Join this moderated roundtable discussion group of 10-20 attendees focusing on selecting ML training platforms for specific use cases.
There will be several moderators per topic area to allow for multiple tables and questions will be prepared in advance. Each group will be multidisciplinary with representation from across the tech stack. Attendees who have registered for the event will be able to sign up for the roundtable discussion groups closer to the event, or via an AI Hardware & Edge AI Summit sales representative.
The subtopics to be discussed will include:
- GPUs vs ASICS vs commodity hardware (i.e. software-accelerated CPUs)
- Considerations for efficient training of training large language models
- Fitting workloads to training hardware - overcoming issues with memory etc.
- Software considerations for novel AI hardware training platforms
In his forthcoming keynote, Lip Bu Tan delves into the transformative impact of Generative AI on today's rapidly evolving intelligent systems. This critical conversation sheds light on the symbiotic relationship between AI semiconductors and systemic hardware growth drivers, showcasing how they are steering the future of purpose-built intelligent systems.
As we navigate this unprecedented era of technological advancement, Mr. Tan will explore how Generative AI platforms are accelerating design productivity and enabling innovative AI chip design tools, and define what’s needed to deliver a full generative AI system stack. The keynote will also touch upon the extension of these advancements, highlighting how computational software initially developed for AI can be adapted and applied to other domains, thereby broadening the impact and utility of intelligent systems.
Don't miss this enlightening session that promises to redefine our understanding of AI's role in shaping intelligent systems and expanding the frontiers of what's possible across multiple sectors.
Lip-Bu Tan
Lip-Bu Tan is Founder and Chairman of Walden International (“WI”), and Founding Managing Partner of Celesta Capital and Walden Catalyst Ventures, with over $5 billion under management. He formerly served as Chief Executive Officer and Executive Chairman of Cadence Design Systems, Inc. He currently serves on the Board of Schneider Electric SE (SU: FP), Intel Corporation (NASDAQ: INTC), and Credo Semiconductor (NASDAQ: CRDO).
Lip-Bu focuses on semiconductor/components, cloud/edge infrastructure, data management and security, and AI/machine learning.
Lip-Bu received his B.S. from Nanyang University in Singapore, his M.S. in Nuclear Engineering from the Massachusetts Institute of Technology, and his MBA from the University of San Francisco. He also received his honorary degree for Doctor of Humane Letters from the University of San Francisco. Lip-Bu currently serves on Carnegie Mellon University (CMU)’s Board of Trustees and the School of Engineering Dean’s Council, Massachusetts Institute of Technology (MIT)’s School of Engineering Dean’s Advisory Council, University of California Berkeley (UCB)’s College of Engineering Advisory Board and their Computing, Data Science, and Society Advisory Board, and University of California San Francisco (UCSF)’s Executive Council. He’s also a member of the Global Advisory Board of METI Japan, The Business Council, and Committee 100. He also served on the board of the Board of Global Semiconductor Alliance (GSA) from 2009 to 2021, and as a Trustee of Nanyang Technological University (NTU) in Singapore from 2006 to 2011. Lip-Bu has been named one of the Top 10 Venture Capitalists in China by Zero2ipo and was listed as one of the Top 50 Venture Capitalists on the Forbes Midas List. He’s the recipient of imec’s 2023 Lifetime of Innovation Award, the Semiconductor Industry Association (SIA) 2022 Robert N. Noyce Award, and GSA’s 2016 Dr. Morris Chang's Exemplary Leadership Award. In 2017, he was ranked #1 of the most well-connected executives in the technology industry by the analytics firm Relationship Science.
Ginny Siller
Abstract coming soon...
Sally Ward-Foxton
Sally Ward-Foxton has been writing about the electronics industry for more than a decade. As a freelance journalist she has published articles in EE Times, Electronic Design Europe, Microwaves & RF, ECN, Electronic Specifier: Design, IoT Embedded Systems, Electropages, Components in Electronics and many more. She also supplies technical writing and ghostwriting services to several of Europe's leading PR agencies. She holds a Masters' degree in Electrical and Electronic Engineering from the University of Cambridge, UK.
Jim Keller
Jim Keller is the CEO of Tenstorrent and a veteran hardware engineer. Prior to joining Tenstorrent, he served two years as Senior Vice President of Intel's Silicon Engineering Group. He has held roles as Tesla's Vice President of Autopilot and Low Voltage Hardware, Corporate Vice President and Chief Cores Architect at AMD, and Vice President of Engineering and Chief Architect at P.A. Semi, which was acquired by Apple Inc. Jim has led multiple successful silicon designs over the decades, from the DEC Alpha processors, to AMD K7/K8/K12, HyperTransport and the AMD Zen family, the Apple A4/A5 processors, and Tesla's self-driving car chip.
Raja Koduri
Bing Yu
Bing Yu is a Sr. Technical Director at Andes Technology. He has over 30 years of experience in technical leadership and management, specializing in machine learning hardware, high performance CPUs and system architecture. In his current role, he is responsible for processor roadmap, architecture, and product design. Bing received his BS degree in Electrical Engineering from San Jose State University and completed the Stanford Executive Program (SEP) at the Stanford Graduate School of Business.
Laurent Moll
Dr. Laurent Moll most recently served as Vice President of Engineering at Qualcomm where he led a 500-person team creating infrastructure IP for Qualcomm’s chips, including NoC interconnects, memory subsystems, cache coherency subsystems and more. Laurent has led a storied career for over two decades, performing key technical roles at industry leaders such as Digital Equipment Corporation, Compaq Computer Corporation, SiByte, Broadcom, Montalvo Systems and NVIDIA. Prior to his nearly 8-year tenure at Qualcomm, he was the Chief Technology Officer at Arteris Inc, a predecessor company of Arteris. Throughout his career, he has played an influential role in inventing the system-on-chip architectures, IP subsystems, and methodologies that are today the foundation of modern semiconductor design. Laurent earned his PhD in Computer Science at École Polytechnique and holds over 60 patents on various aspects of SoC technology.
AI and security workloads are clearly driving next-generation SoC architecture innovations. These architectures need higher performance, and more memory per processing element as technology process nodes advance. However, memories are scaling at smaller rates than the processing elements but the workloads are demanding more memory per processing element leading to a memory wall -- there must be technology disruptions. Off-chip memory offers performance gains, but AI workloads require more efficient and higher density memories per processing element. One clear solution has been multi-die systems, leveraging more on-chip memories at higher bandwidths and improved densities. This presentation will explore these memory and IO innovations and will showcase several real-world case studies on the development of multi-die systems to meet the AI performance and memory challenges.
Ron Lowman
Ron Lowman joined Synopsys in 2014 and is currently the AI Strategic Marketing Manager for the Solutions Group. Ron is responsible for driving Synopsys’ Artificial Intelligence market IP initiatives, including strategic business and market trend analysis.
Prior to joining Synopsys, Lowman spent 16 years at Motorola/Freescale in Controls Engineering, Automotive Product & Test Engineering, Product Management, Business Development, Operations, and Strategy Roles.
Ron holds a Bachelor of Science in Electrical Engineering from Colorado School of Mines and an MBA from the University of Texas in Austin.
Synopsys
Website: https://www.synopsys.com/
Smart, Secure Everything—From Silicon to Software
Synopsys technology is at the heart of innovations that are changing the way we live and work. The Internet of Things. Autonomous cars. Wearables. Smart medical devices. Secure financial services. Machine learning and computer vision. These breakthroughs are ushering in the era of Smart, Secure Everything―where devices are getting smarter, everything’s connected, and everything must be secure.
Powering this new era of technology are advanced silicon chips, which are made even smarter by the remarkable software that drives them. Synopsys is at the forefront of Smart, Secure Everything with the world’s most advanced tools for silicon chip design, verification, IP integration, and application security testing. Our technology helps customers innovate from Silicon to Software, so they can deliver Smart, Secure Everything.
Heather Fowler
Trends in cloud and HPC systems design are converging in the field of ML. As demands for ML compute performance continue to grow, certain trends are dictating systems design choices. Increasing server and rack density is a tried-and-tested tool for driving performance, but results in extreme heat, while packing GPUs and ASICs into AI servers is an inefficient long-term solution when memory bandwidth limits the total amount of FLOPS available at any moment. Some fairly fundamental re-designs are needed in the ML systems space, and this panel will examine what the next generation of systems will look like, what benefits they will bring, and how to get there.
Drew Matter
Drew Matter leads Mikros Technologies, a designer and manufacturer of best-in-class direct liquid cold plates for AI/HPC, semiconductor testing, laser & optics, and power electronics. Mikros provides leading microchannel thermal solutions in single-phase, 2-phase, DLC and immersion systems to leading companies around the world.
Greg Stover
With more than 30 years of experience in data center efficiency optimization with large data center enterprise operators and industry leading VARs/Resellers, Greg champions the successful leveraging and utilization of Vertiv’s amazing and constantly evolving portfolio of thermal, power, monitoring & management solutions for the hyperscale, colocation, on-prem, DR and edge IoT ecosystems.
As a data center efficiency optimization enthusiast, Greg has a proven track record of bringing leading and bleeding edge cooling, power, monitoring and DCIM solutions and tools through introduction, implementation and successful execution, while staying keenly focused and aligned with client/enterprise/edge operator’s goals & objectives. Greg is a frequent presenter at industry conferences, trade shows and Integrator/VAR/Partner training events.
Dudy Cohen
Dudy is a qualified manager and technology expert, with more than 30 years of experience in the networking industry. As a senior AI networking expert, he partners closely with the product and engineering teams to shape DriveNets’ vision for AI Networking, helping to deliver the high performance of a proprietary solution with a standards-based Ethernet implementation that provides unrivaled performance. Previously, Dudy served as the VP of Product Marketing at Ceragon. He also served as a Director of Solutions Engineering at Alvarion Ltd. Dudy holds an M.Sc.-E.E degree from the Tel Aviv University.
Albert Chen
Akhil Vaid
Akhil Vaid, MD, is a distinguished Instructor at the Division of Data Driven and Digital Medicine (D3M), Department of Medicine at the Icahn School of Medicine at Mount Sinai. Renowned for his expertise as a physician-scientist, Dr. Vaid's work navigates the intriguing intersection of medicine and technology, with a resolute commitment to foster democratized healthcare through the power of machine learning.
After obtaining his medical degree from one of India's eminent medical colleges, Dr. Vaid served patients across diverse socio-economic landscapes. This unique exposure catalyzed his conviction that true healthcare equity could only be achieved through machine learning and artificial intelligence. Consequently, he ventured into the intricate domains of multi-modal machine learning, specializing in deep learning with ECGs, federated learning, Natural Language Processing, and deriving valuable insights from the Electronic Healthcare Record.
Before his current role at the Icahn School of Medicine at Mount Sinai, Dr. Vaid honed his clinical skills and amassed a wealth of experience in the Indian healthcare system. His medical journey is punctuated by his relentless quest for innovation, illustrated by his extensive contributions to the rapidly evolving field of digital medicine.
Dr. Vaid is the author of 54 scientific publications, esteemed contributions to esteemed medical journals, including Nature Medicine, the Annals of Internal Medicine, and NPJ Digital Medicine. His work is reflective of his profound understanding of medicine and technology and their potential in transforming patient care. His projects, backed by significant grants, encompass multiple facets of informatics, data science, and machine learning in medicine.
Girish Nadkarni
Girish N. Nadkarni, MD, MPH, is the Irene and Dr. Arthur M. Fishberg Professor of Medicine at the Icahn School of Medicine at Mount Sinai. As an expert physician-scientist, Dr. Nadkarni bridges the gap between comprehensive clinical care and innovative research. He is the System Chief of the Division of Data Driven and Digital Medicine (D3M), the Co-Director of the Mount Sinai Clinical Intelligence Center (MSCIC) and the Director of Charles Bronfman Institute for Personalized Medicine.
Before completing his medical degree at one of the top-ranked medical colleges in India, Dr. Nadkarni received training in mathematics. He then received a master’s degree in public health at the Johns Hopkins Bloomberg School of Public Health, and then was a research associate at the Johns Hopkins Medical Institute. Dr. Nadkarni completed his residency in internal medicine and his clinical fellowship in nephrology at the Icahn School of Medicine at Mount Sinai. He then completed a research fellowship in personalized medicine and informatics.
Dr. Nadkarni has authored more than 240 peer-reviewed scientific publications, including articles in the New England Journal of Medicine, the Journal of the American Medical Association, the Annals of Internal Medicine and Nature Medicine. Dr. Nadkarni is the principal or co-investigator for several grants funded by the National Institutes of Health focusing on informatics, data science, and precision medicine. He is also one of the multiple principal investigators of the NIH RECOVER consortium focusing on the long-term sequelae of COVID-19. He has several patents and is also the scientific co-founder of investor-backed companies—one of which, Renalytix, is listed on NASDAQ. In recognition of his work as an active clinician and investigator, he has received several awards and honors, including the Dr. Harold and Golden Lamport Research Award, the Deal of the Year award from Mount Sinai Innovation Partners, the Carl Nacht Memorial Lecture, and the Rising Star Award from ANIO.
Abstract coming soon...
Matthew Burns
Matthew Burns develops go-to-market strategies for Samtec’s Silicon-to-Silicon solutions. Over the course of 20+ years, he has been a leader in design, applications engineering, technical sales and marketing in the telecommunications, medical and electronic components industries. Mr. Burns holds a B.S. in Electrical Engineering from Penn State University.
Samtec
Website: http://www.samtec.com/AI
Founded in 1976, Samtec is a privately held, $822 MM global manufacturer of a broad line of electronic interconnect solutions, including High-Speed Board-to-Board, High-Speed Cables, Mid-Board and Panel Optics, Precision RF, Flexible Stacking, and Micro/Rugged components and cables. With 40+ location severing approximately 125 countries, Samtec’s global presence enables its unmatched customer service.