Parallel approximation of multidimensional tensors using GPUs

DOI10.1134/s0361768823040060OpenAlexW4385343164MaRDI QIDQ6094422

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Publication date: 13 September 2023

Published in: Programming and Computer Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1134/s0361768823040060

zbMATH Keywords

parallelizationlow-rank approximationCUDAGPUcross approximationlarge dimensionsmultidimensional arraystensor traindimension curseTT-crosstensor expansions

Mathematics Subject Classification ID

Parallel numerical computation (65Y05) Numerical methods for low-rank matrix approximation; matrix compression (65F55)

Cites Work

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• Tensor-Train Decomposition
• TT-cross approximation for multidimensional arrays
• Generalized descent for global optimization
• Pseudo-skeleton approximations by matrices of maximal volume
• Adaptive interpolation algorithm based on a kd-tree for numerical integration of systems of ordinary differential equations with interval initial conditions
• Analysis and optimization of an adaptive interpolation algorithm for the numerical solution of a system of ordinary differential equations with interval parameters
• Adaptive interpolation algorithm using TT-decomposition for modeling dynamical systems with interval parameters
• Methods for nonnegative matrix factorization based on low-rank cross approximations
• Tensor approximations of matrices generated by asymptotically smooth functions
• MATLAB® Kompakt

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