Topic: Hydrodynamics

The SAMRAI library is the code base in CASC for exploring application, numerical, parallel computing, and software issues associated with structured adaptive mesh refinement.

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In the HPC4EI project, LLNL and OxEon Energy will reduce the number of reactor tubes used to convert natural gas to liquid fuel, to lower cost and increase performance of synthetic fuel production.

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Twelve projects are awarded funding for the High Performance Computing for Energy Innovation Program, which leverages DOE’s HPC facilities to improve energy efficiency and manufacturing processes.

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The HPC4EI Initiative seeks industry partners to work with DOE labs to solve key technical challenges in manufacturing and mobility.

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After years of preparation, LLNL’s upgraded Ares code runs a 98-billion-element simulation on 16,384 GPUs on the Sierra supercomputer.

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Computational Scientist Ramesh Pankajakshan came to LLNL in 2016 directly from the University of Tennessee at Chattanooga. But unlike most recent hires from universities, he switched from research professor to professional researcher.

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Highlights include perspectives on machine learning and artificial intelligence in science, data driven models, autonomous vehicle operations, and the OpenMP standard 5.0.

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The HPC4EI program announced 9 public/private projects awarded more than $2 million from the DOE. This program is the umbrella entity for the HPC4Mfg and HPC4Mtls programs, headed out of LLNL.

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An LLNL team used LANL's Trinity supercomputer for a machine-learned surrogate representation of their laser-driven fusion implosion model.

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Highlights include debris an shrapnel modeling at NIF, scalable algorithms for complex engineering systems, magnetic fusion simulation, and data placement optimization on GPUs.

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Highlights include Computation’s annual external review, machine learning for ALE simulations, CFD modeling for low-carbon solutions, seismic modeling, and an in-line floating point compression tool.

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Through research funded at LLNL, scientists have developed BLAST, a high-order finite element hydrodynamics research code that improves the accuracy of simulations, provides a path to extreme parallel computing and exascale architectures, and gives an HPC advantage.

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Brian Gunney became fascinated with the field of computational fluid dynamics because he thought it could be critical in solving many problems he considered unsolvable.

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