Motion video analysis using planar parallax
Harpreet S. Sawhney
IS&T/SPIE Electronic Imaging 1994
During the past few years, algorithmic improvements alone have reduced the time required for the direct solution of unsymmetric sparse systems of linear equations by almost an order of magnitude. This paper compares the performance of some well-known software packages for solving general sparse sytems. In particular, it demonstrates the consistently high level of performance achieved by WSMP-the most recent of such solvers. It compares the various algorithmic components of to solvers and discusses their impact on solver performance. Our experiments show that the algorithmic choices made in WSMP enable it to run more than twice as fast as the best among similar solvers and that WSMP can factor some of the largest sparse matrices available from real applications in only a few seconds on a 4-CPU workstation. Thus, the combination of advances in hardware and algorithms makes it possible to solve those general sparse linear systems quickly and easily that might have been considered too large until recently.
Harpreet S. Sawhney
IS&T/SPIE Electronic Imaging 1994
Andrew Skumanich
SPIE Optics Quebec 1993
Salvatore Certo, Anh Pham, et al.
Quantum Machine Intelligence
Joy Y. Cheng, Daniel P. Sanders, et al.
SPIE Advanced Lithography 2008