Load Balancing For High Performance Computing Using Quantum Annealing:Smoothed Particle Hydrodynamic

Authors: Omer Rathore, Department of Physics, Durham University; Alastair Basden, Department of Physics, Durham University; Nicholas Chancellor, Department of Physics, Durham University and School of Computing, Newcastle University; Halim Kusumaatmaja, Department of Physics, Durham University and Institute for Multiscale Thermofluids, School of Engineering, The University of Edinburgh.

relies on task based parallelism in order to optimise shared-memory performance within each individual node as its backbone. This can then be readily generalised to create a work allocation across multiple, distributed memory nodes using graph partitioning algorithms. In summary, the domain is initially divided into a set of cells, with each cell containing a collection of particles such that if two particles interact they are either in the same cell or at most neighbouring cells.

relies on the graph partitioning software METIS. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: Omer Rathore, Department of Physics, Durham University; Alastair Basden, Department of Physics, Durham University; Nicholas Chancellor, Department of Physics, Durham University and School of Computing, Newcastle University; Halim Kusumaatmaja, Department of Physics, Durham University and Institute for Multiscale Thermofluids, School of Engineering, The University of Edinburgh.

relies on task based parallelism in order to optimise shared-memory performance within each individual node as its backbone. This can then be readily generalised to create a work allocation across multiple, distributed memory nodes using graph partitioning algorithms. In summary, the domain is initially divided into a set of cells, with each cell containing a collection of particles such that if two particles interact they are either in the same cell or at most neighbouring cells.

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