Abstract: Algorithms are often parallelized based on data dependence analysis manually or by means of parallel compilers. Some vector/matrix computations such as the matrix-vector products with simple ...
Primary Algorithm : Algorithmically, Sparse-Sparse multiplication problems manifests itself in three possible forms:(a) Multiplication of a sparse matrix with a sparse diagonal, sparse block-diagonal, ...
Abstract: Real-time movie recommendation systems must efficiently handle large amounts of sparse user-item interaction data while maintaining great prediction accuracy. Conventional collaborative ...
ABSTRACT: Node renumbering is an important step in the solution of sparse systems of equations. It aims to reduce the bandwidth and profile of the matrix. This allows for the speeding up of the ...
Hefei National Laboratory for Physical Sciences at the Microscale, Department of Chemical Physics, and Synergetic Innovation Center of Quantum Information and Quantum Physics, University of Science ...
Recently, a research team from the FhG Institute for Applied Solid State Physics and the University of Cologne has made significant progress in the field of quantum computing by proposing a new ...
ABSTRACT: Node renumbering is an important step in the solution of sparse systems of equations. It aims to reduce the bandwidth and profile of the matrix. This allows for the speeding up of the ...
This repository shows off the (value, column, row pointer) matrix compression algorithm used for reducing the size of sparse matrices. When modeling a 2-dimensional Laplacian differential equation, a ...
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