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Supercomputing for Molecular Dynamics Simulations
Handling Multi-Trillion Particles in Nanofluidics
eBook
Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9783319171487
Veröffentl:
2015
Einband:
eBook
Seiten:
76
Autor:
Alexander Heinecke
Serie:
SpringerBriefs in Computer Science
eBook Typ:
PDF
eBook Format:
Reflowable eBook
Kopierschutz:
Digital Watermark [Social-DRM]
Sprache:
Englisch
Beschreibung:
This work presents modern implementations of relevant molecular dynamics algorithms using ls1 mardyn, a simulation program for engineering applications. The text focuses strictly on HPC-related aspects, covering implementation on HPC architectures, taking Intel Xeon and Intel Xeon Phi clusters as representatives of current platforms. The work describes distributed and shared-memory parallelization on these platforms, including load balancing, with a particular focus on the efficient implementation of the compute kernels. The text also discusses the software-architecture of the resulting code.
This work presents modern implementations of relevant molecular dynamics algorithms using ls1 mardyn, a simulation program for engineering applications. The text focuses strictly on HPC-related aspects, covering implementation on HPC architectures, taking Intel Xeon and Intel Xeon Phi clusters as representatives of current platforms. The work describes distributed and shared-memory parallelization on these platforms, including load balancing, with a particular focus on the efficient implementation of the compute kernels. The text also discusses the software-architecture of the resulting code.
Introduction.- Molecular Dynamics Simulation.- Parallelization of MD Algorithms and Load Balancing.- Efficient Implementation of the Force Calculation in MD Simulations.- Experiments.- Conclusion.
This work presents modern implementations of relevant molecular dynamics algorithms using ls1 mardyn, a simulation program for engineering applications. The text focuses strictly on HPC-related aspects, covering implementation on HPC architectures, taking Intel Xeon and Intel Xeon Phi clusters as representatives of current platforms. The work describes distributed and shared-memory parallelization on these platforms, including load balancing, with a particular focus on the efficient implementation of the compute kernels. The text also discusses the software-architecture of the resulting code.