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Subsurface Biogeochemical Research Program

DOE User Facilities Enabling Science

High-Performance Computing and Data Storage Facilities

Several U.S. Department of Energy (DOE) computing facilities provide access to time on high performance production computing platforms and to associated data storage capabilities through a proposal process. The facilities outlined below should be considered for numerical modeling and simulation of surficial to subsurface hydrobiogeochemical processes:

Molecular Science Computing (MSC) Capability at EMSL

EMSL Cascade Supercomputer

The Molecular Science Computing (MSC)  capability within DOE's Environmental Molecular Sciences Laboratory (EMSL) provides an integrated production computing environment that supports a wide range of computational activities in environmental molecular research, including benchmark calculations on small molecules, reliable calculations on large molecules and solids, simulations of large biomolecules, large data bioinformatics computations, reactive chemical transport modeling, molecular thermodynamics and kinetics, heavy element chemistry, and other geochemistry and surface chemistry modeling and simulation.  EMSL encourages users to combine computational and state-of-the-art experimental tools, providing a cross-disciplinary environment to further research. To enable users to couple the power of high-performance, massively parallel computing systems with advanced computational chemistry techniques for molecular-level studies, MSC provides a comprehensive, integrated set of software tools, including NWChem, ecce, and ParSoft. More than 15 petabytes of hierarchical data storage are available for user research. MSC’s production capability is a 3.4 petaflop Cascade system, which is a 1440 Intel Xeon-Phi Node FDR-Infiniband Linux Cluster. This capability and the associated software and visualization and data storage capabilities are available onsite and remotely.

Allocation: These capabilities are available at no charge through a user proposal process.

DOE ASCR Computing User Facilities

The DOE Office of Advanced Scientific Computing Research (ASCR) supports several Office of Science user facilities for high performance production computing and data storage. These facilities include:

Edison Supercomputer at NERSC

National Energy Research Scientific Computing Center (NERSC)

NERSC, at Lawrence Berkeley National Laboratory, is the primary high performance computing resource for researchers directly supported by the DOE’s Office of Science. Edison is NERSC’s newest supercomputer, a Cray XC30, with a peak performance of 2.57 petaflops/sec, 133,824 compute cores, 357 terabytes of memory, and 7.56 petabytes of disk-based storage.  


OLCF Titan Supercomputer

Oak Ridge Leadership Computing Facility (OLCF)

The OLCF, at Oak Ridge National Laboratory, has a mission of accelerating scientific discovery and engineering progress by providing outstanding computing and data management resources to high-priority research and development projects. OLCF hosts Titan, the most powerful supercomputer for open science in the U.S. Titan is a hybrid-architecture Cray XK7 system with a theoretical peak performance of 27 petaflops. Titan is composed of a hybrid architecture that consists of a combination of NVIDIA Kepler graphics processing units (GPUs) and more conventional 16-core AMD Opteron central processing units (CPUs).


ALCF Mira Supercomputer

Argonne Leadership Computing Facility (ALCF)

The ALCF, at Argonne National Laboratory, has a mission of accelerating major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community. Mira is the ALCF's newest supercomputer. Mira is a 10 petaflop IBM Blue Gene/Q system.

DOE ASCR Allocation Mechanisms

Access to the production computing systems and data storage capabilities at NERSC, OLCF, and ALCF are available through several processes, as described on the ASCR web site. Opportunities to submit proposals for time allocations include:

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