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Highly parallel sparse cholesky factorization
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Gilbert, John R. Schreiber, Robert |
| Copyright Year | 1990 |
| Description | Several fine grained parallel algorithms were developed and compared to compute the Cholesky factorization of a sparse matrix. The experimental implementations are on the Connection Machine, a distributed memory SIMD machine whose programming model conceptually supplies one processor per data element. In contrast to special purpose algorithms in which the matrix structure conforms to the connection structure of the machine, the focus is on matrices with arbitrary sparsity structure. The most promising algorithm is one whose inner loop performs several dense factorizations simultaneously on a 2-D grid of processors. Virtually any massively parallel dense factorization algorithm can be used as the key subroutine. The sparse code attains execution rates comparable to those of the dense subroutine. Although at present architectural limitations prevent the dense factorization from realizing its potential efficiency, it is concluded that a regular data parallel architecture can be used efficiently to solve arbitrarily structured sparse problems. A performance model is also presented and it is used to analyze the algorithms. |
| File Size | 1710544 |
| Page Count | 46 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_19910023533 |
| Archival Resource Key | ark:/13960/t4nk8898w |
| Language | English |
| Publisher Date | 1990-08-01 |
| Access Restriction | Open |
| Subject Keyword | Subroutines Algorithms Simd Computers Performance Prediction Massively Parallel Processors Linear Equations Memory Computers Parallel Processing Computers Cholesky Factorization Matrices Mathematics Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Technical Report |
