Search results for " linear systems"

showing 2 items of 12 documents

On solving separable block tridiagonal linear systems using a GPU implementation of radix-4 PSCR method

2018

Partial solution variant of the cyclic reduction (PSCR) method is a direct solver that can be applied to certain types of separable block tridiagonal linear systems. Such linear systems arise, e.g., from the Poisson and the Helmholtz equations discretized with bilinear finite-elements. Furthermore, the separability of the linear system entails that the discretization domain has to be rectangular and the discretization mesh orthogonal. A generalized graphics processing unit (GPU) implementation of the PSCR method is presented. The numerical results indicate up to 24-fold speedups when compared to an equivalent CPU implementation that utilizes a single CPU core. Attained floating point perfor…

Tridiagonal linear systemsProgramvaruteknikComputer Networks and CommunicationsComputer sciencePartial solution techniquereduction010103 numerical & computational mathematicsParallel computingtietotekniikka01 natural scienceslineaariset mallitTheoretical Computer ScienceSeparable spaceinformation technologyArtificial IntelligenceSeparable block tridiagonal linear systemBlock (telecommunications)Fast direct solverRadix0101 mathematicsta113Computer Sciencesta111Linear systemSoftware EngineeringGPU computingSolverComputer Science::Numerical Analysis010101 applied mathematicsPSCR methodDatavetenskap (datalogi)partial solution techniqueHardware and ArchitectureComputer Science::Mathematical Softwarepienennyslinear modelsSoftwareRoofline modelCyclic reductionJournal of Parallel and Distributed Computing
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Computational aspects in checking of coherence and propagation of conditional probability bounds

2000

In this paper we consider the problem of reducing the computational difficulties in g-coherence checking and propagation of imprecise conditional probability assessments. We review some theoretical results related with the linear structure of the random gain in the betting criterion. Then, we propose a modi ed version of two existing algorithms, used for g-coherence checking and propagation, which are based on linear systems with a reduced number of unknowns. The reduction in the number of unknowns is obtained by an iterative algorithm. Finally, to illustrate our procedure we give some applications.

reduced sets of variables and constrainsCoherent probability assessments propagation random gain computation algorithmsSettore MAT/06 - Probabilita' E Statistica MatematicaChecking of coherencerandom gainpropagationChecking of coherence; computational aspects; propagation; linear systems; random gain; reduced sets of variables and constrainslinear systemscomputational aspects
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