Computing Least Squares Condition Numbers on Hybrid Multicore/GPU Systems

DOI10.1007/978-3-319-12307-3_6zbMath1331.65066OpenAlexW1484489343MaRDI QIDQ3459696

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Publication date: 11 January 2016

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://hal.inria.fr/hal-00947204/file/RR-8479.pdf

zbMATH Keywords

variance-covariance matrixleast squares conditioninglibrary MAGMA

Mathematics Subject Classification ID

Related Items (1)

Improved Bounds for Small-Sample Estimation

Uses Software

• LAPACK
• LSQR
• ScaLAPACK
• MAGMA

Cites Work

• Unnamed Item
• Towards dense linear algebra for hybrid GPU accelerated manycore systems
• Computing the conditioning of the components of a linear least-squares solution
• Parallel Tools for Solving Incremental Dense Least Squares Problems: Application to Space Geodesy
• LAPACK Users' Guide
• LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
• Statistical Condition Estimation for Linear Least Squares
• A Partial Condition Number for Linear Least Squares Problems

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