Computing least squares condition numbers on hybrid multicore/GPU systems
نویسنده
چکیده
This paper presents an efficient computation for least squares conditioning or estimates of it. We propose performance results using new routines on top of the multicore-GPU library MAGMA. This set of routines is based on an efficient computation of the variance-covariance matrix for which, to our knowledge, there is no implementation in current public domain libraries LAPACK and ScaLAPACK.
منابع مشابه
Two-Stage Least Squares Algorithms with QR Decomposition for Simultaneous Equations Models on Heterogeneous Multicore and Multi-GPU Systems
G21 Z̃22 Z̃23 Z̃24 W̃21 G31 Z̃32 Z̃33 Z̃34 W̃31 G41 G42 Z̃43 Z̃44 W̃41 G51 G52 Z̃53 Z̃54 W̃51 Z11 Z12 Z13 Z14 W11 G21 Z̃22 Z̃23 Z̃24 W̃21 G31 Z̃32 Z̃33 Z̃34 W̃31 G41 G42 Z̃43 Z̃44 W̃41 G51 G52 Z̃53 Z̃54 W̃51 Two-Stage Least Squares algorithms with QR decomposition for Simultaneous Equations Models on heterogeneous multicore and multi-GPU systems Carla Ramiroa, José J. López-Espínb, Domingo Giménezc and Antonio M. Vidala
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تاریخ انتشار 2014