Sunday, September 10, 2017

Quick chat with Vishal Dhupar : Keynote speaker DVCon India 2017

Vishal Dhupar
Imagine learning how to ride a bicycle! You learn to balance - pedal - ride on a straight line - turn - ride in busy streets - All set!!! It takes step by step learning & then if you are offered a different bicycle you would try to apply the “truths” you discovered in your earlier learning process & quickly pick up the new one too. Our machines so far perform the tasks they are programmed for and as obedient followers carry out the required job. However, the new wave of technology is striving to make the machines more intelligent, to not only seek but offer assistance, to make our decision making better, help an ageing population store & retrieve memories that fade and much more!!! Sounds interesting? Conniving? …???

Vishal Dhupar, Managing Director – Asia South at Nvidia would be discussing Re-Emergence Of Artificial Intelligence Based On Deep Learning Algorithm as part of the invited keynote on Day 1 DVCon India 2017. Passionate about the subject, Vishal shares the background & what lies ahead for us in the domain of AI & Deep Learning. Extremely useful from beginners to practitioners!!!

Vishal your keynote focusses on AI & Deep learning – intricate & interesting topic. Tell us more about it?

Curiously, the lack of a precise, universally accepted definition of AI probably has helped the field to grow, blossom, and advance at an ever-accelerating pace. Claims about the promise and peril of artificial intelligence are abundant, and growing.

Several factors have fueled the AI revolution which will be the premise of my talk. Touching upon how machine learning is maturing, and further being propelled dramatically forward by deep learning, a form of adaptive artificial neural networks. This leap in the performance of information processing algorithms has been accompanied by significant progress in hardware and software systems technology. Characterizing AI depends on the credit one is willing to give synthesized software and hardware for functioning appropriately and with foresight. I will be touching upon a few examples of AI advancements.

How do we differentiate between machine learning, artificial intelligence & deep learning?

Machine learning, deep learning, and artificial intelligence all have relatively specific meanings, but are often broadly used to refer to any sort of modern, big-data related processing approach. You can think of deep learning, machine learning and artificial intelligence as a set of concentric circles nested within each other, beginning with the smallest and working out. Deep learning is a subset of machine learning, which is a subset of AI. When applied to a problem, each of these would take a slightly different approach and hence a delta in the outcome.

Artificial Intelligence is the broad umbrella term for attempting to make computers think the way humans think, be able to simulate the kinds of things that humans do and ultimately to solve problems in a better and faster way than we do. Then, machine learning refers to any type of computer program that can “learn” by itself without having to be explicitly programmed by a human. Deep learning is one of many approaches to machine learning. Other approaches include decision tree learning, inductive logic programming, clustering, reinforcement learning, and Bayesian networks. Deep learning was inspired by the structure and function of the brain, namely the interconnecting of many neurons.

Some of the discussions on deep learning are intriguing. Does it lead to machines taking over jobs?

Machines are getting smarter because we’re getting better at building them. And we’re getting better at it, in part, because we are smarter about the ways in which our own brains function.

Despite the massive potential of AI systems, they are still far from solving many kinds of tasks that people are good at, like tasks involving hand-eye coordination or manual dexterity; most skilled trades, crafts and artisan- ship remain well beyond the capabilities of AI systems. The same is true for tasks that are not well-defined, and that require creativity, innovation, inventiveness, compassion or empathy. However, repetitive tasks involving mental labor stand to be automated, much as repetitive tasks involving manual labor have been for generations.

Let me give you an example your calculator is smarter than you are in arithmetic already; your GPS is smarter than you are in spatial navigation; Google, Bing, are smarter than you are in long-term memory. And we're going to take, again, these kinds of different types of thinking and we'll put them into, like, a car. The reason why we want to put them in a car so the car drives, is because it's not driving like a human. It's not thinking like us. That's the whole feature of it. It's not being distracted, it's not worrying about whether it left the stove on, or whether it should have majored in finance. It's just driving.

What are the domains that you see would see faster adoption & benefits of these techniques?

In healthcare, deep learning is expected to extend its roots into medical imaging, translational bioinformatics, public health policy development using inputs from EHRs and beyond. There is rapid improvements in computational power, fast data storage and parallelization have contributed to the rapid uptake of deep learning in addition to its predictive power and ability to generate automatically optimized high-level features and semantic interpretation from the input data.

Seems like the ASIC design flow/process can be equally benefited from these techniques. Your views on it?

Deep Learning in its elements is an optimization problem. Its application in any work flow or design process where there is scope for optimization carries enormous benefits. With respect to the design, fab and bring up of ICs, deep learning helps with inspection of defects, determination of voltage and current parameters, and so. In fact, at NVIDIA we carry out rigorous scientific research in these areas. I believe as we unlock more methods of unsupervised learning, we’ll discover and explore many more possibilities of efficient design where we don’t entirely depend of large volumes of labelled data which hard to get in such a complex practice.

What are the error rates in execution we can expect with deep learning? Can we rely on machines for life critical applications?

Deep learning will certainly out-perform us in few specific tasks with very low error rates. For example, classification of images is task where models can be far accurate than mortals. Consider the case of language translation, today machines are capable of such efficient and economic multi-lingual translation that it wouldn’t just be possible for a person. [Recently MSFT’s speech recognition systems achieved a word error rate of 5.1%on par with humans] While we look into health care where life critical decisions are made, deep learning can be used to improve accuracy, speed and scale in solving problems like screening, tumor segmentation, etc. and not necessarily declaring a person alive or otherwise!

In all the instance we just saw, state-of-art capabilities are developed in very specific and highly verticalized applications. Machine are smarter than us in these applications but nowhere close to our general intelligence in piecing these inputs together to make logical conclusions. From a pure systems and software standpoint, we will need guard rails, i.e. fail-safe heuristics that backup a model when it operates outside the boundaries to keep the fault tolerance at bay.  

This is the 4th edition of DVCon in India. What are your expectations from the conference?

While the 20th century is marked by the rise and dominance of the United States, the next 100 years are being dubbed the Asian Century by many prognosticators. No country is driving this tectonic shift more than India with its tech talent. NVIDIA is a world leader in artificial intelligence technologies and is doing significant work to train the next generation of deep learning practitioners. Earlier this year we announced our plans to train 100,000 developers in FY18 in deep-learning skills. We are working across academia and the startup community to conduct trainings in deep learning. I’m keen to understand the enthusiasm of the attendees in these areas and how NVIDIA can provide a bigger platform and bring the AI researchers and scientists community together. 

Thank you Vishal!

Join us on Day 1 (Sep 14) of DVCon India 2017 at Leela Palace, Bangalore to attend this keynote and other exciting topics!

Disclaimer: "The postings on this blog are my own and not necessarily reflect the view of Aricent"

Sunday, August 27, 2017

Quick chat with Ravi Subramanian : Keynote speaker DVCon India 2017

Dr. Ravi Subramanian
For many decades, the semiconductor industry followed Moore’s law, transforming what we called as a discrete chip carrying a function on silicon into a small IP inside the SoC on silicon today. As we continue to debate beyond Moore, more than Moore or stagnation of this law and step in the world of IoT, we realize that the system is no more only a single SoC, but instead, it is a conglomeration of multiple tiny & large systems working in tandem producing interesting use cases & enhancing user experience. But are we as the verification engineering workforce ready with the required skills along with the right arsenal of tools and efficient workhorses to ride through this new challenge?

Dr. Ravi Subramanian, Vice president and General manager of Mentor’s IC Verification Solutions Division shares a holistic view on this subject in his opening keynote on Day 2 at DVCon India 2017. The talk titled Innovations in Computing, Networking, and Communications: Driving the Next Big Wave in Verification, dives into convergence of different technologies and its impact on verification. A quick chat with Ravi, revealed the excitement that we all can look forward to in his talk as well as the future that lies ahead for all of us. Read on!!!

Ravi your keynote focusses on drivers to the next big wave in verification. Tell us more about it?

Yes, my talk will focus on the amazing innovations our industry is developing with respect to computing, networking, and communications. These include the changing nature of computing, the dramatic changes in networking and storage, and the disruptive effect of new broadband communications. Yet, the next big wave in design is actually the convergence of these technologies, which is driving today’s internet-of-things and autonomous systems revolution. A common theme across these emerging systems is the need for low power, security, and safety—whether you are talking about devices on the edge or high-availability systems in the cloud. These new challenges have opened innovation opportunities for us to rethink the way we approach verification

IoT is driving the convergence of different technologies. How would it affect the way we verify the systems today?

To answer your question, I first want to step back in time to provide a framework for today’s challenges. In the 1990’s the concept of separation of concerns was introduced into engineering. Essentially, the idea is that verification would become more productive if we focused on verifying orthogonal concerns or requirements of the design separately versus trying to verify multiple concerns combined. For example, during this period of time, we learned that it is more efficient to verify functional concerns and physical concerns in separate simulation runs. This approach to verification worked well up to about 10 years ago. The emergence of mobile devices introduced new low-power requirements that made it difficult to separate concerns. For example, today we see that physical concerns (such as low power management) now can directly affect functional behavior of a device. Hence, these concerns need to be verified together. Bringing together physical, electrical, and functional has become mandatory.

The key point is that convergence of computing, networking, and communication, which is driving IoT, has introduced new layers of verification requirements that did not exist years ago, and the interaction of these requirements has had a profound effect on the way we must verify systems today.

What are the solutions that the EDA industry is driving to enable this next big wave in verification?

One contributing factor to growing verification complexity is the emergence of new layers of verification requirements, as I previously mentioned. For example, beyond the traditional functional domain, we have added clock domains, power domains, mixed-signal domains, security domains, safety requirements, software, and then obviously, overall performance requirements. Hence, we see the next big wave in verification on multiple fronts:

Continuing introductions of focused solutions optimized for specific verification concerns. Examples of these focused solutions include: formal apps focused on  verifying security features within a design or power apps used to provide complete RTL power exploration and accurate gate-level power analysis within emulation.
Emerging system-level analysis solutions, which provide new metrics and insight into the fully integrated SoC. This becomes essential for system-level performance analysis. The IoT SoC, for example, is a different beast than today’s state-of-the art networking SoC.
Greater convergence across multiple verification engines (e.g., simulation, emulation, and FPGA prototyping), which will improve productivity. The new Accellera Portable Stimulus standard will help facilitate this convergence and foster the introduction of new verification solutions.
Q4: Do you see domain specific solutions like automotive or machine learning etc. getting enabled for verification?

Yes, in fact there are multiple opportunities to leverage big data analytics to solve many system-level analysis problems. Machine learning is only one approach used today for big data analytics; however, there are others. Now, concerning domain-specific solutions in the automotive space, formal technology is being leveraged to improve productivity related to safety fault analysis.

Do you expect all workhorses (Simulation, Emulation & Formal) playing a critical role in verifying these new converged system level designs?

Obviously, this depends on the design. A project developing sensors for an IoT edge solution has different verification requirements than a project developing an automotive SoC containing multiple CPU and GPU cores, a coherent fabric, and multiple complex interfaces. Nonetheless, with increased design integration, multiple verification engines are required today that address the growing volume of verification requirements.

This is the 4th edition of DVCon in India. What are your expectations from the conference?

DVCon, in general, is recognized as the premier conference on the application of languages, tools, methodologies and standards for the design and verification of electronic systems and integrated circuits. And DVCon India is no exception, which has continued to grow in both attendance and exhibitor participation. I expect DVCon 2017 will continue to deliver high-quality technical content and provide valuable networking opportunities for its attendees. It is the premier venue to share state-of-the-art developments and connect the creative minds working on these developments.

Thank you Ravi!

Join us on Day 2 (Sep 15) of DVCon India 2017 at Leela Palace, Bangalore to attend this keynote and other exciting topics.

Disclaimer: “The postings on this blog are my own and not necessarily reflect the views of Aricent”

Sunday, August 20, 2017

Quick chat with Apurva Kalia : Keynote speaker DVCon India 2017

Apurva Kalia
The advancements in semiconductor industry starting picking up with the rise in performance of processors driving the computer industry. Next, the mobile segment opened floodgates when the PC market stagnated & then low power with smaller dimensions on top of performance drove the innovation in silicon implementation. The industry today is at cross roads once again awaiting the next big thing. Automotive is one of the key areas to get the ball rolling yet again. But then, each domain has its characteristics that needs to be aligned to!

Apurva Kalia, Vice President of R&D focusing on Automotive solutions at Cadence picks on an interesting topic for his DV track keynote on Day 1 at DVCon India 2017. With the auto industry shifting gears into autonomous cars, the question worth asking is – Would you send your child to school in an autonomous car? Yes, that’s the theme of Apurva’s keynote and here’s a sneak peek on this topic.

Apurva your keynote focusses on ‘autonomous cars’ – the talk of the town these days. Tell us more about it?

Well, there is major inflection point coming up in automotive electronics. We all know that Moore’s Law driven advances in cost per transistor and capacity have been holding up for many years. Complex chips are now possible within a cost factor that was not possible earlier. Moreover advances in algorithms, especially Machine Learning, now enables much more complex processing, especially vision based processing, to be done in real time. Both these trends coming together with advances in sensor technology has enabled systems to be created which can detect their environment quite accurately and in real time. This is the basis of autonomous driving. Also, as we know, every few years the semiconductor industry is looking for the next big trend which will drive the fab capacity. The above factors are pushing autonomous driving to be the talk of the town.

Security & Safety are emerging areas resulting from this topic. How does this change the way we verify our designs?

As I described above, with autonomous driving really taking off, these systems are becoming mission critical for the automobile. This means that the system needs to be safe and secure. It is inconceivable for a car to stop working at 80 kmph on a highway! Also, with the car needed to be connected to other cars and even to infrastructure and internet, this opens the system to attacks and makes it vulnerable. Therefore, these systems needs to make safe and secure to ensure safety and security of the automobile.

What are the solutions that the EDA industry is driving to enable ISO 26262 requirements from process & product perspective?

ISO26262 is the main standard that defines the safety requirements for automobiles. It is a very comprehensive standard which places requirements on all automotive systems. In fact edition 2 of the standard – coming out in Jan 2018 – will focus specially on semiconductors. Given the excitement around automotive electronics and autonomous systems, EDA industry needs to retool rapidly to address this need. Ensuring safety in these designs requires additional design and verification flows, methodologies and tool changes. The EDA industry needs to step up to define and create these flows, methodologies and tools required.

What are your views on the couple of accidents that happened in the US with autonomous cars? What could have been done better?

We are at early stages of this technology. Unfortunately as with any new technology, technology will take time to stabilize. In the meantime, during this stabilization time, unfortunate things like these accidents could happen. Organizations and individuals who are early adopters of these technologies take these risks, but they also contribute in a big way for advancement of these technologies. However, with the proper use of tools, implementation of standards, and focus on new solutions, we can avoid these kind of accidents.

How do you observe the adoption of autonomous cars across the globe & in India?

Autonomous cars are here to stay. They are solving real problems in real environments. We already have examples of autonomous cars on real roads – driving very safely. In fact, there are statistics which show that autonomous cars will actually cut down on accidents and fatalities – the most of which are caused by human error. Last year, I saw an engineering college in Delhi demonstrate an autonomous vehicle in Govindpuri – one of the most congested areas of Delhi. So this technology is real and works. I think it is just a matter of a few years when we will see this mainstream.

Do you see all workhorses (Simulation, Emulation & Formal) playing a critical role in realizing Auto grade designs?

Yes – all current EDA technologies – not just verification technologies, but even implementation technologies – need to be upgraded to support safety and security design and verification. All engines will need enhancements and special features to support these new requirements and flows.

This is the 4th edition of DVCon in India. What are your expectations from the conference?

I have seen DVCon India grow from humble beginnings to an excellent conference today. I think this conference provides a very good platform to share and discuss new trends in design and verification. I look forward to stimulating conversations on new flows and technologies. This conference attracts many design companies and all EDA vendors in India – what better assemblage of the right people for these discussions.

Thank you Apurva!

Join us on Day 1 (Sep 14) of DVCon India 2017 at Leela Palace, Bangalore to attend this keynote and other exciting topics.

Disclaimer: “The postings on this blog are my own and not necessarily reflect the views of Aricent”

Monday, March 27, 2017

Ni Hao China? says DVCon

Miniaturization of devices is marching into the range where the acceleration may not be contained in one dimension anymore. This is leading to growth in 2D & 3D for packing more functions on a given silicon area. One of the key factors that has enabled this race so far is also the globalization of workforce. Whether the reasons were tapping the talent world-wide or ensuring the work continues round the clock or reduce cost of development. With the tech world turning into a global village, there was a need felt to ensure different age groups, different cultures & different working styles, talk a common language. This has been the prime motive of Accellera working groups getting together from across the world to define standards and methodologies and providing a common ground for everyone to contribute. While rolling out standards is a key outcome of this consortium, encouraging the adoption & ensuring correct application of these standards is equally important. This is one of the prime reasons that the flagship conference DVCon was extended beyond geographies (DVCon goes GLOBAL!) a few years back when India & Europe embraced it with an overwhelming response. This year the 29th edition of DVCon US witnessed 1000+ participants  over a 4-day conference continuing the momentum year after year. However, this caravan would see another stopover before it reaches India in September this year. YES!!! DVCon would be debuting in the Mandarin land this year - DVCon China 2017!!!

If you have any doubts on why China? Let’s review a few interesting pointers from the latest report by PWC titled China’s impact on the semiconductor industry : 2016update

  • China’s semiconductor consumption growth continued to far exceed worldwide semiconductor market growth for the 5th consecutive year in 2015 reaching a new record of 58.5% of the global market. China’s semiconductor industry has grown at an equal or greater rate than its semiconductor market consumption for eight of the past ten years. In 2015, China’s semiconductor industry grew by 15.5% to a record US$89.3bn.
  • China’s IC industry grew by 17.1% in 2015 despite a decline in the global IC market. Since 2010 China’s IC industry revenues have more than doubled, growing 170%. Starting from a very small US$2.2bn base in 2000, China’s IC industry has grown much faster than the worldwide IC market for every subsequent year except 2010 with revenue touching 2015 to US$57.5bn.
  • Integrated circuit (IC) design continues to be the fastest growing segment of China’s semiconductor industry. During the ten years from 2005 through 2015 China’s IC design (fabless) industry has grown at a 30.1% compound annual growth rate (CAGR) from US$1.52bn to just over US$21bn in 2015.
  • The China Center of Information Industry Development (CCID) reports that the number of China’s IC design enterprises increased from 681 in 2014 to 715 by the end of 2015 with the total number of employees in China’s IC design totaling to about 155,000.
These pointers clearly confirm that the semiconductor industry is growing in China at an unparalleled speed and hosting a conference to bring in the stakeholders together would further stimulate the development process. Clearly a thoughtful decision by Accellera!

Coming back to the details of the event, the 1st edition of the Design and Verification Conference and ExhibitionChina is planned for 19, April 2017 at the Parkyard Hotel, Shanghai. DVCon China provides an excellent platform to bring together the global semiconductor industry in general & the China semiconductor industry in particular, along with academia and international standards development organizations. The 1 fullday event is completely packed with an assortment of keynotes from eminent speakers, tutorials from the gurus, papers & posters from practitioners and avenues for networking, learning opportunities, and exciting exhibits with different offerings. Along with experts from China there is an active participation from universities like Tsinghua and Fudan as part of the DVCon China steering and program committees. The day starts with keynote from Dr. Wally Rhines - CEO Mentor Graphics on the topic Design Verification:Challenging Yesterday, Today and Tomorrow while the event concludes with another interesting talk on What's Next in Verification from Yong Fu – Group Director, Synopsys. 

Leaders from the local industry with extended support from experts across the globe have put together a fantastic program for you to actively participate in person and be part of this enriching experience.

Reiterating the words of Benjamin Franklin that truly exhibit the spirits of DVCon–

Tell me and I forget.
Teach me and I remember.
Involve me and I learn.

 Get involved NOW!!! Registrations open with early bird discounts - here


Disclaimer: "The postings on this are my own and not necessarily reflect the views of Aricent".