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$\mathrm{LAMMPS}$ - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales

Computer Physics Communications

Thompson, Aidan P.; Aktulga, H.M.; Berger, Richard; Bolintineanu, Dan S.; Brown, W.M.; Crozier, Paul C.; In 'T Veld, Pieter J.; Kohlmeyer, Axel; Moore, Stan G.; Nguyen, Trung D.; Shan, Ray; Stevens, Mark J.; Tranchida, Julien; Trott, Christian R.; Plimpton, Steven J.

Since the classical molecular dynamics simulator LAMMPS was released as an open source code in 2004, it has become a widely-used tool for particle-based modeling of materials at length scales ranging from atomic to mesoscale to continuum. Reasons for its popularity are that it provides a wide variety of particle interaction models for different materials, that it runs on any platform from a single CPU core to the largest supercomputers with accelerators, and that it gives users control over simulation details, either via the input script or by adding code for new interatomic potentials, constraints, diagnostics, or other features needed for their models. As a result, hundreds of people have contributed new capabilities to LAMMPS and it has grown from fifty thousand lines of code in 2004 to a million lines today. In this paper several of the fundamental algorithms used in LAMMPS are described along with the design strategies which have made it flexible for both users and developers. We also highlight some capabilities recently added to the code which were enabled by this flexibility, including dynamic load balancing, on-the-fly visualization, magnetic spin dynamics models, and quantum-accuracy machine learning interatomic potentials.

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TYPE Journal Article YEAR 2021
DOIOSTI

Kokkos 3: Programming Model Extensions for the Exascale Era

IEEE Transactions on Parallel and Distributed Systems

Trott, Christian R.; Lebrun-Grandie, Damien; Arndt, Daniel; Ciesko, Jan; Dang, Vinh Q.; Ellingwood, Nathan D.; Gayatri, Rahulkumar; Harvey, Evan C.; Hollman, Daisy S.; Ibanez-Granados, Daniel A.; Liber, Nevin; Madsen, Jonathan; Miles, Jeff S.; Poliakoff, David Z.; Powell, Amy J.; Rajamanickam, Sivasankaran R.; Simberg, Mikael; Sunderland, Dan; Turcksin, Bruno; Wilke, Jeremiah

As the push towards exascale hardware has increased the diversity of system architectures, performance portability has become a critical aspect for scientific software. We describe the Kokkos Performance Portable Programming Model that allows developers to write single source applications for diverse high performance computing architectures. Kokkos provides key abstractions for both the compute and memory hierarchy of modern hardware. Here, we describe the novel abstractions that have been added to Kokkos recently such as hierarchical parallelism, containers, task graphs, and arbitrary-sized atomic operations. We demonstrate the performance of these new features with reproducible benchmarks on CPUs and GPUs.

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TYPE Journal Article YEAR 2021
DOIOSTI
Results 1–25 of 203
Results 1–25 of 203