Some Features of Gaussian Elimination with Rook Pivoting

نویسنده

  • Iain S. Duff
چکیده

Rook pivoting is a relatively new pivoting strategy used in Gaussian elimination (GE). It can be as computationally cheap as partial pivoting and as stable as complete pivoting. This paper shows some new attractive features of rook pivoting. We first derive error bounds for the LU factors computed by GE and show rook pivoting usually gives a highly accurate U factor. Then we show accuracy of the computed solution of a linear system by rook pivoting is essentially independent of row scaling of the coefficient matrix. Thus if the matrix is ill-conditioned due to bad row scaling a highly accurate solution can usually be obtained. Finally for a typical inversion method involving the LU factorization we show rook pivoting usually makes both left and right residuals for the computed inverse of a matrix small. AMS subject classification: 15A23, 65F05, 65G50

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Complete pivoting strategy for the $IUL$ preconditioner obtained from Backward Factored APproximate INVerse process

‎In this paper‎, ‎we use a complete pivoting strategy to compute the IUL preconditioner obtained as the by-product of the Backward Factored APproximate INVerse process‎. ‎This pivoting is based on the complete pivoting strategy of the Backward IJK version of Gaussian Elimination process‎. ‎There is a parameter $alpha$ to control the complete pivoting process‎. ‎We have studied the effect of dif...

متن کامل

Parallel Sparse Gaussian Elimination with Partial Pivoting and 2-d Data Mapping Parallel Sparse Gaussian Elimination with Partial Pivoting and 2-d Data Mapping Abstract Parallel Sparse Gaussian Elimination with Partial Pivoting and 2-d Data Mapping

Sparse Gaussian elimination with partial pivoting is a fundamental algorithm for many scientiic and engineering applications, but it is still an open problem to develop a time and space eecient algorithm on distributed memory machines. In this thesis, we present an asynchronous algorithm which incorporates static symbolic factorization, nonsymmetric L/U supernode partitioning and supern-ode ama...

متن کامل

Smoothed Analysis of Gaussian Elimination

We present a smoothed analysis of Gaussian elimination, both with partial pivoting and without pivoting. Let A be any matrix and let A be a slight random perturbation of A. We prove that it is unlikely that A has large condition number. Using this result, we prove it is unlikely that A has large growth factor under Gaussian elimination without pivoting. By combining these results, we bound the ...

متن کامل

Iterative Refinement Implies Numerical Stability for Gaussian Elimination

Because of scaling problems, Gaussian elimination with pivoting is not always as accurate as one might reasonably expect. It is shown that even a single iteration of iterative refinement in single precision is enough to make Gaussian elimination stable in a very strong sense. Also, it is shown that without iterative refinement row pivoting is inferior to column pivoting in situations where the ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2002