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High Performance Computing

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DOE launches major 10-year project to use high performance computing for climate change research; ACME

August 24, 2014

Acme
The ACME Project Roadmap, showing the relative sequencing of major simulation campaigns, model version development, and machine deployment. Click to enlarge.

Eight national laboratories—Lawrence Livermore, Argonne, Brookhaven, Lawrence Berkeley, Los Alamos, Oak Ridge, Pacific Northwest and Sandia—are combining forces with the National Center for Atmospheric Research, four academic institutions and one private-sector company in a 10-year project to use high performance computing (HPC) to develop and to apply the most complete climate and Earth system model.

The project, called Accelerated Climate Modeling for Energy (ACME), is designed to accelerate the development and application of fully coupled, state-of-the-science Earth system models for scientific and energy applications. The plan is to exploit advanced software and new high performance computing machines as they become available. The initial focus will be on three climate change science drivers and corresponding questions to be answered during the project’s initial phase:

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32.5M hours of supercomputer time to aid GM, Ford engine projects with Oak Ridge Lab

August 06, 2014

Edwards-gm
Simulation of injector. Graphic from GM, Edwards AMR 2014 presentation. Click to enlarge.

As part of its 2014 ASCR Leadership Computing Challenge (ALCC) awards of processor time (totaling more than 3 billion processor hours), the US Department of Energy’s (DOE) Office of Science has awarded 15 million hours on Oak Ridge National Laboratory’s (ORNL) Titan supercomputer to a project led by General Motors, and 17.5 million hours on Titan to a project led by ORNL with Ford and Convergent Science as co-investigators. Titan is current Nº2 on the Top 500 Supercomputer list, and offers 27.1 petaflop (PF) peak processing capacity, with about 300,000 compute cores.

The two projects are part of a larger multi-year DOE-funded project to develop and to apply innovative simulation strategies and tools to maximize benefits of predictive information from high performance computing (HPC) for internal combustion engines. The Principal Investigator on that DOE project is Dean Edwards of ORNL.

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