominance.
The real root cause of AMD’s resurgence also may not be only Intel’s stumble but Global Foundries stumble as well. GloFo’s stumble in ability to deliver to AMD allowed AMD to go outside of its relationship and hook up with TSMC which “leap frogged” it into a truly competitive position.
At some point in time , its not a question of if but rather when, TSMC will be subsumed by China (along with Taiwan..). This makes the AMD versus Intel story really all about technology dominance in the future between the US and China.
Right now TSMC (China) appears to be in the lead even though Intel (USA) appears to be finally recovering from its large 10NM stumble. TSMC long ago won the foundry wars as it makes Apple chips, communications and video chips. On the logic side, the only thing left for TSMC to win is CPU/PC/server chips which AMD will serve as the vehicle for.
Although it can be argued that Samsung is still the number one chip maker by dollar volume, that is obviously due to its dominance of memory as it doesn’t compare to TSMC in the more technologically important foundry market.
Although memory is also obviously extremely important in today’s data obsessed world, we think China can more easily copy both NAND and DRAM than logic in the future. There are a number of memory fabs in China already starting on that quest.
With GloFo (owned by Abu Dhabi) out of the race, Intel is the only real participant in the semiconductor race for the US. Intel in recent years has been focused on everything and anything not core semiconductor. Software, AI, AR, VR & drones… and of course Mobileye. One could argue that BK took his eye off the ball, distracted by the lure of new shiny toys. We would hope that Intel’s new Ceo return focus to its core technology heritage and doubles down on that focus.
Maybe Jerry Sanders (founder of AMD) quote “real men have fabs” is even more important today as the real “fab king”, TSMC, owns the foundry industry and is the barbarian at the gates to the CPU industry.
TSMC will make more money from AMD than AMD will
We have pointed out in previous articles that TSMC is the dominant partner in the relationship with AMD. AMD needs TSMC more than TSMC needs AMD. Now that the good ship GloFo has been burned to the ground by its 7NM abandonment, AMD has no escape from TSMC island (Samsung is not a viable rescue). TSMC can control AMD’s profit margins by controlling their chip supply costs. They can also control AMD’s market share by dropping costs to AMD to increase share versus Intel or raising costs to tighten the competition. TSMC is at the controls…
AMD is now largely a captive puppet of TSMC
What is the correct market valuation of a captive puppet? We had suggested in previous notes that AMD was getting overly expensive. The market appears to finally, belatedly, be figuring this out. AMD’s stock seems to have discounted huge share gains and profitability both of which were still in the further future.
We think analysts would be mistaken to assume that AMD’s supply costs from TSMC will fall sharply or even remain constant as TSMC ramps up supply. AMD’s model is not that of a fab owner with high fixed costs and marginal incremental costs. TSMC controls AMD’s financial model going forward.
The relationship between AMD and GloFo was much more even handed as both sides needed one another more equally than the one sided TSMC/AMD relationship.
Design versus Fabrication
Although modern chip design is ever more critically complex and important than before, the fabrication of chips into silicon (Moore’s Law) has become exponentially more complex and has hit many more costly and technically complex barriers. Just compare the revenues of EDA companies versus chip tool companies . Look at the cost of building a fab or mask sets.
While AMD has great CPU designs and great video and AI capabilities, those designs have no value without the ability to fab them. TSMC brings that to the table and at a level equal to and better than Intel can.
At the end of the day, its the fab’s capability that wins the race….. a great design is worthless without a fab that can make it a reality…..
10NM finally out of the woods?
We were the first to break the news of Intel’s 10NM delay years ago. At the time we never would have imagined that the delay would be this long. This was far from normal as previously Intel’s “Tick Tock” strategy was as precise as a Swiss watch. Something happened, not clear what, but we think it was beyond just a technical barrier.
High on the rumor mill of causes of the delay are discussions of cobalts insertion into the manufacturing process. This sounds somewhat similar to the industries switch from aluminum to copper only a few orders of magnitude harder.
It is interesting to note that TSMC has not done cobalt yet so perhaps it has not suffered the same pain but may in the future. It is also interesting to note that GloFo was trying cobalt as well.
In any event it seems that Intel has “broken the code” and is now yielding better or at least enough to ramp production starting next year.
As most investors know, Intel’s 10NM and TSMC’s 7NM are rough equivalents in geometry and performance. Intel ramping in Q1 2019 would put them about 9 months behind TSMC’s leading edge which has already ramped.
It sounds like TSMC is already pushing hard at 5NM so Intel is going to have to go even harder to make up for lost time. So far TSMC has not gotten tripped up but it has yet to do cobalt and/or EUV. Perhaps if TSMC hits some hurdles Intel may have a chance to catch up but I would not count on it.
The US versus China in the fight for technology dominance
China has already proven to be a formidable competitor in software, Internet and AI etc;. It has a $100B checkbook to advance its semiconductor industry. So far they have made good (perhaps not great) progress. TSMC alone is a big enough prize in the technology race to justify getting even more aggressive on Taiwan. TSMC coupled with some memory fabs in the mainland would be a lethal combination way bigger than Samsung.
Maybe the US government will wake up and support the US semiconductor industry more. Maybe encourage Intel and Micron to merge. Maybe seek a buyer for GloFo Malta that will pick up the baton. Maybe put export restrictions on key US tool technology to delay China’s ascent.
So far, there is no such support from the government for the industry that holds the key to future technology dominance. There have been some very small import tariffs on Chinese goods related to semiconductors but nothing more.
Even though China is obviously no longer a communist country, we think a Lenin quote is appropriate; “The capitalists will sell us the rope with which to hang them,” In other words, we will continue to supply China with the technology that they will eventually dominate us with.
The Stocks
As we have previously suggested, we think AMD is overvalued as investors have stampeded into the stock on a good story without digging much deeper. While we think there is a lot of upside in AMD we think much of it is already in the stock and not a lot of room for any negative news.
As for Intel, ramping 10Nm is obviously good news but it won’t really impact things until at least Q1 2019 at best and realistically speaking Q2. In the mean time Intel still is still short of 14NM capacity that has caused it to perform unnatural acts to serve unexpected demand. It has also ticked up capex to try to help out but this also won’t fix the 14NM shortage for at least a couple of quarters as equipment has to roll in. This suggests that AMD will get some opportunistic share gains near term.
Semi Equipment Stocks – News remains negative…RTEC preannounces
As for the equipment companies, the news flow continues to be negative. RTEC pre-announced a roughly 10% shortfall in revenue that will cut EPS by a third or so.
The weakness for Rudolph appears broad based, not just Samsung and not just memory, and sounds like a fair number of tools have either slipped into next year or been canceled.
This also fits with our view of another 10% down leg for the quarter following on KLACs reset of Q4 expectations. The chip equipment flu which started with Samsung has spread to Micron, GloFo, TSMC and others. Intel seems to be the only chip company increasing capex near term but obviously not enough to make up for all the other cuts.
It has been a while in the chip equipment industry since we last had a negative pre-anouncement. Things have been that good for too long. RTEC’s pre-announcement underscores that we are in a standard cyclical downturn. At this point 2018 H2 is all downhill and the real question is when will we hit bottom (trough)? Q1 2019, Q2 2019 or further out?nIn looking at previous down cycles and current demand it feels a lot like a 3 or 4 quarter downturn.
We would not be surprised to see further negative news either in pre-announcements or quarterly reports as the weakness will show up in revenues and EPS.
We may have another leg down in the stocks. We are also seeing analysts downgrading the stocks, as we did earlier this week, as we get closer to a bottom. This obviously fits the “locking the barn door after the horse has bolted” as the stocks are way down from their peaks, but many bought into the one quarter air pocket fantasy.
Buckle your seat belts for a bumpy earnings season…..
Gerry Hsu’s departure from Cadence to form Avanti (originally named ArcSys) is chronicled in legal testimony as accusations of theft of software were followed by legal battles, financial awards and even prison terms. Mentor and Synopsys were simply onlookers as the drama unfolded but both had an interest in the outcome. The outcome of the trial pointed to substantial civil damages that Avanti would have to pay to Cadence. Mentor went to work with some of the top legal advisors at O’Melvany and Myers to estimate just how much those damages would be. Synopsys was reluctant to engage but was worried that, if Mentor acquired Avanti, the EDA balance of power could shift.
Gerry Hsu had taken up residence in Taipei, having avoided criminal charges for which some of his employees were not so lucky. Chi-Foon Chan, then EVP of Synopsys, suspected that Mentor was negotiating with Gerry Hsu to buy Avanti and Chi-Foon has since told me that he called every major hotel in Taipei to see if I was registered as a guest. In reality, we were much more serious about buying Avanti than Chi-Foon imagined. I rented an apartment in Taipei and spent more than a month living there and regularly meeting with Gerry. Meanwhile, Greg Hinckley, who was then Mentor CFO but effectively becoming COO, conducted meetings with the investment bankers to determine how we could put together a successful proposal to buy Avanti.
The bankers paid a lot of attention to two issues: 1) Negotiating how much they would be paid for the transaction and 2) Removing the absurd benefit in Gerry Hsu’s contract as Avanti CEO that would pay him $10 million if he left Avanti for any reason. Why would a Board of Directors approve such a condition? The Board of Avanti at that time consisted of five people, four of whom were employees who reported to Gerry, and the fifth was a forestry major whose knowledge of semiconductors and EDA was very limited. Securing approval for this condition couldn’t have been very difficult for Gerry even though it seemed to stand in the face of most responsible corporate governance. Greg, who is one of the best “out-of-the-box” thinkers I’ve ever known, addressed the bankers with a different question. “Why don’t we triple the amount”, suggested Greg, “and offer to pay Gerry $30 million instead of $10 million”? The bankers were aghast. Why would we do that? Greg’s response: “There’s obviously only one decision maker for the sale of the company so why don’t we appeal to his self- interest?” The bankers were skeptical but we put together a proposal that incorporated this feature. As justification, we asked that Gerry extend his non-compete agreement from one year to three years in trade for tripling the severance payment.
I arranged to have dinner with Gerry in Taipei. He brought his son along and I presented the proposal. When I highlighted the change in severance arrangement for Gerry, he quickly became suspicious and began arguing with me that he was entitled to the $10 million severance payment. I had to repeat twice that I didn’t dispute his right to the payment; I just wanted to extend his non-compete agreement to three years and triple the severance payment. Once Gerry understood, he became enthusiastic about the proposal and asked how quickly we could close an agreement. I cautioned Gerry that the terms of the agreement must be confidential and I had Gerry approve the letter of intent and confidentiality agreement. We shook hands on the deal and I called the Mentor team to join us in Taipei to finalize the agreement.
I can’t be sure how Gerry communicated with Synopsys but, by the time the Mentor negotiating team arrived, Gerry was already expressing second thoughts about his agreement to be purchased by Mentor. It became apparent that he was talking to another potential buyer despite his commitment to Mentor. So we returned to the U.S. with no deal. Subsequently, Gerry’s team contacted our bankers to re-start negotiations but we held firm, responding that we didn’t feel we could trust him based upon our previous experience. We didn’t engage again. Negotiations between Synopsys and Avanti continued and a deal was announced on December 3, 2001. A long period of review by the International Trade Commission ensued. After more than six months, the transaction was approved. Details were then published in a joint S4A filing by Synopsys and Avanti – https://www.sec.gov/Archives/edgar/data/883241/000095012302004502/0000950123-02-004502-index.htm Among the most interesting details for me were:
[LIST=1]
Let’s start with hiring through Q3 and what to expect for Q4…
Hiring for Q3 (and the year as a whole) has been strong and robust. The EDA/Semi hiring needs are indeed stronger this year than in a long time, yet more exacting than ever. We have had an exceptionally strong year even though it has been exponentially so much more difficult to find the right candidates. Even with so much demand for good people, companies continue to be extremely picky about their preferred candidate requirements. I have said it before and it bears repeating…if a company finds a smart, talented, capable engineer, who is desirable of learning whatever is needed, and has several of the primary prerequisites, it is smarter to hire (the proverbial) bird in the hand and help get them up to speed now, than hope a better option comes along. While a better candidate might follow, they also MIGHT NOT! When passing on a candidate that could fit, in lieu of that perfect fit, companies must think about the valuable time lost in searching and interviewing for the more perfect candidate, (with no guarantee of how long that might take), when they could have had someone else already up and running, learning what is necessary. The time it takes to search, find, and interview, and (hopefully) hire can be considerable, especially in today’s environment. I have seem companies pass on a relatively decent candidate, in hopes of finding someone that is a closer fit, only to be looking months, or even a year, later…it is not uncommon.
As we move into Q4, it is looking to be yet another robust quarter and hiring will remain strong. Here is what I know… All the economic numbers for EDA/Semi are strong, targets are being met and exceeded, and growth is occurring across a wide array of sectors. As I said earlier and it bears repeating… It continues to get harder and harder to find the right candidates for the overly-exact specifications that exist today. People are not leaving quite as fast as in years past and that makes it harder to “recruit” them out; harder, but not impossible. Comps seem to be going up, which is good news and a direct result of a strong market, and which should hopefully entice more people to consider alternative opportunities.
Because hiring is so difficult, companies need to ask if they can afford to wait for the exactly right candidate. I realize that for the most part, hiring managers want someone that can come in and make an immediate contribution with the least amount of training and resources. Certainly that makes sense on paper. The reality is, that is rarely the case. Even with the best of hires, ramp-up time can be considerable and more of a drain on internal resources than contemplated. All tech companies work in varying general domains of one category or another, but each domain has a specialty, shall we say a new subset, frontier that they are tackling. That newness inherently requires a learning curve. Strong internal training and support for the new hire is mandatory for them to learn the specific specialized domain. Sometimes, the new hire requires more bring-up-to-speed time than anticipated. Realistically, reality actually shows that to be the norm…more training time was needed than anticipated, and that happens more times than not. That fact brings to light this question: Is it worth the risk to pass on the decent, fits-most-of-the-specs candidate or wait and hope that a better one comes along? This is a big question, and one every company should consider when they have pressing, critical hiring needs. Certainly I am not saying hire someone that MIGHT be able to do the job, but I am saying that if they have most of what you need, you should be weighing your options carefully.
Candidates too need to learn how to impress the hiring managers during the interview process with their willingness to learn. They need to be compelling and convincing enough so that hiring managers are confident about your commitment to excel. It is essential to convince the team that you have what it takes and will do what is necessary to get up to speed quickly and succeed. Even on your own time, after hours!
ARM TechCon is right around the corner and has a good mix of technology and a decent attendance. I will be there in my famous white jacket, walking the aisles, seeing clients all day. I already have several off-site interviews scheduled with both new and existing clients. It seems like both ARM TechCon and my quick visit in and out will be quite busy…I hope to see you there and you should always feel free to call me with any questions you may have. Perhaps we can meet during the conference.
I recently learned that Accellera has formed an IP security working group. My first reaction was “Great, we really need that!”. My second reaction was “But I have so many questions.” Security in the systems world is still very much a topic in its infancy. I don’t mean to imply that there isn’t good work being done in both software and hardware domains. But it still mostly feels reactionary and ad-hoc. Where’s the ISO 26262 for security? How do we quantify strong security versus weak security? And so on. Here, in no particular order, are some questions that I hope the working group will eventually answer.
How does IP security tie to SoC security and then to system security? In part this feels like the system element out of context (SEooC) topic in ISO 26262. How can you demonstrate security in a sub-component when you don’t know how it will be used in the larger system? Moreover, we still don’t have a good handle on defining security for the whole stack. Even if we have a well-defined definition for the IP, how do we compose those measures into a system-level measure?
Which raises a scope question. I see the chair is from Intel, which is a great start. They probably know more than most about security than most, despite their recent stumbles. And Synopsys is involved which is also good, not just for their IP expertise but also for their software security expertise. I hope Rambus will join, also maybe someone from Google ProjectZero (you see where I’m going with this). I hope Accellera will become a regular presenter at BlackHat. Meantime, it would be good to know how the WG plans to connect with existing compliance requirements from PCI, NSA and others.
But even given a WG group loaded with experts from the industry, how much will they share, and will that be enough to build an effective standard? Security through obscurity is still important and will likely always be important. What you don’t share is harder to attack because that makes it harder to guess at vulnerabilities. So how much can be shared in a standard? Mechanisms almost certainly not because that would limit innovation and differentiation, which hackers would love and the industry would hate. Measures of security seem more likely as long as they’re fairly general. Targeted metrics might be clues to likely weak areas. Or maybe these could be a good way to demonstrate strengths against a spectrum of possible attacks? (I said I had questions, not answers.)
Back to the element out of context point, how effective can security measures at this level be? Consider timing-channel attacks. I can run these from inside a VM nowhere near the IP, as long as I have access to an accurate timer. I just have to launch an operation that will use the IP. You could argue that attention to such attacks is out of scope for this work and should be the responsibility of a different standard. But that begs the question – how useful will this standard be if it does not consider such attacks? Answering that question requires a way to compare, at least approximately, the class of attacks that will be covered versus the class of all likely attacks (as anticipated within the lifetime of a device using the IP).
I could go on, but I do want to stress that, despite all my questions, I am very much a fan of this effort. Certainly the people contributing on the WG will know far more about security than I do and must see further and more clearly than I can. And frankly security is a huge problem, so every possible angle is worth exploring. I look forward to learning more as this develops. You can learn more about the Accellera WG HERE.
Go into any bar in New York City or San Francisco (or increasingly Mumbai and Sydney) popular with the younger crowd and you will find a curious transformation. The majority of the patrons spend at least as much time checking their phones as they do checking out potential mates or talking to people they are with. Why? They are on Tinder. The wildly popular dating app has changed the mating game, in ways that we believe are toxic. A growing body of research associates Tinder use with less romantic satisfaction, less happiness, and even diminished sense of self-worth – particularly among men.
Let’s be clear: online dating isn’t itself bad. This new way of finding mates has broken down plenty of barriers. We can now meet people from different parts of the country, from diverse social groups. Websites such as Match.com and eHarmony are good at bringing people who want to have relationships together.
But Tinder brings a fundamental change to online dating. In the past, online dating was an intentional act. People logged on to a dating website to look for partners. The website was separate from other online activity and wasn’t just focused on inducing addictive behavior.
Tinder used swiping and other clever user-interface tricks that foster the actions of rating, comparing, and selecting potential mates. This made dating an omnipresent activity —swipe left, swipe right—that Tinder users could play in bars, in elevators, on the subway. Tinder’s innovation made online dating more addictive and comparative in an unhealthy way – a form of never-ending shopping that focuses on the shallowest of qualities.
The effects of dating apps on happiness are complex. On the one hand, online dating exposes people to a far wider set of options and allows filtering by criteria of the user’s choosing. On the other hand, the paradox of choice affects many by making a decision difficult—and when they do make a decision, they tend to can be less happy with it—possibly because that style of online dating promotes a mentality that views people and relationships as commodities to shop for.
Tinder promotes a winner-take-all effect, wherein everyone seeks the most attractive people. This eliminates selection of mates by other variables that may be more predictive of compatibility, leading to frustration all around. Evaluating choices side by side tends to encourage daters to emphasize factors and characteristics that are unlikely to determine compatibility. Whether someone is fairer or is taller, is highly unlikely to reflect compatibility over time; far less so than more-innate traits such as empathy, intelligence, or humor.
Particularly useless in this regard are superficial physical traits that tend to be overemphasized due to reliance on photos as the primary basis upon which to choose a date. Psychologists have long known that humans are bad at predicting compatibility. Tinder makes that bad prediction far more common and replaces other modes of interaction that might lead us to better matches.
This rating culture and mindset may also lead to diminished appreciation of people before we even meet them. Scientists are coming to believe that physical attraction is not fixed. We change what we think about people’s attractiveness based on our interaction with them. Funny people or clever people or extremely empathetic people may become more attractive to us after we talk with them or spend time with them.
Kansas University researchers documented this effect, calling it “the Tinder trap.” In a lab setting, they showed subjects pictures of potential mates and asked them to rate their attractiveness. The researchers then introduced some of the subjects to the people they had rated face to face. The scientists found, curiously, that potential partners they had rated as less attractive or moderately attractive were far more likely to get increased ratings after a face-to-face meeting than were potential partners they had rated as attractive. So evaluating a potential partner solely on visual attractiveness is a poor predictor of what you will think of that person once you meet in real life.
Perhaps most importantly, rating people’s attractiveness prior to meeting them tends to diminish the rater’s evaluation of that person afterward, “probably because the rater is comparing their conversation partner to all the other potential partners they saw online. In other words, the apparently endless choice that online dating offers may cheapen and undermine our perceptions of people in real life.
More concerning is that some online-dating applications have been linked with low self-esteem. In a survey of Tinder users and nonusers, those who used the swiping app recorded lower levels of self-worth and, along with other negative impressions, said that they were less satisfied with their own face’s appearance. Curiously, this effect was stronger in male users.
In our new book, Your Happiness Was Hacked: Why Tech Is Winning the Battle to Control Your Brain—and How to Fight Back, Alex Salkever and I look at how technologies are actually diminishing our well-being. Tinder is one of the most troubling developments we have seen, but it is in a long line of efforts by tech companies to addict users using techniques perfected in Las Vegas casinos and fine-tuned by armies of scientists and user experience experts in Silicon Valley.
The fact is that the tech industry is working overtime to steal our happiness and we must wrestle it back.
For more, please visit my website, www.wadhwa.com and follow me on Twitter: @wadhwa
Last month I attended the 2018 U.S. Executive Forum where Wally Rhines was one of the keynotes. I was also lucky enough to have lunch with Wally afterwards and talk about his presentation in more detail and he sent me his slides which are attached to the end of this blog.
The nice thing about Wally’s presentations is that they are not company specific while a lot of keynotes are company pitches in disguise. The other thing is that his slides are very detailed and tell a story so reading them really is the next best thing to being there.
When I first started in Silicon Valley in the 1980s we all designed and manufactured our own CPUs which I consider domain specific architectures. Intel then came around with a more general architecture and the personal computing revolution began. Fabless semiconductor companies then restarted domain specific computing with GPUs and SoCs that are now replacing Intel chips at an alarming pace. System companies (Apple) then took the lead with custom SoCs and now even software companies (Google) are making their own domain specific chips (TPU). There are also IoT and automotive domain specific chips flooding the markets.
We have a front row seat to this transformation on SemiWiki because we see the domains that read our site. The first IoT blogs started in 2014 and we now have over 400 that have been read close to 2 million times. Automotive also started for us in 2014 and we now have more than 300 blogs that have been read more than 1 million times. AI started for us in 2016 and now we have close to 100 blogs that have been read more than 250 thousand times. IoT wins but AI has just begun.
Wally has some interesting slides on AI, Automotive, VC Funds, and the China semiconductor initiative. Definitely worth a look. Here is his summary slide for those who are short of time:
Here are the other keynotes. I have access to the slides and will blog about them when I have time but since Wally sent me his slides he goes first. I will end this blog with the perilous thoughts I had on this subject during my long and dark drive home.
Opening Keynote: Looking To The Future While Learning From The Past
Presentation by Daniel Niles / Founding Partner / AlphaOne Capital Partners
Keynote: Convergence of AI Driven Disruption: How multiple digital disruptions are changing the face of business decisions
Presentation by Anthony Scriffignano / Senior Vice President & Chief Data Scientist / Dun & Bradstreet
AI and the Domain Specific Architecture Revolution
Presentation by Wally Rhines / President and CEO / Mentor, a Siemens Business
AI Led Security
Presentation by Steven L. Grobman / Senior Vice President and CTO / McAfee
AI is the New Normal – 3 key trends for the path forward
Presentation by Kushagra Vaid / General Manager & Distinguished Engineer – Azure Infrastructure / Microsoft
Innovating for Artificial Intelligence in Semiconductors and Systems
Presentation by Derek Meyer / CEO / Wave Computing
The Evolution of AI in the Network Edge
Presentation by Remi El-Ouazzane/Vice President and COO, Artificial Intelligence Products Group / Intel
GSA Expert Panel Discussion
Moderated by Aart de Geus / Chairman and Co-CEO / Synopsys
Keynote: Long Term Implications of AI & ML
Presentation by Byron Reese / CEO, Gigaom / Technology Futurist / Author
The semiconductor industry (EDA included) has posted some very nice gains in the past two years but how long can that continue? Take a look at this graph and you will see a pattern that will no doubt repeat itself but the question is how low will we go?
One thing I can tell you is that EDA is definitely in a bubble. Look at the VC money and all of the fabless startups that are buying tools, especially the ones in China. At some point in time money will run out and only a fraction of these companies will continue to expand and buy more tools. Someone else can run the numbers but my bet is that the EDA bubble will pop in 2019, absolutely.
It turns out that consumers are not alone in their love-hate relationship with SIM cards. SIM cards save us from increasingly widespread cellphone cloning. However, if your experience is anything like mine, it seemed that with every new phone, a new SIM card format was needed. Furthermore, people travelling overseas who wanted to avoid roaming charges often find themselves trying to buy SIM cards in foreign countries (and languages) and then juggling these new cards with their original card to make calls, read texts and more recently pay for purchases.
Consumer gripes aside, there are bigger drawbacks with SIM cards as we know them. Manufacturers encounter higher costs due to the additional parts and the reliability issues associated with the slot and removable card. Also, the IoT has changed the needs for subscriber verification. It’s not just for phones anymore. Expect to see cars, watches, appliances, sensor hubs and almost all manner of connected devices needing unique and secure subscriber identification. Already, it should be clear that these things cannot have SIM cards slots that require manually adding or changing cards every time they are put into service or undergo a service provider change.
So what is a SIM card anyway? It is really a software application running on a secure processor and a set of security identifiers in the form of a subscriber ID number and an associated encryption key. There is more to it, but for the purposes of this discussion this will suffice. The physical hardware in the card is known as a Universal Integrated Circuit Card (UICC). It contains a CPU, memory and interface hardware. The software that runs on the UICC is called Universal Subscriber Identification Module (USIM) application.
In order to eliminate the need to insert, and subsequently replace, SIM cards, a method is needed to securely bootstrap a permanently built-in UICC and perform a secure Over the Air (OTA) transfer of the subscriber and security information. More than just handset side software and hardware is required to accomplish this. The GSMA has developed a standard for remote SIM provisioning. This has enabled the birth of the eSIM, which uses a UICC that is soldered to the mobile/remote device circuit board. Though, a separate component may still be an issue for some applications because it still takes up valuable board real estate and adds to the BOM.
The next logical step in this evolution is the incorporation of the UICC hardware and software into the system SOC. Synopsys has announced their iSIM, which is a UICC and USIM that can be integrated into any SOC design. Synopsys already has a large portfolio of secure and security related IP, so the addition of this innovative offering will dovetail nicely with their related IP. I recently spoke to Rich Collins, Senior Marketing Manager at Synopsys, about this.
He emphasized that the demands of IoT require moving from a standalone SIM card. IoT designs are already combining the application processor and modem, so including SIM functionality fits the requirements of these IoT systems. To ensure they are offering a complete solution he outlined for me their partnership with Truphone. Rather than leave it to their customers to find and integrate carrier side software to handle the network and OTA provisioning, Synopsys is offering a complete solution that includes the integration with Truphone’s worldwide network. Importantly, end users will have the freedom to choose any local carrier they wish, and Truphone will enable the handoff.
Synopsys is combining many of its mission critical IP components to facilitate iSIM functionality. Among these is their True Random Number Generator (TRNG) which is a vital element to avoid compromised security. Synopsys is integrating Truphone’s eSIM software stack (which includes Javacard OS) in a new tRoot HSM implementation for iSIM.
With the proliferation of IoT devices, the advent of 5G combined with the many benefits of completely integrated SIM hardware, it is clear that the next year or two will see big changes in SIM implementations. Synopsys is well positioned to help SOC and device designers navigate the process. End users and IoT deployment operators should be pleased with the end results. For more information on the complete Synopsys iSIM offering, visit the product page on their website.
