A new cross-research center was announced, funded with an initial $5.5 Million from the U.S. Department of Energy’s Office of Science, to promote collaboration between scientists at the three organizations to develop priorities, including but not limited to cybersecurity and electric grid resilience.
The Center for ARtificial Intelligence-focused ARchitectures and Algorithms (ARIAA), was formed to accelerate the research, development, delivery, and adoption of AI. This imitative complements an earlier announcement the DOE to establish the DOE Artificial Intelligence and Technology Office (AITO) to coordinate the AI work being done across the DOE enterprises.
PNNL senior research scientist Roberto Gioiosa will be the ARIAA’s director and will lead the overall vision, strategy and research direction. Gioiosa was part of the team that 15 years ago built IBM Blue Gene, a powerful and efficient supercomputer whose heart is co-design. Siva Raja Manickam from Sandia and Professor Tushar Krishna from Georgia Tech will serve as deputy directors.
In a statement, 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 the way 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.”
ARIAA will explore how AI and machine learning can support four areas that touch virtually everyone: the power grid, cybersecurity, graph analytics, and computational chemistry. A focus of the center is to develop algorithms and architectures that can be used and applied in a variety of different systems, both today’s as well as systems to be created in the future.
According to PNNL’s announcement, each institution brings unique strengths to the collaboration:
- PNNL has expertise in power grid simulation, chemistry, and cybersecurity and has done robust research in computer architecture and programming models, as well as computing resources, including systems for testing emerging architectures.
- Sandia has expertise in software simulation of computer systems, machine learning algorithms, graph analytics, and sparse linear algebra, and will provide access to computer facilities and testbed systems to support early access to emerging computing architectures for code development and 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.
“AI promises to yield answers to many problems in a fraction of the time compared to current processes,” said Gioiosa. “But more importantly, AI will allow us to solve problems today, that simply cannot be solved because they are too complex. This is the science of the future.
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