Search Results - "Sparse matrix software"

Towards sparse matrix operations: graph database approach for power grid computation.

Authors: Daoxing Li Kai Xiao Xiaohui Wang et al.

Source: Global Energy Interconnection. Feb2023, Vol. 6 Issue 1, p50-63. 14p.

Solving Large Sparse Nonlinear Programs Using GRG.

Authors: Smith, Stuart Lasdon, Leon

Source: ORSA Journal on Computing. Winter92, Vol. 4 Issue 1, p2. 14p.

Textile fabric defect detection based on low-rank representation.

Authors: Shen, Xubang Li, Peng Zhao, Minghua et al.

Source: Multimedia Tools & Applications. Jan2019, Vol. 78 Issue 1, p99-124. 26p.

Subjects: Eigenvalues, Sparse matrix software, Singular value decomposition, Composite materials, Integrated circuits

GPU‐based Polynomial Finite Element Matrix Assembly for Simplex Meshes.

Authors: Mueller‐Roemer, J. S. Stork, A.

Source: Computer Graphics Forum; Oct2018, Vol. 37 Issue 7, p443-454, 12p, 1 Color Photograph, 3 Diagrams, 3 Charts, 2 Graphs

Explicit Fourth-Order Runge-Kutta Method on Intel Xeon Phi Coprocessor.

Authors: Bylina, Beata Potiopa, Joanna

Source: International Journal of Parallel Programming. Oct2017, Vol. 45 Issue 5, p1073-1090. 18p.

Subjects: Sparse matrices, Sparse matrix software, Multiprocessors, Markovian jump linear systems, Euler method, Vector algebra

Sparsity estimation based adaptive matching pursuit algorithm.

Authors: Yao, Shihong Wang, Tao Chong, Yanwen et al.

Source: Multimedia Tools & Applications. Feb2018, Vol. 77 Issue 4, p4095-4112. 18p.

Subjects: Image reconstruction algorithms, Sparse matrix software, Signal reconstruction, Restricted isometry property, Robust convex optimization

Ternary Sparse Matrix Representation for Volumetric Mesh Subdivision and Processing on GPUs.

Authors: Mueller‐Roemer, J. S. Altenhofen, C. Stork, A.

Source: Computer Graphics Forum. Aug2017, Vol. 36 Issue 5, p59-69. 11p.

Subjects: Sparse matrix software, Volumetric analysis, Graphics processing units, Mesh networks, Ternary system

Fast Fluid Simulations with Sparse Volumes on the GPU.

Authors: Wu, Kui Truong, Nghia Yuksel, Cem et al.

Source: Computer Graphics Forum; May2018, Vol. 37 Issue 2, p157-167, 11p, 6 Color Photographs, 4 Diagrams, 6 Charts

Improvement of workload balancing using parallel loop self-scheduling on Intel Xeon Phi.

Authors: Yang, Chao-Tung Huang, Chao-Wei Chen, Shuo-Tsung

Source: Journal of Supercomputing; Nov2017, Vol. 73 Issue 11, p4981-5005, 25p

G-IK-SVD: parallel IK-SVD on GPUs for sparse representation of spatial big data.

Authors: Song, Weijing Deng, Ze Wang, Lizhe et al.

Source: Journal of Supercomputing; Aug2017, Vol. 73 Issue 8, p3433-3450, 18p

MINIMUM-RANK POSITIVE SEMIDEFINITE MATRIX COMPLETION WITH CHORDAL PATTERNS AND APPLICATIONS TO SEMIDEFINITE RELAXATIONS.

Authors: XIN JIANG YIFAN SUN ANDERSEN, MARTIN S. et al.

Source: Applied Set-Valued Analysis & Optimization; 2023, Vol. 5 Issue 2, p265-283, 19p

Semi-deterministic Sparse Matrix for Low Complexity Compressive Sampling.

Authors: Lei Quan Song Xiao Xiao Xue et al.

Source: KSII Transactions on Internet & Information Systems; May2017, Vol. 11 Issue 5, p2468-2483, 16p, 1 Chart, 6 Graphs

Sparse LU Factorization for Parallel Circuit Simulation on GPU.

Authors: Ling Ren Xiaoming Chen Yu Wang et al.

Source: DAC: Annual ACM/IEEE Design Automation Conference; Jun2012, p1125-1130, 6p

BANDWIDTH REDUCTION ON SPARSE MATRICES BY INTRODUCING NEW VARIABLES.

Alternate Title: REDUCCIÓN DEL ANCHO DE BANDA DE MATRICES DISPERSAS MEDIANTE LA INTRODUCCIÓN DE NUEVAS VARIABLES.

Authors: Glüge, Rainer¹ gluege@ovgu.de

Source: INGENIARE - Revista Chilena de Ingeniería. 2010, Vol. 18 Issue 3, p395-400. 6p. 1 Diagram, 1 Chart.

Subjects: Sparse matrix software, Finite element method, Mathematical optimization, Linear systems, Asymptotic homogenization

Sparse conjugate directions pursuit with application to fixed-size kernel models.

Authors: Karsmakers, Peter Pelckmans, Kristiaan Brabanter, Kris et al.

Source: Machine Learning. Oct2011, Vol. 85 Issue 1-2, p109-148. 40p.

Subjects: Sparse matrix software, Machine learning, Linear systems, Algorithms, Support vector machines

A Library for Pattern-based Sparse Matrix Vector Multiply.

Authors: Belgin, Mehmet Back, Godmar Ribbens, Calvin J.

Source: International Journal of Parallel Programming. Feb2011, Vol. 39 Issue 1, p62-87. 26p. 7 Diagrams, 8 Charts, 5 Graphs.

Subjects: Sparse matrix software, Kernel functions, Bandwidths, Data transmission systems, Central processing units, Computer storage devices

Factorized Sparse Approximate Inverses for Preconditioning.

Authors: Huckle, Thomas¹ huckle@in.tum.de

Source: Journal of Supercomputing. Jun2003, Vol. 25 Issue 2, p109-117. 9p.

Subjects: Sparse matrix software, Sparse matrices, Matrices (Mathematics), Algorithms

Computing non-negative tensor factorizations.

Authors: Friedlander, MichaelP. Hatz, Kathrin

Source: Optimization Methods & Software. Aug2008, Vol. 23 Issue 4, p631-647. 17p. 1 Black and White Photograph, 1 Chart.

Subjects: Least squares software, Sparse matrix software, Factorization, Mathematical optimization, Mathematical analysis

Covariance selection for nonchordal graphs via chordal embedding.

Authors: Dahl, Joachim Vandenberghe, Lieven Roychowdhury, Vwani

Source: Optimization Methods & Software. Aug2008, Vol. 23 Issue 4, p501-520. 20p. 5 Diagrams, 3 Charts.

Subjects: Sparse matrix software, Mathematical optimization, Mathematical analysis, Embeddings (Mathematics), Analysis of covariance

Computing and analyzing recoverable supports for sparse reconstruction.

Authors: Kruschel, Christian Lorenz, Dirk

Source: Advances in Computational Mathematics; Dec2015, Vol. 41 Issue 6, p1119-1144, 26p