Cloud computing today offers a wealth of capacity, elasticity, and computing choice. As architects, we often focus on the speeds and feeds that keep this computing humming along, but in today's climate, security is top of mind. In this talk, we'll explore the journey which has led to at-scale, at-speed confidential computing — capabilities which now enable protection of sensitive data sets, with privacy and authority over computation and data, even when leveraging the advantages of a multi-tenant cloud environment. From custody of digital assets to protection of healthcare records and financial payments, we'll look at how the work of architects is having real-world impact each and every day.
Hillery Hunter is CTO of IBM Cloud, responsible for technical strategy for IBM's cloud-native and infrastructure offerings. Prior to this role, she served as Director of Accelerated Cognitive Infrastructure in IBM Research, leading a team doing cross-stack (hardware through software) optimization of AI workloads, producing productivity breakthroughs of 40x and greater which were transferred into IBM product offerings. Her technical interests have always been interdisciplinary, spanning from silicon technology through system software, and she has served in technical and leadership roles in memory technology, Systems for AI, and other areas. She is a member of the IBM Academy of Technology and was appointed as an IBM Fellow in 2017. Hillery is a BS, MS, and PhD graduate of the University of Illinois at Urbana–Champaign.
This year marks the 50th anniversary of the Intel 4004, the world's first microprocessor and an engineering achievement that continues to evolve at a blistering pace. This technical and visionary panel offers the rare opportunity to bring together microprocessor experts who have been part of this evolution and watch them look back at 5 decades of achievement. We expect a lively discussion as the panel exchanges ideas about what the microprocessor might be in another 25 years (assuming it still exists in a recognizable form). The panelists collectively span most major microprocessor architectures and spent their careers at companies such as Acorn/Arm, Tensilica, Centaur, IBM, and Intel:
The panel will be moderated by J. Scott Gardner, an independent microprocessor-technology analyst. Panel Chair: Lizy K. John.
The biological and life sciences present a wealth of sophisticated and efficient computing substrates and, as a consequence, have been the source of inspiration for next-generation computing. This panel will cover emerging opportunities for research cross-pollination between the life sciences and computing technologies. Discussions will focus on topics ranging from machine learning and neural networks, brain computer interfaces, molecular & DNA computing, to the opportunities that they present for classical computing and acceleration, as well as emerging neuromorphic and quantum computing technologies
Virtual assistants today provide a proprietary voice interface for over 100,000 skills and are built with a 100,000-strong workforce. This talk presents the Stanford open virtual assistant initiative that uses deep learning to lower the development cost, improve the scalability and robustness, and to add dialogue capabilities to enhance the user experience. The research results are encapsulated in the Genie toolset to make voice interfaces as easy to build as web interfaces, and can thus accelerate the growth of an open worldwide voice web. In addition, the open-source assistant is federated to protect user privacy; it is distributed with Home Assistant, an open-source local gateway for home IoTs with over 100,000 users.
Dr. Monica Lam has been a Professor of Computer Science at Stanford University since 1988, and is the Faculty Director of the Stanford Open Virtual Assistant Laboratory. She leads the Genie open virtual assistant project, which aims to advance and democratize voice assistant technology, keep the voice web open, and protect the privacy of consumers.
Prof. Lam is a member of the National Academy of Engineering and an ACM Fellow. She has won numerous best paper awards, and has published over 150 papers on many topics: natural language processing, machine learning, HCI, compilers, computer architecture, operating systems, and high-performance computing. She is a co-author of the "Dragon Book", the definitive text on compiler technology. She received a B.Sc. from University of British Columbia (1980) and a Ph.D. from Carnegie Mellon University (1987).
Quantum computers promise to solve a class of commercial and scientifically important problems that are beyond the abilities of classical computers. Computing, whether it is conventional or quantum, is ultimately a series of transformations, ranging from algorithms at the top, to devices at the bottom. Over the past three decades, there has been significant progress in the field of quantum algorithms (which relies on mathematical properties of quantum states) and quantum devices (which relies on physical properties of materials), however, the role of computer systems (which transforms mathematics into physics) has only recently started to gain prominence.
This panel will discuss the role and the challenges for the architecture and compiler community in making quantum computing practical.
The new era of computer architecture heavily focuses on cross-stack system design with heterogeneous accelerators and new memory and storage systems. This change brings the opportunity and excitement of innovating new systems, but also introduces the challenge of building tools and system components necessary to evaluate radically new designs. The question we will discuss on this panel is the following: how should the architecture community propose, validate, and prototype ideas in this new era of computer architecture to maximize the impact?
Artificial intelligence (AI) is touching, if not transforming, every aspect of our lives. Fast-evolving AI algorithms are driving demand for general-purpose computing that cannot be met by "business as usual" engineering. At the same time, programmers are often data scientists, not computer scientists; expecting programmers to figure out increasingly complex hardware on their own just doesn't work. Architects are therefore needed more than ever – chip architects to create new processors, systems architects to design new data centers, software architects to design new frameworks, and AI architects to churn out new models and new algorithms. Are we up to the task? Or do we need to augment human architects with AI to meet the challenge?
Pradeep K. Dubey is an Intel Senior Fellow and director of the Parallel Computing Lab, a part of the Intel Labs organization at Intel Corporation. He leads a team of top researchers focused on state-of-the-art research in parallel computing. Dubey and his team are responsible for defining computer architectures that can efficiently handle emerging machine learning/artificial intelligence, traditional HPC applications for data-centric computing environments, and deriving product differentiation opportunities for Intel's CPU and GPU processing platforms. Dubey previously worked at IBM's T.J. Watson Research Center. Dubey has made significant contributions to the design, architecture and application performance of various microprocessors, including the IBM Power PC, the Intel386™, Intel486™, Intel® Pentium®, and Intel Xeon® processors. He holds 36 patents and has published more than 100 peer-reviewed technical papers. In 2012, Dubey was honored with an Intel Achievement Award for breakthroughs in parallel computing research, and was honored with the Outstanding Electrical and Computer Engineer Award from Purdue University in 2014. Dubey holds a Ph.D. in electrical engineering from Purdue University. He is also a Fellow of IEEE
The 50 years of microprocessor technologies have tremendously advanced all aspects of our lives. This panel provides us the space to examine the powerful technologies we are developing, responsibilities and societal impacts we must keep in mind when developing the technologies. This panel will discuss the societal challenges brought by digital technologies — the ever-increasing carbon emissions from computing, bias and fairness issues facing AI technologies, and the disparate social justice. What underinvested research directions should the community focus on in order to build environmentally-sustainable, socially-responsible technologies for the next decades to come?
In the last decade, the computer architecture research community has grown dramatically. There are now many young faculty and graduate students in many academic institutions. With the seismic changes taking place in our technical field, we have an opportunity to use these creative minds to crack some of the many computer systems architecture challenges. To do so, researchers need to be aware of the opportunities available to them. This panel will include leaders from industry and funding agencies who will help the audience reflect on the existing funding and research opportunities, priorities and future trends.