Three mysteries of Gaussian elimination
- 1 October 1985
- journal article
- Published by Association for Computing Machinery (ACM) in ACM SIGNUM Newsletter
- Vol. 20 (4) , 2-5
- https://doi.org/10.1145/1057954.1057955
Abstract
If numerical analysts understand anything, surely it must be Gaussian elimination. This is the oldest and truest of numerical algorithms. To be precise, I am speaking of Gaussian elimination with partial pivoting, the universal method for solving a dense, unstructured n X n linear system of equations Ax = b on a serial computer. This algorithm has been so successful that to many of us, Gaussian elimination and Ax = b are more or less synonymous. The chapter headings in the book by Golub and Van Loan [3] are typical -- along with "Orthogonalization and Least Squares Methods," "The Symetric Eigenvalue Problem," and the rest, one finds "Gaussian Elimination," not "Linear Systems of Equations."Keywords
This publication has 5 references indexed in Scilit:
- Forward error analysis of gaussian eliminationNumerische Mathematik, 1985
- How Can We Speed Up Matrix Multiplication?SIAM Review, 1984
- On the average number of steps of the simplex method of linear programmingMathematical Programming, 1983
- On the Asymptotic Complexity of Matrix MultiplicationSIAM Journal on Computing, 1982
- Gaussian elimination is not optimalNumerische Mathematik, 1969