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General framework for re-assuring numerical reliability in parallel Krylov solvers: A case of bi-conjugate gradient stabilized methods.
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- International Journal of High Performance Computing Applications, 2024, v. 38, n. 1, p. 17, doi. 10.1177/10943420231207642
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- Article
Reproducibility of parallel preconditioned conjugate gradient in hybrid programming environments.
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- International Journal of High Performance Computing Applications, 2020, v. 34, n. 5, p. 502, doi. 10.1177/1094342020932650
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- Article
Hierarchical approach for deriving a reproducible unblocked LU factorization.
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- International Journal of High Performance Computing Applications, 2019, v. 33, n. 5, p. 791, doi. 10.1177/1094342019832968
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- Article
Interoperability strategies for GASPI and MPI in large-scale scientific applications.
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- International Journal of High Performance Computing Applications, 2019, v. 33, n. 3, p. 554, doi. 10.1177/1094342018808359
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- Article
Gauss‐Newton‐Secant method for solving nonlinear least squares problems.
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- PAMM: Proceedings in Applied Mathematics & Mechanics, 2018, v. 18, n. 1, p. 1, doi. 10.1002/pamm.201800228
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Combined Newton-Kurchatov method for solving nonlinear operator equations.
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- PAMM: Proceedings in Applied Mathematics & Mechanics, 2016, v. 16, n. 1, p. 719, doi. 10.1002/pamm.201610348
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- Article
Methods with Successive and Parallel Approximations of Inverse Operator for the Nonlinear Least Squares Problem.
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- PAMM: Proceedings in Applied Mathematics & Mechanics, 2015, v. 15, n. 1, p. 569, doi. 10.1002/pamm.201510274
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- Article
On the Convergence Analysis of a Two-Step Modification of the Gauss-Newton Method.
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- PAMM: Proceedings in Applied Mathematics & Mechanics, 2014, v. 14, n. 1, p. 813, doi. 10.1002/pamm.201410387
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- Article
Gauss–Newton–Secant Method for Solving Nonlinear Least Squares Problems under Generalized Lipschitz Conditions.
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- Axioms (2075-1680), 2021, v. 10, n. 3, p. 158, doi. 10.3390/axioms10030158
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- Article
A taxonomy of task-based parallel programming technologies for high-performance computing.
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- Journal of Supercomputing, 2018, v. 74, n. 4, p. 1422, doi. 10.1007/s11227-018-2238-4
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- Article