Modeling polarization for Hyper-NA lithography tools and masks
Kafai Lai, Alan E. Rosenbluth, et al.
SPIE Advanced Lithography 2007
We present subroutines for the Cholesky factorization of a positive-definite symmetric matrix and for solving corresponding sets of linear equations. They exploit cache memory by using the block hybrid format proposed by the authors in a companion article. The matrix is packed into n(n + 1)/2 real variables, and the speed is usually better than that of the LAPACK algorithm that uses full storage (n2 variables). Included are subroutines for rearranging a matrix whose upper or lower-triangular part is packed by columns to this format and for the inverse rearrangement. Also included is a kernel subroutine that is used for the Cholesky factorization of the diagonal blocks since it is suitable for any positive-definite symmetric matrix that is small enough to be held in cache. We provide a comprehensive test program and simple example programs. © 2007 ACM.
Kafai Lai, Alan E. Rosenbluth, et al.
SPIE Advanced Lithography 2007
Hans Becker, Frank Schmidt, et al.
Photomask and Next-Generation Lithography Mask Technology 2004
Paul J. Steinhardt, P. Chaudhari
Journal of Computational Physics
David L. Shealy, John A. Hoffnagle
SPIE Optical Engineering + Applications 2007