Gonnet, Pedro Efficient and scalable algorithms for smoothed particle hydrodynamics on hybrid shared/distributed-memory architectures. (English) Zbl 1330.76113 SIAM J. Sci. Comput. 37, No. 1, C95-C121 (2015). Summary: This paper describes a new fast and implicitly parallel approach to neighbor-finding in multiresolution smoothed particle hydrodynamics (SPH) simulations. This new approach is based on hierarchical cell decompositions and sorted interactions, within a task-based formulation. It is shown to be faster than traditional tree-based codes and to scale better than domain decomposition-based approaches on hybrid shared/distributed-memory parallel architectures, e.g., clusters of multicores, achieving a \(40\times\) speedup over the Gadget-2 simulation code. MSC: 76M28 Particle methods and lattice-gas methods 65Y05 Parallel numerical computation 65N75 Probabilistic methods, particle methods, etc. for boundary value problems involving PDEs 15A09 Theory of matrix inversion and generalized inverses 15A15 Determinants, permanents, traces, other special matrix functions 15A23 Factorization of matrices Keywords:smoothed particle hydrodynamics; simulation; task-based parallelism; multicores Software:StarPU; GADGET; TREESPH; QUARK; deal.ii; CHARM++; MPI PDFBibTeX XMLCite \textit{P. Gonnet}, SIAM J. Sci. Comput. 37, No. 1, C95--C121 (2015; Zbl 1330.76113) Full Text: DOI arXiv