Parallel tools for solving incremental dense least squares problems: application to space geodesy
نویسندگان
چکیده
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.
منابع مشابه
Parallel tools for solving incremental dense least squares
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 recentl...
متن کاملAn Incremental DC Algorithm for the Minimum Sum-of-Squares Clustering
Here, an algorithm is presented for solving the minimum sum-of-squares clustering problems using their difference of convex representations. The proposed algorithm is based on an incremental approach and applies the well known DC algorithm at each iteration. The proposed algorithm is tested and compared with other clustering algorithms using large real world data sets.
متن کاملA Boundary Meshless Method for Neumann Problem
Boundary integral equations (BIE) are reformulations of boundary value problems for partial differential equations. There is a plethora of research on numerical methods for all types of these equations such as solving by discretization which includes numerical integration. In this paper, the Neumann problem is reformulated to a BIE, and then moving least squares as a meshless method is describe...
متن کاملDealing with Dense Rows in the Solution of Sparse Linear Least Squares Problems1
Sparse linear least squares problems containing a few relatively dense rows occur frequently in practice. Straightforward solution of these problems could cause catastrophic ll and delivers extremely poor performance. This paper studies a scheme for solving such problems eeciently by handling dense rows and sparse rows separately. How a sparse matrix is partitioned into dense rows and sparse ro...
متن کاملSolving Rank-Deficient Linear Least-Squares Problems*
Numerical solution of linear least-squares problems is a key computational task in science and engineering. Effective algorithms have been developed for the linear least-squares problems in which the underlying matrices have full rank and are well-conditioned. However, there are few efficient and robust approaches to solving the linear least-squares problems in which the underlying matrices are...
متن کامل