Bibliographic Details
| Title: |
EFFICIENT AND SCALABLE ALGORITHMS FOR SMOOTHED PARTICLE HYDRODYNAMICS ON HYBRID SHARED/DISTRIBUTED-MEMORY ARCHITECTURES. |
| Authors: |
GONNET, PEDRO1 gonnet@google.com |
| Source: |
SIAM Journal on Scientific Computing. 2015, Vol. 37 Issue 1, pC95-C121. 27p. |
| Subjects: |
Hydrodynamics, Hierarchical Bayes model, Hybrid computers (Computer architecture), Multiresolution time-domain method, Simulation methods & models |
| Abstract: |
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 40x speedup over the Gadget-2 simulation code. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |
