% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Basermann:155203,
author = {Basermann, A.},
title = {{C}onjugate {G}radient and {L}anczos {M}ethods for {S}parse
{M}atrices on {D}istributed {M}emory {M}ultiprocessors},
journal = {Journal of parallel and distributed computing},
volume = {45},
number = {1},
issn = {0743-7315},
address = {Orlando, Fla.},
publisher = {Academic Press},
reportid = {FZJ-2014-04384},
pages = {46 - 52},
year = {1997},
abstract = {Conjugate gradient methods for solving sparse systems of
linear equations and Lanczos algorithms for sparse symmetric
eigenvalue problems play an important role in numerical
methods for solving discretized partial differential
equations. When these iterative solvers are parallelized on
a multiprocessor system with distributed memory, the data
distribution and the communication scheme—depending on the
data structures used for the sparse coefficient
matrices—are crucial for efficient execution. Here, data
distribution and communication schemes are presented that
are based on the analysis of the indices of the nonzero
matrix elements. On an Intel PARAGON XP/S 10 with 140
processors, the developed parallel variants of the solvers
show good scaling behavior for matrices with different
sparsity patterns stemming from real finite element
applications.},
cin = {ZAM / JSC},
ddc = {004},
cid = {I:(DE-Juel1)VDB62 / I:(DE-Juel1)JSC-20090406},
pnm = {899 - ohne Topic (POF2-899)},
pid = {G:(DE-HGF)POF2-899},
typ = {PUB:(DE-HGF)16},
UT = {WOS:A1997YE90400004},
doi = {10.1006/jpdc.1997.1364},
url = {https://juser.fz-juelich.de/record/155203},
}