A common data management infrastructure for adaptive algorithms for PDE solutions

Manish Parashar; James C. Browne; Carter Edwards; Kenneth Klimkowski

doi:10.1145/509593.509649

A common data management infrastructure for adaptive algorithms for PDE solutions

Manish Parashar, James C. Browne, Carter Edwards, Kenneth Klimkowski

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

12 Scopus citations

Abstract

This paper presents the design, development and application of a computational infrastructure to support the implementation of parallel adaptive algorithms for the solution of sets of partial differential equations. The infrastructure is separated into multiple layers of abstraction. This paper is primarily concerned with the two lowest layersof this infrastructure: A layer which defines and implements dynamic distributed arrays (DDA), and a layer in which several dynamic data and programming abstractions are implemented in terms of the DDAs. The currently implemented abstractions are those needed for formulation of hierarchical adaptive finite difference methods, hp-adaptive finite element methods, and fast multipole method for solution of linear systems. Implementation of sample applications based on each of these methods are described and implementation issues and performance measurements are presented.

Original language	English (US)
Title of host publication	Proceedings of the 1997 ACM/IEEE Conference on Supercomputing, SC 1997
Publisher	Association for Computing Machinery
ISBN (Print)	0897919858, 9780897919852
DOIs	https://doi.org/10.1145/509593.509649
State	Published - 1997
Event	1997 ACM/IEEE Conference on Supercomputing, SC 1997 - San Jose, CA, United States Duration: Nov 15 1997 → Nov 21 1997

Publication series

Name	Proceedings of the International Conference on Supercomputing

Other

Other	1997 ACM/IEEE Conference on Supercomputing, SC 1997
Country	United States
City	San Jose, CA
Period	11/15/97 → 11/21/97

All Science Journal Classification (ASJC) codes

Computer Science(all)

Keywords

Adaptive mesh-refinement
Distributed dynamic data structures
Fast multipole methods
Hp-adaptive finite elements
Parallel adaptive algorithm
Problem solving environment

Access to Document

10.1145/509593.509649

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title = "A common data management infrastructure for adaptive algorithms for PDE solutions",

abstract = "This paper presents the design, development and application of a computational infrastructure to support the implementation of parallel adaptive algorithms for the solution of sets of partial differential equations. The infrastructure is separated into multiple layers of abstraction. This paper is primarily concerned with the two lowest layersof this infrastructure: A layer which defines and implements dynamic distributed arrays (DDA), and a layer in which several dynamic data and programming abstractions are implemented in terms of the DDAs. The currently implemented abstractions are those needed for formulation of hierarchical adaptive finite difference methods, hp-adaptive finite element methods, and fast multipole method for solution of linear systems. Implementation of sample applications based on each of these methods are described and implementation issues and performance measurements are presented.",

keywords = "Adaptive mesh-refinement, Distributed dynamic data structures, Fast multipole methods, Hp-adaptive finite elements, Parallel adaptive algorithm, Problem solving environment",

author = "Manish Parashar and Browne, {James C.} and Carter Edwards and Kenneth Klimkowski",

year = "1997",

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Parashar, M, Browne, JC, Edwards, C & Klimkowski, K 1997, A common data management infrastructure for adaptive algorithms for PDE solutions. in Proceedings of the 1997 ACM/IEEE Conference on Supercomputing, SC 1997. Proceedings of the International Conference on Supercomputing, Association for Computing Machinery, 1997 ACM/IEEE Conference on Supercomputing, SC 1997, San Jose, CA, United States, 11/15/97. https://doi.org/10.1145/509593.509649

A common data management infrastructure for adaptive algorithms for PDE solutions. / Parashar, Manish; Browne, James C.; Edwards, Carter; Klimkowski, Kenneth.

Proceedings of the 1997 ACM/IEEE Conference on Supercomputing, SC 1997. Association for Computing Machinery, 1997. (Proceedings of the International Conference on Supercomputing).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Edwards, Carter

AU - Klimkowski, Kenneth

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N2 - This paper presents the design, development and application of a computational infrastructure to support the implementation of parallel adaptive algorithms for the solution of sets of partial differential equations. The infrastructure is separated into multiple layers of abstraction. This paper is primarily concerned with the two lowest layersof this infrastructure: A layer which defines and implements dynamic distributed arrays (DDA), and a layer in which several dynamic data and programming abstractions are implemented in terms of the DDAs. The currently implemented abstractions are those needed for formulation of hierarchical adaptive finite difference methods, hp-adaptive finite element methods, and fast multipole method for solution of linear systems. Implementation of sample applications based on each of these methods are described and implementation issues and performance measurements are presented.

AB - This paper presents the design, development and application of a computational infrastructure to support the implementation of parallel adaptive algorithms for the solution of sets of partial differential equations. The infrastructure is separated into multiple layers of abstraction. This paper is primarily concerned with the two lowest layersof this infrastructure: A layer which defines and implements dynamic distributed arrays (DDA), and a layer in which several dynamic data and programming abstractions are implemented in terms of the DDAs. The currently implemented abstractions are those needed for formulation of hierarchical adaptive finite difference methods, hp-adaptive finite element methods, and fast multipole method for solution of linear systems. Implementation of sample applications based on each of these methods are described and implementation issues and performance measurements are presented.

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KW - Hp-adaptive finite elements

KW - Parallel adaptive algorithm

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