PaStiX

PaStiX: A high-performance parallel direct solver for sparse symmetric positive definite systems. Solving large sparse symmetric positive definite systems of linear equations is a crucial and time-consuming step, arising in many scientific and engineering applications. The block partitioning and scheduling problem for sparse parallel factorization without pivoting is considered. There are two major aims to this study: the scalability of the parallel solver, and the compromise between memory overhead and efficiency. Parallel experiments on a large collection of irregular industrial problems validate our approach.


References in zbMATH (referenced in 29 articles , 1 standard article )

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  1. Liu, Yang; Ghysels, Pieter; Claus, Lisa; Li, Xiaoye Sherry: Sparse approximate multifrontal factorization with butterfly compression for high-frequency wave equations (2021)
  2. Cambier, Léopold; Chen, Chao; Boman, Erik G.; Rajamanickam, Sivasankaran; Tuminaro, Raymond S.; Darve, Eric: An algebraic sparsified nested dissection algorithm using low-rank approximations (2020)
  3. Demidov, D.; Rossi, R.: Subdomain deflation combined with local AMG: a case study using AMGCL library (2020)
  4. Klockiewicz, Bazyli; Darve, Eric: Sparse hierarchical preconditioners using piecewise smooth approximations of eigenvectors (2020)
  5. Agullo, Emmanuel; Giraud, Luc; Poirel, Louis: Robust preconditioners via generalized eigenproblems for hybrid sparse linear solvers (2019)
  6. Demidov, D.: AMGCL: an efficient, flexible, and extensible algebraic multigrid implementation (2019)
  7. Kirby, Robert C.; Mitchell, Lawrence: Code generation for generally mapped finite elements (2019)
  8. Zampini, Stefano; Tu, Xuemin: Multilevel balancing domain decomposition by constraints deluxe algorithms with adaptive coarse spaces for flow in porous media (2017)
  9. Ghysels, Pieter; Li, Xiaoye S.; Rouet, François-Henry; Williams, Samuel; Napov, Artem: An efficient multicore implementation of a novel HSS-structured multifrontal solver using randomized sampling (2016)
  10. Mathias Jacquelin, Yili Zheng, Esmond Ng, Katherine Yelick: An Asynchronous Task-based Fan-Both Sparse Cholesky Solver (2016) arXiv
  11. Maurer, Daniel; Wieners, Christian: A scalable parallel factorization of finite element matrices with distributed Schur complements. (2016)
  12. Paszyński, Maciej: Fast solvers for mesh-based computations (2016)
  13. Stupfel, Bruno; Lecouvez, Matthieu: One-way domain decomposition method with exact radiation condition and fast GMRES solver for the solution of Maxwell’s equations (2016)
  14. Christopher Paciorek; Benjamin Lipshitz; Wei Zhuo; Prabhat; Cari G. Kaufman; Rollin Thomas: Parallelizing Gaussian Process Calculations in R (2015) not zbMATH
  15. Abgrall, R.; Beaugendre, H.; Dobrzynski, C.: An immersed boundary method using unstructured anisotropic mesh adaptation combined with level-sets and penalization techniques (2014)
  16. Georgescu, Serban; Chow, Peter; Okuda, Hiroshi: GPU acceleration for FEM-based structural analysis (2013)
  17. Hogg, Jonathan; Scott, Jennifer: New parallel sparse direct solvers for multicore architectures (2013)
  18. Ratnani, Ahmed; Sonnendrücker, Eric: An arbitrary high-order spline finite element solver for the time domain Maxwell equations (2012)
  19. Agullo, Emmanuel; Giraud, Luc; Guermouche, Abdou; Roman, Jean: Parallel hierarchical hybrid linear solvers for emerging computing platforms (2011)
  20. Agullo, Emmanuel; Guermouche, Abdou; L’Excellent, Jean-Yves: Reducing the I/O volume in sparse out-of-core multifrontal methods (2010)

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Further publications can be found at: http://www.labri.fr/perso/ramet/bib/Keyword/SPARSE.html