Parallel Tools for Solving Incremental Dense Least Squares Problems: Application to Space Geodesy
Parallel Tools for Solving Incremental Dense Least Squares Problems: Application to Space Geodesy
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DOI：
10.1260/174830109787186541
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发表时间：
2009-03
影响因子：
0.9
通讯作者：
Arc Baboulin;L. Giraud;S. Gratton;J. Langou
中科院分区：
文献类型：
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作者：
Arc Baboulin;L. Giraud;S. Gratton;J. Langou
提出了一种并行分布求解器，使我们能够求解一些参数估计问题中出现的增量密集最小二乘问题。该求解器基于ScaLAPACK[8]和PBLAS[9]内核例程。在增量过程中，周期性地收集观测值，求解器使用QR分解算法用新的观测值更新解。它使用最近定义的分布式打包格式[3]，在基于scalapack的实现中处理对称或三角矩阵。我们提供IBM pSeries 690的性能分析。并给出了一个应用于空间大地测量学重力场计算的实例，并给出了一些实验结果。
We present a parallel distributed solver that enables us to solve incremental dense least squares arising in some parameter estimation problems. This solver is based on ScaLAPACK [8] and PBLAS [9] kernel routines. In the incremental process, the observations are collected periodically and the solver updates the solution with new observations using a QR factorization algorithm. It uses a recently defined distributed packed format [3] that handles symmetric or triangular matrices in ScaLAPACK-based implementations. We provide performance analysis on IBM pSeries 690. We also present an example of application in the area of space geodesy for gravity field computations with some experimental results.