Advanced Scientific Computing Research

Advanced Scientific Computing Research
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Name	Advanced Scientific Computing Research
Established	1990s
Type	Research program
Headquarters	Washington, D.C.
Parent	United States Department of Energy

Advanced Scientific Computing Research

Advanced Scientific Computing Research supports computational science initiatives across national laboratories and universities to accelerate simulation, data analysis, and algorithm development for energy, physics, chemistry, and materials. It operates within a network of facilities and partnerships that include national laboratories, federal agencies, and academic centers to advance high-performance computing, exascale systems, and software ecosystems. The program interfaces with projects and institutions involved in large-scale facilities, scientific instruments, and multidisciplinary collaborations.

Overview and Mission

The mission emphasizes scalable algorithms, high-performance computing platforms, and integrated software stacks to enable research in areas connected to Lawrence Livermore National Laboratory, Los Alamos National Laboratory, Argonne National Laboratory, Oak Ridge National Laboratory, and Sandia National Laboratories. It supports partnerships with universities such as Massachusetts Institute of Technology, Stanford University, University of California, Berkeley, Princeton University, and University of Illinois Urbana–Champaign and collaborates with agencies including National Aeronautics and Space Administration, National Science Foundation, National Institutes of Health, National Oceanic and Atmospheric Administration, and United States Department of Defense. The program aligns with strategic initiatives named by administrations associated with Barack Obama, Donald Trump, and Joe Biden administrations and coordinates on roadmaps discussed at venues like Supercomputing Conference and forums involving Gordon Bell Prize nominees.

Research Areas and Methodologies

Research emphasizes algorithms for partial differential equations used in modeling systems studied at CERN, Fermi National Accelerator Laboratory, Brookhaven National Laboratory, European Organization for Nuclear Research, and facilities such as Spallation Neutron Source. Methodologies include uncertainty quantification work linked to groups at California Institute of Technology, multiscale modeling pursued with collaborators at University of Chicago and Columbia University, and machine learning research intersecting projects at Carnegie Mellon University, University of Washington, and University of Toronto. Areas span computational chemistry relevant to Argonne National Laboratory collaborations on projects tied to Pacific Northwest National Laboratory and materials modeling similar to efforts at National Institute of Standards and Technology. Numerical linear algebra research connects with groups at Courant Institute, ETH Zurich, and Imperial College London, while graph algorithms and data analytics align with teams at Google, Microsoft Research, IBM Research, and NVIDIA. Research methodologies draw on practices from Lawrence Berkeley National Laboratory staff who published in venues like Communications of the ACM, SIAM Journal on Scientific Computing, and award circuits including the Turing Award and Enrico Fermi Award.

Software, Tools, and Infrastructure

The program funds development of software stacks and frameworks interoperable with projects such as Linux, OpenMP, MPI, and tools used by communities at CERN OpenLab, XSEDE, NEC Corporation, and hardware vendors like Intel, AMD, and NVIDIA. Infrastructure efforts involve collaborations on supercomputers at Oak Ridge National Laboratory (including systems from Cray Inc. and vendors connected to Hewlett Packard Enterprise), procurement linked to federal contracting practices involving General Services Administration, and operations coordinated with facility managers from National Energy Research Scientific Computing Center and Argonne Leadership Computing Facility. Software projects reference ecosystems that include GitHub, Apache Software Foundation, and package tools popularized by groups at University of California, San Diego and University of Michigan. Data management, visualization, and workflows intersect with instrument teams at SLAC National Accelerator Laboratory, European Synchrotron Radiation Facility, and initiatives such as Machine Learning for Science collaborations championed by research offices in Horizon 2020 programs.

Collaborations and Funding

Funding mechanisms include awards administered through offices with ties to Office of Science and Technology Policy, grant competitions analogous to DARPA programs, and partnerships with philanthropic entities similar to Gordon and Betty Moore Foundation and Simons Foundation. Collaborations span international laboratories like CERN, DESY, Rutherford Appleton Laboratory, and consortia including PRACE and EuroHPC. The program engages industrial partners such as Microsoft, Google DeepMind, IBM, NVIDIA Corporation, Intel Corporation, and Amazon Web Services for cloud and hardware collaborations. Governance and oversight involve interactions with congressional committees including those chaired historically by figures from United States Senate and United States House of Representatives and coordination with federal laboratories managed by Battelle Memorial Institute, University of California, and Fermilab administrative structures.

Education, Workforce, and Outreach

Workforce initiatives connect to graduate programs at Massachusetts Institute of Technology, California Institute of Technology, Harvard University, Yale University, University of Cambridge, University of Oxford, and training efforts through summer schools modeled after workshops at Argonne National Laboratory and Lawrence Berkeley National Laboratory. Outreach includes partnerships with professional societies such as IEEE, Association for Computing Machinery, Society for Industrial and Applied Mathematics, and conferences like International Conference for High Performance Computing, Networking, Storage and Analysis and NeurIPS to recruit diverse talent. Educational resources are developed in collaboration with consortia like XSEDE and initiatives inspired by programs at National Laboratories and universities with exchange programs involving European Commission research networks and international scholarships analogous to Fulbright Program.

Category:United States Department of Energy