A Parallel Rendezvous Algorithm for Interpolation Between Multiple Grids
Steven J. Plimpton,Bruce Hendrickson,James A. Stewart +2 more
- 07 Nov 1998
- pp 1-8
41
TL;DR: This paper describes a grid transfer algorithm suitable for massively parallel codes which use multiple grids that uses a rendezvous technique wherein a third decomposition is used to search for elements in one grid that contain nodal points of the other.
read more
Abstract: A number of computational procedures employ multiple grids on which solutions are computed. For example, in multi-physics simulations a primary grid may be used to compute mechanical deformation of an object while a secondary grid is used for thermal conduction calculations. When modeling coupled thermo-mechanical effects, solution data must be interpolated back and forth between the grids each timestep. On a parallel machine, this grid transfer operation can be challenging if the two grids are decomposed to processors differently for reasons of computational efficiency. If the grids move or adapt separately, the complexity of the operation is compounded. In this paper we describe a grid transfer algorithm suitable for massively parallel codes which use multiple grids. It uses a rendezvous technique wherein a third decomposition is used to search for elements in one grid that contain nodal points of the other. This has the advantage of enabling the grid transfer to be load-balanced separately from the remainder of the computations. The algorithm has been implemented as an object-oriented tool for the multi-physics code SIERRA, currently under development at Sandia. Performance and scalability results for the grid transfer operation running on the Intel/Sandia TFLOPS supercomputer are presented.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Direct simulation Monte Carlo on petaflop supercomputers and beyond
Steven J. Plimpton,Stan Gerald Moore,Arnaud Borner,A. K. Stagg,Timothy P. Koehler,John R. Torczynski,Michail A. Gallis +6 more
TL;DR: SPARTA as mentioned in this paper is an implementation of the Direct Simulation Monte Carlo (DSMC) method for modeling rarefied gas dynamics in a variety of scenarios, and it can operate in parallel at the scale of many billions of particles or grid cells.
233
Parallel domain connectivity algorithm for unsteady flow computations using overlapping and adaptive grids
TL;DR: The algorithms and functionality of a new module developed to support overset grid assembly associated with performing time-dependent and adaptive moving body calculations of external aerodynamic flows using a multi-solver paradigm are described.
153
Software components for parallel multiscale simulation: an example with LAMMPS
TL;DR: It is concluded that it is possible to efficiently re-use existing single-scale simulation software as a component in multiscale-simulation software.
91
CHIMPS: A high-performance scalable module for multi-physics simulations
Juan J. Alonso,Seonghyeon Hahn,Frank Ham,Marcus Herrmann,Gianluca Iaccarino,Georgi Kalitzin,Patrick LeGresley,Ken Mattsson,Gorazd Medic,Parviz Moin,Heinz Pitsch,Jorg Schluter,Jorg Schluter,Magnus Svärd,E. van der Weide,Donghyun You,Xiaohua Wu +16 more
- 01 Jan 2006
TL;DR: This paper describes the efforts to develop a Coupler for High-Performance Integrated Multi-Physics Simulations, CHIMPS, that can enable the exchange of information between solvers and that automates the search, interpolation and communication processes in order to allow the developer to focus on appropriate strategies to couple solvers in an accurate and stable fashion.
49
A parallel rendezvous algorithm for interpolation between multiple grids
TL;DR: This paper describes a grid transfer algorithm suitable for massively parallel codes which use multiple grids that uses a rendezvous technique wherein a third decomposition is used to search for elements in one grid that contain nodal points of the other.
46
References
A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
George Karypis,Vipin Kumar +1 more
TL;DR: This work presents a new coarsening heuristic (called heavy-edge heuristic) for which the size of the partition of the coarse graph is within a small factor of theSize of the final partition obtained after multilevel refinement, and presents a much faster variation of the Kernighan--Lin (KL) algorithm for refining during uncoarsening.
A Partitioning Strategy for Nonuniform Problems on Multiprocessors
TL;DR: This work uses a binary decomposition of the domain to partition it into rectangles requiring equal computational effort, and studies the communication costs of mapping this partitioning onto different multiprocessors: a mesh- connected array, a tree machine, and a hypercube.
Parallel Smoothed Aggregation Multigrid : Aggregation Strategies on Massively Parallel Machines
Raymond S. Tuminaro,C. Tong +1 more
- 01 Nov 2000
TL;DR: This paper considers parallelization of the smoothe aggregation multigrid methods, and discusses three different parallel aggregation algorithms an illustrates the advantages an disadvantages of each variant in terms of parallelism an convergence.
A New Algorithm for Multi-objective Graph Partitioning
Kirk Schloegel,George Karypis,Vipin Kumar +2 more
- 31 Aug 1999
TL;DR: This work presents a new formulation of the multi-objective graph partitioning problem and describes an algorithm that computes partitionings with respect to this formulation and explains how this algorithm provides the user with a fine-tuned control of the tradeoffs among the objectives, results in predictable partitionings, and is able to handle both similar and dissimilar objectives.
Parallel strategies for crash and impact simulations
TL;DR: A general strategy is described effective for parallelizing solid mechanics simulations that has led to a parallel implementation of a widely used solid mechanics code that can now be run efficiently on thousands of processors of the Pentium-based Sandia/Intel TFLOPS machine.
82