Scientists from DOE's Pacific Northwest National Laboratory, DOE's Sandia National Laboratories, and the Georgia Institute of Technology will collaborate on solutions to some of the most challenging problems in AI.

PNNL senior research scientist Roberto Gioiosa will lead a new co-design center, ARtificial Intelligence-focused ARchitectures, and Algorithms (ARIAA), to promote collaboration between scientists at the three organizations PNNL, Sandia National Laboratories, and Georgia Institute of Technology. Three powerhouses in the realm of artificial intelligence have become partners in a new research center created by the U.S. Department of Energy. They develop core technologies essential for applying AI to DOE mission priorities, such as cybersecurity and electric grid resilience.

DOE's Office of Science funded $5.5M reinforces its commitment to accelerating the research, development, delivery, and adoption of AI and complements an earlier announcement by Secretary of Energy Rick Perry. He had announced the establishment of the DOE Artificial Intelligence and Technology Office (AITO) to coordinate the AI work done across the DOE enterprise. The development is in line with President Trump's call for a national strategy to assure AI technologies developed to impact the American public's lives positively.

PNNL senior research scientist Roberto Gioiosa will be the center's director and lead the overall vision, strategy, and research direction. Siva Rajamanickam from Sandia and Professor Tushar Krishna from Georgia Tech will serve as deputy directors.

Gioiosa said: “Artificial intelligence is revolutionizing our world. You can see this everywhere, from your mobile phone to the development of self-driving cars. AI is also revolutionizing the way we do science and how we tackle problems important to our nation. The creation of ARIAA is part of the strategy for solving some of the most challenging problems by employing novel artificial intelligence and machine learning techniques.”

One of the biggest difficulties facing researchers today is a problem of their own making: How to best design future supercomputers so that they can help DOE solve the nation's most challenging problems in science, engineering, health, and energy.

ARIAA centered around a concept known as “co-design,” which alludes to the need for researchers to weigh and balance hardware and software capabilities – how to corral the vastly different types of architectures and algorithms possible to best solve the problems at hand. What types of applications will run best on a given hardware setup, and conversely, what types of hardware need to be created to serve newly created software best? It's a balance that Gioiosa knows well: He was part of the team that 15 years ago built IBM Blue Gene, a powerful and efficient supercomputer whose heart is co-design.

While co-design requires a balance that computer scientists have faced for decades, AI's surging discipline demands newly focused attention.
The center will explore how AI and machine learning can support four areas that touch virtually everyone: the power grid, cybersecurity, graph analytics, and computational chemistry. Those disciplines touch upon how new medicines created, how to keep one's online identity safe, analyze masses of information, and keep the electric grid humming despite multiple challenges.

A focus of the center is to develop algorithms and architectures that can be used and applied in various systems, both today's and systems to be created in the future.

Each institution brings to the collaboration a unique strength:

  • PNNL has expertise in power grid simulation, chemistry, and cybersecurity and has done robust research in computer architecture and programming models and computing resources, including systems for testing emerging architectures.
  • Sandia has expertise in a software simulation of computer systems, machine learning algorithms, graph analytics, and sparse linear algebra. It will provide access to computer facilities and testbed systems to support early access to emerging computing architectures for code development testing.
  • Georgia Tech has expertise in modeling and developing custom accelerators for machine learning and sparse linear algebra and will provide access to its advanced computing resources.

Gioiosa said, “AI promises to yield answers to many problems in a fraction of the time compared to current processes. But more importantly, AI will allow us to solve problems today, that simply cannot be solved because they are too complex. It is the science of the future.”

About PNNL

Pacific Northwest National Laboratory draws on signature capabilities in chemistry, Earth sciences, and data analytics to advance scientific discovery and create solutions to the nation's toughest challenges in energy resiliency and national security. Founded in 1965, Battelle operated PNNL for the U.S. Department of Energy's Office of Science. DOE's Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit PNNL's News Center. Follow us on Facebook, LinkedIn, and Twitter.

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Date: October 2, 2019