Výsledky vyhledávání - "Cleve Ashcraft"

Block Low-Rank Matrices with Shared Bases: Potential and Limitations of the BLR^2 Format

Autor: Alfredo Buttari, Théo Mary, Cleve Ashcraft

Publikováno v: SIAM Journal on Matrix Analysis and Applications
SIAM Journal on Matrix Analysis and Applications, Society for Industrial and Applied Mathematics, In press

International audience; We investigate a special class of data sparse rank-structured matrices that combine a flat block low-rank (BLR) partitioning with the use of shared (called nested in the hierarchical case) bases. This format is to H 2 matrices

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fecb1ae5c38c8f29d9e1f7789ab3f8c4
https://hal.archives-ouvertes.fr/hal-03070416/file/paper.pdf

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Scalability Challenges of an Industrial Implicit Finite Element Code

Autor: Francois-Henry Rouet, Cleve Ashcraft, James Ong, Erman Guleryuz, Todd A. Simons, Ting-Ting Zhu, Seid Koric, Robert F. Lucas, Jef Dawson, Roger G. Grimes

Publikováno v: IPDPS

LS-DYNA is a well-known multiphysics code with both explicit and implicit time stepping capabilities. Implicit simulations rely heavily on sparse matrix computations, in particular direct solvers, and are notoriously much harder to scale than explici

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2275322336c640271024fe4f838b2a8b
https://doi.org/10.1109/ipdps47924.2020.00059

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Improving Multifrontal Methods by Means of Block Low-Rank Representations

Autor: Patrick R. Amestoy, Olivier Boiteau, Cleve Ashcraft, Jean-Yves L'Excellent, Clement Weisbecker, Alfredo Buttari

Publikováno v: SIAM Journal on Scientific Computing
SIAM Journal on Scientific Computing, Society for Industrial and Applied Mathematics, 2015, 37 (3), pp.A1451-A1474. ⟨10.1137/120903476⟩
SIAM Journal on Scientific Computing, 2015, 37 (3), pp.A1451-A1474. ⟨10.1137/120903476⟩

International audience; Matrices coming from elliptic partial differential equations have been shown to have alow-rank property: well-defined off-diagonal blocks of their Schur complements can be approximatedby low-rank products. Given a suitable ord

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3dedbe6f40120ffdeec7bd56a5ca6327
https://hal.inria.fr/hal-01237169

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Robust Ordering of Sparse Matrices using Multisection

Autor: Joseph W. H. Liu, Cleve Ashcraft

Publikováno v: SIAM Journal on Matrix Analysis and Applications. 19:816-832

In this paper we provide a robust reordering scheme for sparse matrices. The scheme relies on the notion of multisection, a generalization of bisection. The reordering strategy is demonstrated to have consistently good performance in terms of fill re

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::10388331081a0290b0f967da8e7c9aa5
https://doi.org/10.1137/s0895479896299081

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Applications of the Dulmage--Mendelsohn Decomposition and Network Flow to Graph Bisection Improvement

Autor: Joseph W. H. Liu, Cleve Ashcraft

Publikováno v: SIAM Journal on Matrix Analysis and Applications. 19:325-354

In this paper, we consider the use of the Dulmage--Mendelsohn decomposition and network flow on bipartite graphs to improve a graph bisection partition. Given a graph partition [B, W, S] with a vertex separator S and two disconnected components B and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::972e517a616d33de5a5968ab1688961b
https://doi.org/10.1137/s0895479896308433

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Accurate Symmetric Indefinite Linear Equation Solvers

Autor: Cleve Ashcraft, Roger G. Grimes, John G. Lewis

Publikováno v: SIAM Journal on Matrix Analysis and Applications. 20:513-561

The Bunch-Kaufman factorization is widely accepted as the algorithm of choice for the direct solution of symmetric indefinite linear equations; it is the algorithm employed in both LINPACK and LAPACK. It has also been adapted to sparse symmetric inde

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4e70d964bdc359501b80fdec7876c8da
https://doi.org/10.1137/s0895479896296921

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Using domain decomposition to find graph bisectors

Autor: Joseph W. H. Liu, Cleve Ashcraft

Publikováno v: BIT Numerical Mathematics. 37:506-534

In this paper we introduce a three-step approach to find a vertex bisector of a graph. The first step finds adomain decomposition of the graph, consisting of a set of domains and a multisector. Eachdomain is a connected subgraph, and themultisector c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::28ea14eb44432218fc5bbd0a4b546ca0
https://doi.org/10.1007/bf02510238

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Compressed Graphs and the Minimum Degree Algorithm

Autor: Cleve Ashcraft

Publikováno v: SIAM Journal on Scientific Computing. 16:1404-1411

The minimum degree algorithm is well known and widely used to find a permutation matrix P such that a sparse symmetric positive definite matrix A can be factored as $PAP^T = LL^T $ to yield a lower triangular matrix L with relatively few nonzero entr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::37d068bc82331fb6147c90e27804c5ee
https://doi.org/10.1137/0916081

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A Fan-In Algorithm for Distributed Sparse Numerical Factorization

Autor: Stanley C. Eisenstat, Joseph W. H. Liu, Cleve Ashcraft

Publikováno v: SIAM Journal on Scientific and Statistical Computing. 11:593-599

This paper presents a column-oriented distributed algorithm for factoring a large sparse symmetric positive definite matrix on a local-memory parallel processor. Processors cooperate in computing each column of the Cholesky factor by calculating inde

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d45a1eb2244fffbc38c53109d9ffcfdb
https://doi.org/10.1137/0911033

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Performance Tuning of Matrix Triple Products Based on Matrix Structure

Autor: Cleve Ashcraft, James Demmel, Ismail Bustany, Katherine Yelick, Eun-Jin Im

Publikováno v: Applied Parallel Computing. State of the Art in Scientific Computing ISBN: 9783540290674
PARA

Sparse matrix computations arise in many scientific and engineering applications, but their performance is limited by the growing gap between processor and memory speed. In this paper, we present a case study of an important sparse matrix triple prod

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6196609140f7a871ace1b680ea61dba9
https://doi.org/10.1007/11558958_89

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