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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Parashar, M. Browne, J.C. Edwards, C. Klimkowski, K. |
| Copyright Year | 1997 |
| Description | Author affiliation: University of Texas at Austin (Parashar, M.) |
| Abstract | We present 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 work is primarily concerned with the two lowest layers of 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. |
| Starting Page | 56 |
| Ending Page | 56 |
| File Size | 226693 |
| Page Count | 1 |
| File Format | |
| ISBN | 0897919858 |
| DOI | 10.1109/SC.1997.10028 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1997-11-15 |
| Access Restriction | Subscribed |
| Rights Holder | Association for Computing Machinery, Inc. (ACM) |
| Subject Keyword | Adaptive algorithm Dynamic programming Algorithm design and analysis Computer applications Concurrent computing Partial differential equations Finite difference methods Finite element methods Linear systems Measurement |
| Content Type | Text |
| Resource Type | Article |
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