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 22 articles , 1 standard article )

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  1. Demidov, D.: AMGCL: an efficient, flexible, and extensible algebraic multigrid implementation (2019)
  2. Zampini, Stefano; Tu, Xuemin: Multilevel balancing domain decomposition by constraints deluxe algorithms with adaptive coarse spaces for flow in porous media (2017)
  3. 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)
  4. Mathias Jacquelin, Yili Zheng, Esmond Ng, Katherine Yelick: An Asynchronous Task-based Fan-Both Sparse Cholesky Solver (2016) arXiv
  5. Maurer, Daniel; Wieners, Christian: A scalable parallel factorization of finite element matrices with distributed Schur complements. (2016)
  6. Paszyński, Maciej: Fast solvers for mesh-based computations (2016)
  7. 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)
  8. Christopher Paciorek; Benjamin Lipshitz; Wei Zhuo; Prabhat; Cari G. Kaufman; Rollin Thomas: Parallelizing Gaussian Process Calculations in R (2015) not zbMATH
  9. Abgrall, R.; Beaugendre, H.; Dobrzynski, C.: An immersed boundary method using unstructured anisotropic mesh adaptation combined with level-sets and penalization techniques (2014)
  10. Georgescu, Serban; Chow, Peter; Okuda, Hiroshi: GPU acceleration for FEM-based structural analysis (2013)
  11. Hogg, Jonathan; Scott, Jennifer: New parallel sparse direct solvers for multicore architectures (2013)
  12. Ratnani, Ahmed; Sonnendrücker, Eric: An arbitrary high-order spline finite element solver for the time domain Maxwell equations (2012)
  13. Agullo, Emmanuel; Guermouche, Abdou; L’Excellent, Jean-Yves: Reducing the I/O volume in sparse out-of-core multifrontal methods (2010)
  14. Dupros, Fabrice; De Martin, Florent; Foerster, Evelyne; Komatitsch, Dimitri; Roman, Jean: High-performance finite-element simulations of seismic wave propagation in three-dimensional nonlinear inelastic geological media (2010)
  15. Hogg, J. D.; Reid, J. K.; Scott, J. A.: Design of a multicore sparse Cholesky factorization using DAGs (2010)
  16. Czarny, Olivier; Huysmans, Guido: Bézier surfaces and finite elements for MHD simulations (2008)
  17. Dolean, Victorita; Lanteri, Stéphane; Perrussel, Ronan: A domain decomposition method for solving the three-dimensional time-harmonic Maxwell equations discretized by discontinuous Galerkin methods (2008)
  18. Hénon, Pascal; Ramet, Pierre; Roman, Jean: On using an hybrid MPI-thread programming for the implementation of a parallel sparse direct solver on a network of SMP nodes (2006) ioport
  19. Amestoy, Patrick R.; Duff, Iain S.; Vömel, Christof: Task scheduling in an asynchronous distributed memory multifrontal solver (2005)
  20. Hénon, P.; Ramet, P.; Roman, J.: PaStiX: A high-performance parallel direct solver for sparse symmetric positive definite systems (2002)

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