Skip to main content
SpringerLink
Log in
SpringerLink
Log in

Parallelization of General Matrix Multiply Routines Using OpenMP

  • Conference paper
Shared Memory Parallel Programming with Open MP (WOMPAT 2004)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3349))

Included in the following conference series:

Abstract

An application programmer interface (API) is developed to facilitate, via OpenMP, the parallelization of the double precision general matrix multiply routine called from within GAMESS [1] during the execution of the coupled-cluster module for calculating physical properties of molecules. Results are reported using the ATLAS library and the Intel MKL on an Intel machine, and using the ESSL and the ATLAS library on an IBM SP.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Schmidt, M.W., et al.: General Atomic and Molecular Elecronic Structure System. J. Comput. Chem. 14, 1347–1363 (1993)

    Article  Google Scholar 

  2. Santos, E.E.: Parallel Complexity of Matrix Multiplication. J. Supercomp. 25, 155–175 (2003)

    Article  MATH  Google Scholar 

  3. Lawson, C.L., Hanson, R.J., Kincaid, D.R., Krogh, F.T.: Basic Linear Algebra Subprograms for Fortran Usage. ACM Trans. Math. Soft. 5, 308–323 (1979)

    Article  MATH  Google Scholar 

  4. Lawson, C.L., Hanson, R.J., Kincaid, D.R., Krogh, F.T.: ALGORITHM 539, Basic Linear Algebra Subprograms for Fortran Usage. ACM Trans. Math. Soft. 5, 245–324 (1979)

    Article  Google Scholar 

  5. Dongarra, J.J., Du Croz, J., Hammarling, S., Hanson, R.J.: An Extended Set of FORTRAN Basic Linear Algebra Subprograms. ACM Trans. Math. Soft. 14, 1–17 (1988)

    Article  MATH  Google Scholar 

  6. Dongarra, J.J., Du Croz, J., Hammarling, S., Hanson, R.J.: ALGORITHM 656, An Extended Set of Basic Linear Algebra Subprograms: Model Implementation and Test Programs. ACM Trans. Math. Soft. 14, 18–32 (1988)

    Article  MATH  Google Scholar 

  7. Dongarra, J.J., Du Croz, J., Hammarling, S., Duff, I.: A Set of Level 3 Basic Linear Algebra Subprograms. ACM Trans. Math. Soft. 16, 1–17 (1990)

    Article  MATH  Google Scholar 

  8. GAMESS User’s Guide, http://www.msg.ameslab.gov/GAMESS/GAMESS.html

  9. Piecuch, P., Kucharski, S.A., Kowalski, K., Musial, M.: Efficient computer implementation of the renormailized coupled-cluster methods: The R-CCSD[T], R-CCSD(T), CR-CCSD[T], and CR-CCSD(T) approaches. Comput. Phys. Commun. 149, 71–96 (2002)

    Article  Google Scholar 

  10. Whaley, R.C., Petitet, A., Dongarra, J.J.: Automated Empirical Optimization of Software and the ATLAS project. Parallel Computing, 27, 3-35. Also available as University of Tennessee LAPACK Working Note #147, UT-CS-00-448 (2001), http://www.netlib.org/lapack/lawns/lawn147.ps

  11. Intel Corporation. Intel Math Kernel Library, Reference Manual, http://www.intel.com/software/products/mkl/docs/mklman61.htm

  12. IBM Corporation. Engineering and Scientific Subroutine Library for AIX Version 3 Release 3: Guide and Reference, http://publib.boulder.ibm.com/doc_link/en_US/a_doc_lib/sp34/essl/essl.html

  13. Dunning Jr., T.H.: Gaussian basis sets for use in correlated molecular calculations. I. The atoms boron through neon and hydrogen. J. Chem. Phys. 90, 1007–1023 (1989)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Scalable Computing Laboratory, Ames Laboratory, U.S. DOE, Department of Computer Science, Iowa State University, Ames, IA, 50011, USA

    Jonathan L. Bentz & Ricky A. Kendall

Authors
  1. Jonathan L. Bentz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ricky A. Kendall
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Dept. of Computer Science, University of Houston, 501 Philip G. Hoffman Hall, 4800 Calhoun Rd, 77204-3010, Houston, TX, USA

    Barbara M. Chapman

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bentz, J.L., Kendall, R.A. (2005). Parallelization of General Matrix Multiply Routines Using OpenMP. In: Chapman, B.M. (eds) Shared Memory Parallel Programming with Open MP. WOMPAT 2004. Lecture Notes in Computer Science, vol 3349. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31832-3_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-31832-3_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24560-5

  • Online ISBN: 978-3-540-31832-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation