Researchers Sang-Ho Kim, An-Ping Li, Bronson Messer and Zac Ward of ORNL have been named Fellows of the American Physical Society in recognition of their outstanding impact in their respective fields.
The Department of Energy has renewed funding for the Quantum Science Center through 2030 to create a new scientific ecosystem for fault-tolerant, quantum-accelerated high-performance computing.
ORNL, NVIDIA, and HPE are partnering to integrate quantum computing, AI, and high-performance computing using NVIDIA NVQLink and CUDA-Q, establishing a hybrid testbed at ORNL to advance quantum–classical convergence and scientific discovery.
The U.S. Department of Energy announced today its newest supercomputers, Discovery and Lux, at Oak Ridge National Laboratory that will expand America’s leadership in artificial intelligence for scientific computing, strengthen national security, and drive the next generation of Gold Standard Science and innovation.
The Simplified Interface to Complex Memories (SICM) project delivers a powerful software solution that abstracts away the complexity of modern, multi-tiered memory systems. By providing a unified interface and automated data placement strategies, SICM allows scientific applications to achieve optimal performance without requiring developers to write complex, non-portable code. This work is critical for the future of high-performance computing, as it enhances developer productivity, boosts application efficiency, and provides a durable framework for harnessing the power of next-generation computer architectures. The result is a practical and effective tool that makes exascale systems more accessible and powerful for the entire scientific community.
The research team developed an intelligent, automated software solution that elegantly solves the complex problem of managing data in modern computers with multiple memory types. This framework helps applications run more efficiently on today's advanced hardware, improves how resources are utilized in multi-tasking environments, and simplifies data management without requiring any manual intervention from programmers. By making heterogeneous memory systems both powerful and easy to use, this work provides an essential enabling technology for next-generation architectures, including systems with high-bandwidth and disaggregated memories.
Summary: Automation and autonomy can enable revolutionary scientific advances by coordinating a diverse array of experimental and computational capabilities more efficiently and more effectively than current hands-on approaches. This experiment creates an autonomous system to plan and adaptively control additive manufacturing build processes. It involves multiple characterization modes, computation across the edge-to-center computing continuum, and multiple scientific user facilities. The objective of the autonomous additive manufacturing (AAM) system is to control the residual stress in a part to address a grand challenge – building parts that are ready and safe to use immediately (i.e., “born qualified”). The AAM system is deployed at ORNL’s Manufacturing Demonstration Facility (MDF), Spallation Neutron Source (SNS), and Oak Ridge Leadership Computing Facility (OLCF) as a cross-facility instrument-science workflow. Its INTERSECT architecture consists of science use case design patterns, a system of systems architecture, and a microservices architecture. For more details see: https://intersect-architecture.readthedocs.io/en/latest/examples/aam/.
This research introduces a data-efficient, AI-driven framework for making smarter scheduling decisions in High-Performance Computing. By using attention-based techniques and intelligent data sampling, the method effectively models the complex trade-off between performance and power. This work paves the way for more sustainable next-generation supercomputing systems that accelerate scientific discovery while minimizing operational costs.
By combining AI with molecular dynamics simulations, researchers at ORNL have developed a new tool to more accurately predict how plants and helpful microbes communicate and form partnerships at the most fundamental level. The new AI-powered workflow helps scientists identify which plant genes control the best microbial partnerships.
Plant scientists representing a cross-section of academic and private sector research institutions joined colleagues from the Department of Energy’s Oak Ridge National Laboratory at a July workshop to review the Advanced Plant Phenotyping Laboratory (APPL) shared-use facility at ORNL, designed to quickly analyze new plant materials and cultivars, and to accelerate breeding of new biofuels,
Distinguished Staff Fellow, Paul Kairys is exploring the next frontier: bridging quantum computing with neutron science. His research aims to integrate quantum algorithms with neutron scattering experiments, opening new possibilities for understanding materials at an atomic level. Distinguished Staff Fellowship
Analyzing massive datasets from nuclear physics experiments can take hours or days to process, but researchers are working to radically reduce that time to mere seconds using special software being developed at the Department of Energy’s Lawrence Berkeley and Oak Ridge national laboratories.