Large sparse linear systems
The solution of large sparse linear systems on parallel computers using a hybrid implementation of the block Cimmino method
... 3.3. Two complementary Preprocessing Strategies based on Cuthill-McKee or by the number of rows in a contiguous subset of these diagonal blocks. The row partitioning we obtain from this still has the properties of the ...
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Parallel triangular solution in the out-of-core multifrontal approach for solving large sparse linear systems
... Perspectives We have shown how critical a scheduler can be in a parallel out-of-core environment. We have proposed an efficient local scheduler to improve the performance of the solution phase. Even if significant gains ...
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Hierarchical hybrid sparse linear solver for multicore platforms
... of large sparse linear systems is a critical operation for many numerical ...a sparse direct method and the problem on their interface with a preconditioned iterative method applied to ...
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On the numerical solution of sparse linear systems emerging in finite volume discretizations of 2D Boussinesq-type models
... This work is complementary to [18, 19] where, for the first time, a high-order well-balanced unstructured finite volume (FV) scheme on triangular meshes was presented for modeling weakly nonlinear and weakly dispersive ...
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Reordering Strategy for Blocking Optimization in Sparse Linear Solvers
... IN SPARSE LINEAR SOLVERS ∗ GREGOIRE PICHON † , MATHIEU FAVERGE ‡ , PIERRE RAMET † , AND JEAN ROMAN † ...Solving sparse linear systems is a problem that arises in many scientific ...
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A Recursive Sparse Learning Method: Application to Jump Markov Linear Systems
... batch sparse estimation has been extensively treated in the existing literature [6, 7], recursive sparse esti- mation is a problem that has not received much attention so ...too large, it may be ...
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Compression approaches for the regularized solutions of linear systems from large-scale inverse problems
... is sparse, having approximately ...very large: the dimensions of the matrix A are 2,968,933 × 3,637,248 and it is approximately 3 TB in size on the disk in a double precision sparse ...the ...
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Sparse analysis for mesoscale convective systems tracking
... 2) Object and shape tracking: Beside MCS tracking, there is a large corpus of literature addressing the problems of object tracking. One of the main approach in this regard is the Bayesian particle filtering ...
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Identification of switched linear systems via sparse optimization
... switched linear models, the algebraic-geometric method [32,21,30], the product-of-errors based method ...affine systems, i.e., particular switched linear/affine systems where the switching ...
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Optimization framework for large-scale sparse blind source separation
... tary sparse non-negative theoretical spectra of chemical compounds taken from the SDBS database 1 , which are further convolved with a Laplacian having a width of 3 samples to simulate a given spectral ...
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Trajectory Tracking Control Design for Large-Scale Linear Dynamical Systems With Applications to Soft Robotics
... through linear large-scale ...physical systems, and the finite-element method is one of the most common ...process. Large-scale dynamical systems arise from this spatial ...two ...
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Minimal single linear functional observers for linear systems
... single linear functional ( l = ...single linear functional of the state vector may be obtained by means of an observer of order (ν − 1), with arbitrary dynamics, where ν is the observability index of the ...
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Minimal single linear functional observers for linear systems
... Frédéric Rotella received his Ph.D. in 1983 and his Doctorat d’Etat in 1987 from the University of Science and Technology of Lille-Flandres-Artois, France. During this period, he served at the Ecole Centrale de Lille, ...
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Stacked Sparse Blind Source Separation for Non-Linear Mixtures
... the linear case, this prior is nevertheless not anymore sufficient to sep- arate the sources in the general non-linear setting ( Comon & Jutten , 2010 ...
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Scheduling Trees of Malleable Tasks for Sparse Linear Algebra
... perfect linear speed-up, and we rather concentrate on the case α < 1 which takes into consideration the cost of the ...runtime systems such as StarPU [3], KAAPI [9], or PaRSEC ...
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Sparse online self-organizing maps for large relational data
... Table 2. Average results for Astraptes fulgerator (100 random initializations, up- dates were made with a random design). Professional trajectories. The second example comes from [15]. It contains information about 2 000 ...
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Simulated Data for Linear Regression with Structured and Sparse Penalties
... for linear regression in which we control: The signal-to-noise ratio, the internal correlation structure of the data and the optimisation prob- lem that they are a solution ...
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Semi-linear diffusive representations for non-linear fractional differential systems
... Finally, in order to extend the sucient stability condition, a more ac- curate result can be conjectured, as a fractional version of the Hartman{ Grobman theorem, namely: Theorem 3 (Conjecture). The local stability of ...
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Minimal single linear functional observers for discrete-time linear systems
... I. I NTRODUCTION In observer design theory, it does not usually re- quired to observe all the states of the system so only a few number of functions of the states can be es- timated. Ever since Luenberger has introduced ...
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Low Cost Subspace Tracking Algorithms for Sparse Systems
... Index Terms— Principal subspace tracking, sparse sub- space, adaptive estimation, sparse source separation. 1. INTRODUCTION Subspace techniques play a fundamental role in statistical es- timation and ...
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