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  Accelerating Sparse Arithmetic in the Context of Newton’s Method for Small Molecules with Bond Constraints

Mikkelsen, C. C. K., Alastruey-Benedé, J., Ibáñez-Marín, P., & Risueño, P. G. (2016). Accelerating Sparse Arithmetic in the Context of Newton’s Method for Small Molecules with Bond Constraints. In R. Wyrzykowski, E. Deelman, J. Dongarra, K. Karczewski, J. Kitowski, & K. Wiatr (Eds.), Parallel Processing and Applied Mathematics (pp. 160-171). Berlin: Springer.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002A-C4F6-9 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-002A-C4F8-5
Genre: Book Chapter

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 Creators:
Mikkelsen, Carl Christian Kjelgaard 1, Author
Alastruey-Benedé, Jesús 2, Author
Ibáñez-Marín, Pablo 2, Author
Risueño, Pablo García3, 4, 5, Author           
Affiliations:
1Department of Computing Science and HPC2N, Umeå University, Umeå, Sweden, ou_persistent22              
2Instituto Universitario de Investigación en Ingeniería de Aragón (I3A), Universidad de Zaragoza, Zaragoza, Spain, ou_persistent22              
3Theory, Fritz Haber Institute, Max Planck Society, ou_634547              
4Institut für Physik, Humboldt Universität zu Berlin, Berlin, Germany, ou_persistent22              
5Instituto de Biocomputación y Física de Sistemas Complejos, Zaragoza, Spain, ou_persistent22              

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 Abstract: Molecular dynamics is used to study the time evolution of systems of atoms. It is common to constrain bond lengths in order to increase the time step of the simulation. Here we accelerate Newton’s method for solving the constraint equations for a system consisting of many identical small molecules. Starting with a modular and generic base code using a sequential data layout, we apply three different optimization techniques. The compiled code approach is used to generate subroutines equivalent to a single step of Newton’s method for a user specified molecule. Differing from the generic subroutines, these specific routines contain no loops and no indirect addressing. Interleaving the data describing different molecules generates vectorizable loops. Finally, we apply task fusion. The simultaneous application of all three techniques increases the speed of the base code by a factor of 15 for single precision calculations.

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 Dates: 2016-04-02
 Publication Status: Issued
 Pages: 12
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1007/978-3-319-32149-3_16
 Degree: -

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Title: Parallel Processing and Applied Mathematics
Source Genre: Book
 Creator(s):
Wyrzykowski, Roman, Editor
Deelman, Ewa, Editor
Dongarra, Jack, Editor
Karczewski, Konrad, Editor
Kitowski, Jacek, Editor
Wiatr, Kazimierz, Editor
Affiliations:
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Publ. Info: Berlin : Springer
Pages: 12 Volume / Issue: - Sequence Number: - Start / End Page: 160 - 171 Identifier: ISBN: 978-3-319-32148-6

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Title: Lecture Notes in Computer Science
  Other : Lect. Notes Comput. Sci.
Source Genre: Series
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Affiliations:
Publ. Info: Berlin : Springer
Pages: - Volume / Issue: 9573 Sequence Number: - Start / End Page: - Identifier: ISSN: 0302-9743