S. Filippone and M. Colajanni. PSBLAS: A library for parallel linear algebra computation on sparse matrices. ACM Transactions on Mathematical Software, 26(4):527--550, December 2000. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Automatic Performance Tuning and Analysis of Sparse .. - Vuduc, Kamil, Hsu, .. (2002) (Correct)
....using symbolic structures (e.g. the elimination tree) available during LU factorization. However, we do not assume access to such information. This assumption is consistent with the latest standardized Sparse BLAS interface [9] earlier interfaces [34, 31] and parallel sparse BLAS libraries [15]. void dense trisolve dot( int n, const double L, const double y, double x ) int i, j; 1 for( i = 0; i n; i ) 2 register double t = y[i] 3 for( j = 0; j i; j ) 4 t = L[i n j] x[j] 5 x[i] t L[i n i] void dense trisolve axpy( int n, const double L, const ....
S. Filippone and M. Colajanni. PSBLAS: A library for parallel linear algebra computation on sparse matrices. ACM Transactions on Mathematical Software, 26(4):527--550, December 2000.
An Object-Oriented Environment for Sparse Parallel.. - Filippone.. Self-citation (Filippone Colajanni) (Correct)
....of such applications on distributed memory parallel machines. Our solution is based on the PSBLAS library that already contains basic linear algebra routines for sparse computations on MIMD distributed memory computers [7] and a new object oriented interface implemented in Fortran 90 [9]. The key extension presented in this paper is the automatic support for dynamic grid refinement that provides the user with all data structures and operations necessary to work on dynamically refined computational grids. The standardization of numerical operations on sparse matrices has received ....
....are working with a second order discretization, it is necessary to employ a quadratic interpolation scheme to avoid a degradation in the accuracy. For the same reason, a finite element application would require additional continuity conditions. 3. PSBLAS Library The Parallel Sparse BLAS library [7, 9] has been designed and implemented to alleviate the problem of a proper implementation of implicit solvers on distributed memory machines. It contains numerical kernels and support operations oriented to the implementation of iterative solvers for sparse linear systems (the main kernels in ....
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S. Filippone, M. Colajanni, S. Maiolatesi. PSBLAS: A Library for Parallel Linear Algebra Computation on Sparse Matrices. Tech. Rep. DISP-RR-98.5, Dept. of Computer Engineering, University of Roma Tor Vergata, Mar. 1998. (http://www.ce.uniroma2.it/psblas/submitted2.ps)
Automatic Performance Tuning and Analysis of Sparse .. - Vuduc, Kamil, Hsu, .. (2002) (Correct)
No context found.
S. Filippone and M. Colajanni. PSBLAS: A library for parallel linear algebra computation on sparse matrices. ACM Transactions on Mathematical Software, 26(4):527--550, December 2000.
Performance Optimizations and Bounds for Sparse.. - Vuduc, Demmel, Yelick (2002) (4 citations) (Correct)
No context found.
Salvatore Filippone and Michele Colajanni. PSBLAS: A library for parallel linear algebra computation on sparse matrices. ACM Transactions on Mathematical Software, 26(4):527--550, December 2000.
Memory Hierarchy Optimizations and Performance Bounds.. - Vuduc, Gyulassy.. (2003) (Correct)
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Salvatore Filippone and Michele Colajanni. PSBLAS: A library for parallel linear algebra computation on sparse matrices. ACM Transactions on Mathematical Software, 26(4):527--550, December 2000.
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