As Transformer models continue to grow in size and complexity, numerous high-fidelity pruning methods have been proposed to mitigate the increasing parameter count. However, transforming these ...

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, ...

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 ...

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 ...

Abstract: The solution of sparse matrix equations is essential in scientific computing. However, traditional solvers on digital computing platforms are limited by memory bottlenecks in largescale ...

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: The sparsity-regularized linear inverse problem has been widely used in many fields, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, ...

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 ...