Results 31 to 40 of about 164,297 (154)
Taking advantage of hybrid systems for sparse direct solvers via task-based runtimes [PDF]
, 2014 The ongoing hardware evolution exhibits an escalation in the number, as well as in the heterogeneity, of computing resources. The pressure to maintain reasonable levels of performance and portability forces application developers to leave the traditional
Bosilca, George +4 more
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Direct multiplicative methods for sparse matrices. Linear programming [PDF]
Компьютерные исследования и моделирование, 2017 Multiplicative methods for sparse matrices are best suited to reduce the complexity of operations solving systems of linear equations performed on each iteration of the simplex method.
Anastasiya Borisovna Sviridenko
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Element Aggregation for Estimation of High-Dimensional Covariance Matrices
MathematicsThis study addresses the challenge of estimating high-dimensional covariance matrices in financial markets, where traditional sparsity assumptions often fail due to the interdependence of stock returns across sectors.
Jingying Yang
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Magnus integrators on multicore CPUs and GPUs
, 2018 In the present paper we consider numerical methods to solve the discrete Schr\"odinger equation with a time dependent Hamiltonian (motivated by problems encountered in the study of spin systems). We will consider both short-range interactions, which lead
Auer, N. +3 more
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Controlling the level of sparsity in MPC [PDF]
, 2014 In optimization routines used for on-line Model Predictive Control (MPC), linear systems of equations are usually solved in each iteration. This is true both for Active Set (AS) methods as well as for Interior Point (IP) methods, and for linear MPC as ...
Axehill, Daniel
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Advanced Engineering Research, 2023 Introduction. The widespread use of piezoelectric materials in various industries stimulates the study of their physical characteristics and determines the urgency of such research.
P. A. Oganesyan, O. O. Shtein
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SparseM: A sparse matrix package for R: Working paper series--02-31 [PDF]
, 2002 SparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the package is illustrated by a family of linear model fitting functions that implement least squares methods for problems with sparse design matrices ...
Koenker, Roger, Ng, Pin
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A neighbor pixel modelled ROI for mammogram classification
ArrayThe effective selection of the Region of Interest (ROI) plays a vital role in enhancing the performance of computer-aided detection and diagnosis (CADx) systems.
Kanadam Karteeka Pavan +5 more
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Hierarchical Matrices Method and Its Application in Electromagnetic Integral Equations
International Journal of Antennas and Propagation, 2012 Hierarchical (H-) matrices method is a general mathematical framework providing a highly compact representation and efficient numerical arithmetic. When applied in integral-equation- (IE-) based computational electromagnetics, H-matrices can be regarded ...
Han Guo, Jun Hu, Hanru Shao, Zaiping Nie
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Auto-Selection of an Optimal Sparse Matrix Format in the Neuro-Simulator ANNarchy
Frontiers in Neuroinformatics, 2022 Modern neuro-simulators provide efficient implementations of simulation kernels on various parallel hardware (multi-core CPUs, distributed CPUs, GPUs), thereby supporting the simulation of increasingly large and complex biologically realistic networks ...
Helge Ülo Dinkelbach +3 more
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