Abstract
The natural preconditioner defined by local potentials is effective in the truncated Newton method for minimizing large scale biomolecular potential energy functions. This paper extends its definition, and proposes an algorithm for generating the sparse pattern of the preconditioner from the primary structure of a molecular system with N atoms. It shows that the implementation of the new compressed sparse preconditioner requires only a linear order of N memory locations.
This work was supported by the National Science Foundation through grant DMS-0241236, and, in part, by the Graduate School Research Committee Award (343267-101-4) of the University of Wisconsin-Milwaukee.
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Xie, D. (2004). An Effective Compressed Sparse Preconditioner for Large Scale Biomolecular Simulations. In: Zhang, J., He, JH., Fu, Y. (eds) Computational and Information Science. CIS 2004. Lecture Notes in Computer Science, vol 3314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30497-5_11
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DOI: https://doi.org/10.1007/978-3-540-30497-5_11
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