Santa Clara Convention Center, 5001 Great America Parkway, Santa Clara, CA 95054
Artificial Intelligence has seen resurgence in recent years fueled by the advance in computational power, algorithms and large amount of data, which are propelled by the semiconductor chip technology. AI technology in-turns is transforming the way businesses operate and how people engage with the world, which creates new demand for semiconductor industry. We have brought together best of AI and Semiconductor worlds for the coming CASPA Annual Conference to be held at Santa Clara Convention Center in 10/28. You would see keynote speeches from pioneering companies such asIntel/ARM/NVIDIA/Cadence/Lam Research and CEOs from new ventures in this field such as Cognitive Venture, AutoX, Pintuitive and StreamMosaic. Don’t miss this major event in the Silicon Valley. Come and discover the technology frontier and market driving forces that are changing our industry future.
- Registration and Networking:
- CASPA Board of Director Election:
- Welcome from CASPA President:
- Keynote Speech:
Accelerating Machine Learning and Deep Learning at Scale
Ziya Ma, VP, Intel
Distributed Machine Learning for Large-scale IoT Systems
Rob Atiken, Fellow, ARM
Machine Learning in Advanced Automotive Quality
David Greenlaw, VP, nVidia
Intelligent Systems for Electronic Design Automation
David White, DE, Cadence
Pixels, Deep Learning and Startups: the revolution in ubiquitous imaging
Chris Rowen, CEO, Cognitive Venture:
- Panel Discussion: Semiconductor & AI Fusion
Moderator: Mario Morales, VP, IDC
Democratizing Autonomous Driving with Affordable Cameras and AI
Jianxiong Xiao, CEO, AutoXa
The XMT processor for AI
Xingzhi Wen, CEO, Pintuitive
Transforming the Semiconductor Industry with AI and Machine Learning
Jeff David, CEO, StreamMosaic
Equipment Intelligence is more than AI
Alan Berezin, MD, Lam Research:
Ziya Ma, VP, Intel: “Accelerating Machine Learning and Deep Learning at Scale”
Abstract: In her presentation, Ziya will talk about Intel’s AI strategy, from the hardware architecture layer all the way up to deep learning frameworks. Intel sees AI transforming the way businesses operate and how people engage with the world. Intel is assembling the broadest set of technology options to drive AI capabilities in everything from smart factories and drones to sports, fraud detection and autonomous cars.
Deep learning is a fast growing subset of AI and machine learning. There is an emerging trend to conduct deep learning in the same cluster along with existing data processing pipelines to support feature engineering and traditional machine learning. Being one of early and top contributors to Apache Spark, Intel has developed and open sourced a distributed deep learning framework called BigDL that is built organically on big data (Apache Spark) platform. It combines the benefits of high performance computing and big data architecture for rich deep learning support. With BigDL on Spark, customers can eliminate large volume of unnecessary dataset transfer between separate systems, eliminate separate HW clusters and move towards a CPU cluster, reduce system complexity and the latency for end-to-end learning.
BIO and Photo
Ziya Ma is vice president in the Software and Services Group and director of big data technologies at Intel Corporation. She is responsible for optimizing big data solutions on the Intel® architecture platform, leading open source efforts in the Apache community, and bringing about optimal big data analytics experiences for Intel customers. Her team works closely with internal product teams, the open source community, the industry and academia to further Intel’s efforts in the big data field.
Before assuming her current position in 2014, Ma was the product development software director at Intel IT. In that role, she led the team that provided software lifecycle management tools and infrastructure and analytics solutions to Intel software teams worldwide. Ma spent the first 10 years of her Intel career in the Technology and Manufacturing Group, holding various management positions related to the development of embedded software for factory equipment, manufacturing execution systems, process-control systems, user interfaces and business intelligence solutions. Before joining Intel in 2000, Ma was a software engineer in the semiconductor product division at Motorola Inc. She is also a co-founder of the Women in Big Data forum.
Rob Aitken, Fellow, ARM: “Distributed Machine Learning for Large-scale IoT Systems”
Abstract: The Internet of Things vision promises systems where huge numbers of sensors gather data and machine learning algorithms in the cloud process and make sense of it. While such solutions sound desirable and simple in theory, their practical implementation is complicated. In particular, there are multiple communication bottlenecks between the sensors and the cloud, as well as large amounts of unexploited compute capability along the way. This talk looks at some of the issues involved and explores promising avenues for future innovation.
Bio & Photo
Rob Aitken is an ARM Fellow responsible for technology direction at ARM Research. He works on low power design, library architecture for advanced process nodes, technology roadmapping, and next generation memories. He has worked on 15+ Moore’s law nodes and has published over 80 technical papers, on a wide range of topics. Dr. Aitken joined ARM as part of its acquisition of Artisan Components in 2004. Prior to Artisan, he worked at Agilent and HP. He holds a Ph.D. from McGill University in Canada. Dr. Aitken is an IEEE Fellow, and serves on a number of conference and workshop committees.
Guna Ponnuvel, Director, NVIDIA: “Machine Learning in Advanced Automotive Quality”
Abstract: Autonomous vehicles, with their successful early programs and tremendous potential, make headline news every day and promise to dramatically change the economics of many industries. As the automobile industry is transitioning to self-driving, automotive quality requirements become even more critical. This talk gives an overview of the automotive supply chain complexity, tools and processes used to manage quality of all the components of a complex autonomous driving system and application of machine learning in test processes to achieve desired quality. The traditional OEM-supplier model will not be enough to meet the quality requirements of autonomous drive technology and need true partnerships with total transparency of unit level feedback when components fail.
Bio & Photo:
Guna Ponnuvel is Director of Product Engineering at NVIDIA, responsible for the bring-up and qualification of chip and board products. Guna has worked on leading edge technology for 15 years, innovating many silicon process optimization, test productivity & quality improvement techniques to enable low transformation cost and high quality commercial and automotive products.Prior to joining NVIDIA, Guna was responsible for the bring -up and qualification of Conexant’s Central Office and Customer Premises Equipment chipset products. He holds a bachelor’s degree in EE from Bharathiar university, India and a master’s degree in EE from Illinois Institute of Technology, Chicago.
David White, Distinguished Engineer, Cadence: “Intelligent Systems for Electronic Design Automation”
Bio & Photo:
David White (Sc.D. ’01) received a Doctor of Science Degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. Dr. White is currently a Senior Group Director for R&D with the Virtuoso Product Group at Cadence Design Systems. He joined Cadence in 2006 through the acquisition of Praesagus, a software company he co-founded in 2001 and where he served as CTO. Previously he co-founded the machine learning based software company, Neurodyne and served as a Visiting Scientist at the MIT Artificial Intelligence Lab.
Dr. White was appointed to the Advisory Board for the National Science Foundation (NSF) in Washington D.C. and the MIG Advisory Board at MIT. He was an editor and co-author of the Handbook of Intelligent Control, a text written in 1992 by leaders in the machine learning community and the NSF. He also co-organized and chaired one of the first industry led conferences on neural networks in 1990. He has given invited talks at the White House Office of Science and Technology Policy (OSTP) and NSF forums on neural networks and AI, as well as at IEEE, NASA, ACM and IJCNN conferences.
Chris Rowen, CEO, Cognitive Venture: "Pixels, Deep Learning and Startups: the revolution in ubiquitous imaging”
Abstract: The dramatic proliferation of cameras doesn’t just change the quantity of image streams and applications, but also drives fundamental qualitative shifts on the role of imaging in technology, business and society. This talk explores the most important changes as camera systems are designed and deployed just for computer vision, as the urban-area density of cameras sky-rockets, and as deep learning methods change the nature of insights we can extract, and as vision-inspired statistical computing supplants traditional computing models . Deep learning, in particular, is driving a new wave of innovation and of startups built to extra much more insight from existing surveillance, monitoring, human-machine- interface, robotic and automotive streams. The distribution of these innovators across geographies and application segments tells us a lot about how vision will change most. As a byproduct of studying the targets for new ventures in vision, we can even derive useful lessons about the entrepreneurial success formula in the vision space.
Bio and Photo:
Chris Rowen is a well-known Silicon Valley entrepreneur and technologist. He created Cognite Ventures in 2016 to invest in, advise, and analyze the cognitive computing and deep learning startup arena. He has served as CTO for Cadence’s IP Group, where he and his team develop new processor and memory for advanced applications in mobile, automotive, infrastructure, deep learning and IoT systems. Chris joined Cadence after its acquisition of Tensilica, the company he founded to develop extensible processors. He founded and led Tensilica as CEO and CTO, to become one of the leading embedded architectures, with more than 225 chip and system company licensees, who together have shipped more than 12 billion processor cores. Before founding Tensilica in 1997, he was VP and GM of the Design Reuse Group at Synopsys. Chris also was a pioneer in developing RISC architecture and helped found MIPS Computer Systems, where he was VP of Microprocessor Development. He holds an MSEE and PhD in electrical engineering from Stanford and a BA in physics from Harvard. He holds about 50 US and international patents. He was named an IEEE Fellow in 2015 for his work in development of microprocessor technology.
Panel Discussion (Moderator: Mario Morales, VP of IDC):
Mario Morales is the program vice president of IDC's enabling technologies and semiconductor research. He is responsible for in-depth analysis, evaluation of emerging markets, forecasting, and research of major semiconductor application areas such as embedded and intelligent systems, wireless, personal computing, wired communications, and consumer.
Mr. Morales is an industry analyst with over 25 years of extensive experience in managing a multinational research team of analysts, management consultants, and business development managers, Author of over 220 reports and studies in the area of semiconductors, mobile, PC, wireless, embedded, and ICT marketplace. Mr. Morales is a trusted advisor to leading high tech company executives, financial investors, and bankers on market landscape and direction, product and technology positioning, competitive benchmarking, M&A, HW and SW technology, and brand health and sustainability. His career includes past positions with NEC Electronics and Dataquest.
Jianxiong Xiao, CEO, AutoX: “Democratizing Autonomous Driving with Affordable Cameras and AI”
Abstract: AutoX is striving to democratize autonomy and make autonomous driving universally accessible to everyone. With over 10 years of experience in computer vision and robotics, Professor X is working to reduce the price of entry into the autonomous driving field for several orders of magnitudes with an innovative camera-first solution -- using cameras as primary sensors. By doing so, he posits, the safety and convenience benefits of autonomy will be delivered to more people, faster. He will share how he found a company with the mission of democratizing autonomy, gather an expert team, and commercialize his passion.
Bio - Dr. Jianxiong Xiao is the founder and CEO of AutoX, a silicon valley tech startup focusing on creating full-stack A.I. software solution for self-driving vehicles. Former professor and founding director at Princeton’s Computer Vision & Robotics Lab, Xiao has over ten years of research and engineering experience in Computer Vision, Autonomous Driving, and Robotics. In particular, he is a pioneer in the fields of 3D Deep Learning, RGB-D Recognition and Mapping, Big Data, Large-scale Crowdsourcing, and Deep Learning for Robotics.
Xingzhi Wen, CEO, Pintuitive: “The XMT processor for AI”
BIO: Xingzhi Wen, Ph.D. is the co-founder of Pintuitive, a startup company focusing on parallel computing based on XMT technology. Dr. Wen worked as Sr. Digital Design Manager at Marvell and Sr. Digital Design Engineer at NVIDA and Apple. During Ph.D study, Dr. Wen prototyped the first 64-core XMT processor in FPGA. Dr. Wen holds Ph.D from University of Maryland, College Park and MS and BS from Tsinghua University, Beijing.
Jeff David, CEO, StreamMosaic: “Transforming the Semiconductor Industry with AI and Machine Learning”
Bio: Jeff David is the Founder and CEO of StreamMosaic and author/co-author of 82 granted US patents. StreamMosaic develops production-implementable AI products that improve yield and reduce costs in semiconductor manufacturing by leveraging data throughout the manufacturing and testing process. For over 20 years, Jeff has been inventing and implementing process control systems for the world’s largest semiconductor manufacturers. Prior to founding StreamMosaic in 2014, Jeff was at Applied Materials for 18 years. Jeff received his M.B.A. from Indiana University Kelley School of Business, his M.S. in Interdisciplinary Engineering from Purdue University, and his B.S. in Electrical Engineering from Purdue University.
Sub-16nm device nodes and new device architectures have created unprecedented manufacturing challenges, and have put pressure on the industry to find completely new ways to keep costs down while maintaining high yield and device performance. In order to achieve acceptable yield and performance levels with these new architectures and processes, very tight process specifications must be achieved. A large part of the problem is that individual steps involved in fabrication and testing require complex integration and can no longer be performed independently of each other. Thus, better process control, testing and integration schemes are needed now more than ever. Fortunately, the emergence of new machine learning and artificial intelligence (AI) technologies have presented novel and transformative ways to leverage the growing amount of test and process data collected. By leveraging and integrating data collected pre and post-wafer sort and by employing robust and scalable machine learning algorithms tailored specifically for semiconductor manufacturing, many of these new challenges faced by the industry can be addressed in a cost-efficient manner.
Alan Berezin, MD, Lam Research: “Equipment Intelligence is much more than AI”
Alan received his BA in physics from UC Berkeley and spent several years doing software development before pursuing his Ph.D. in physics from University of Texas Austin. He then spent 6 years at Advanced Micro Devices on yield enhancement before leaving to cofound a software analytics startup, Drillinginfo. As CTO, he and the team grew the business to 500 person worldwide firm. Following the sale of that business, he stayed on in a corporate strategy role until leaving to pursue investing and consulting. Alan join the Advanced Equipment and Process Control group as a managing director in 2016 where he is focused on equipment intelligence, concept & feasibility of computational products, and software enabled products.
- Registration & Networking:
- Opening with Traditional Band & Dinner Banquet:
- Retiring BOD Service Recognitions:
- CASPA 2017-2018 Leadership Transition:
- Executive Keynote Speech
Ajit Manocha, President and CEO, SEMI:
- 2017 Student Scholarship Award:
- Performance & Prizes Drawing:
Dinner Banquet Executive Keynote Speaker
Founders, Builders, and New Leaders Propel the Global Electronics Manufacturing Industry
President and CEO, SEMI
2017 is a record-breaking year.
Semiconductor sales will top $400B, semiconductor equipment sales are on track
to shatter prior highs set in the year 2000. The past progression of
monolithic demand drivers has been replaced by a diversity of applications
including: AR, VR, AI, cloud storage, IoT, Smart Automotive (driver assistance
and autonomous), Smart Manufacturing, and Smart MedTech. These growing demand
drivers and the increasing silicon (semiconductor) content in electronics is
fueling what many are calling a “super cycle.”
How did we get here – and where are we headed? The electronics manufacturing industry has grown and prospered, and SEMI has speed the time to better business results for the industry, because of founders, builders, and today’s new industry leaders. These groundbreakers, trailblazers, and transformers continue to play roles in our industry’s future. Similarly, geographic regions have invested to develop semiconductor and electronics manufacturing and have emerged, grown, specialized, and matured in a cycle that has moved around the globe. China is the latest to take the high-growth spotlight, with a projected annual fab spending surpassing $11B in 2018 and potentially exceeding $18B in 2020.
While looking ahead to see where the industry is heading, it is important to highlight the roles of founders, builders, and new leaders. To continue to connect, collaborate, and innovate at the exponential rate, our global industry needs to identify the inflections and common issues to address collectively. There is more work to do together to simplify and streamline the electronics manufacturing supply chain to ensure continued growth and prosperity through this “super cycle” and beyond. There has never been a more exciting time to be working in our industry.
Ajit Manocha is the president and CEO of SEMI. Headquartered in Milpitas, California, SEMI is the global industry association serving the electronics manufacturing supply chain. Manocha, an industry leader has over 35 years of global experience in the semiconductor industry.
Manocha was the former CEO at GLOBALFOUNDRIES, during which he also served as vice chairman and chairman of the Semiconductor Industry Association (SIA). Earlier, Manocha served as EVP of worldwide operations at Spansion. Prior to Spansion, Manocha was EVP and chief manufacturing officer at Philips/NXP Semiconductors. He began his career at AT&T Bell Laboratories as research scientist where he was granted several patents related to microelectronics manufacturing.
Additionally, Manocha has served on the President’s committees for “Advanced Manufacturing Partnerships” and the President’s Council of Advisors on Science & Technology (PCAST) during the last 4+ years.