Argonne National Laboratory, part of the U.S. Department of Energy (DOE), has announced a new partnership with RIKEN, Fujitsu, and NVIDIA. The collaboration, formalized through a memorandum of understanding (MOU) signed on January 27, aims to advance artificial intelligence (AI) and high-performance computing (HPC) to speed up scientific discovery.
The partnership supports the DOE’s Genesis Mission, a national initiative focused on leveraging advanced AI to accelerate research, enhance national security, and drive innovation in energy technologies.
Building on a previous agreement between Argonne and RIKEN from 2024, the four organizations will work together to develop next-generation computing infrastructure, design and evaluate software and applications for science and engineering, and expand the use of AI technologies to accelerate research breakthroughs.
“By combining AI and HPC, this collaboration takes a major step toward solving urgent scientific challenges in energy, national security, and fundamental research,” said Laboratory Director Paul Kearns. “Together, we are laying the groundwork for future computing systems and AI-driven scientific discovery in line with the goals of the Genesis Mission.”
The partnership will involve joint meetings, workshops, and engagement with the broader scientific community. Key focus areas include:
- Next-generation HPC and AI architectures: Designing computing systems that integrate simulation, modeling, and AI to tackle complex scientific problems.
- Integrated HPC platforms: Developing and testing end-to-end systems that combine hardware, software, and infrastructure.
- Shared AI software ecosystem: Creating an open, scalable software stack to support large-scale AI-driven research.
- Flagship AI applications: Demonstrating AI’s impact through high-value scientific projects that guide future computing systems.
- Laboratory automation: Using AI and robotics to automate experiments in research labs.
- Quantum computing acceleration: Exploring how AI combined with quantum computing can enable practical, large-scale scientific capabilities.
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