Abstract
The motion of stars in the universe is determined by a gravitational field, which itself depends on the position and mass of all stars. We shall use this interesting astrophysical problem, called the N-body problem, to introduce particle methods. Algorithmically, these methods are substantially different from grid-oriented computations for two reasons. First, grid operators are short-range operators: they act only on neighboring grid points. Standard particle methods, on the other hand, feature long-range interactions: all particles interact with all other particles. Second, the load balance of multicomputer computations based on particle methods depends on computed values. This contrasts with grid-oriented computations, where the load balance depends only on the amount of data. From our experience with LU-decomposition, which is based on long-range operators and whose load balance is data-dependent through pivoting, we already know that data-distribution strategies play an important role for particle methods on multicomputers. However, as for grid-oriented computations, the data distribution is also tied to the geometry of the problem.
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© 1994 Springer Science+Business Media New York
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Van de Velde, E.F. (1994). Particle Methods. In: Concurrent Scientific Computing. Texts in Applied Mathematics, vol 16. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-0849-5_11
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DOI: https://doi.org/10.1007/978-1-4612-0849-5_11
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4612-6921-2
Online ISBN: 978-1-4612-0849-5
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