Advertisement

RAxML-OMP: An Efficient Program for Phylogenetic Inference on SMPs

  • Alexandros Stamatakis
  • Michael Ott
  • Thomas Ludwig
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3606)

Abstract

Inference of phylogenetic trees comprising hundreds or even thousands of organisms based on the Maximum Likelihood (ML) method is computationally extremely intensive. In order to accelerate computations we implemented RAxML-OMP, an efficient OpenMP-parallelization for Symmetric Multi-Processing machines (SMPs) based on the sequential program RAxML-V (Randomized Axelerated Maximum Likelihood). RAxML-V is a program for inference of evolutionary trees based upon the ML method and incorporates several advanced search algorithms like fast hill-climbing and simulated annealing. We assess performance of RAxML-OMP on the widely used Intel Xeon, Intel Itanium, and AMD Opteron architectures. RAxML-OMP scales particularly well on the AMD Opteron architecture and achieves even super-linear speedups for large datasets (with a length ≥ 5.000 base pairs) due to improved cache-efficiency and data locality. RAxML-OMP is freely available as open source code.

Keywords

Branch Length Phylogenetic Inference Alignment Length Open Source Code Distribute Shared Memory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bader, D.A., Moret, B.M.E., Vawter, L.: Industrial Applications of High-Performance Computing for Phylogeny Reconstruction. In: Proceedings of SPIE ITCom: Commercial Applications for High-Performance Computing, vol. 4528, pp. 159–168 (2001)Google Scholar
  2. 2.
    Bininda-Emonds, O.R.P., Brady, S.G., Sanderson, M.J., Kim, J.: Scaling of accuracy in extremely large phylogenetic trees. In: Proceedings of Pacific Symposium on Biocomputing, pp. 547–558 (2000)Google Scholar
  3. 3.
    Bodlaender, H.L., Fellows, M.R., Hallett, M.T., Wareham, T., Warnow, T.: The hardness of perfect phylogeny, feasible register assignment and other problems on thin colored graphs. Theor. Comp. Sci. 244, 167–188 (2000)zbMATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Day, W.E., Johnson, D.S., Sankoff, D.: The computational Complexity of inferring rooted phylogenies by parsimony. Math. Bios. 81, 33–42 (1986)zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Felsenstein, J.: Evolutionary Trees from DNA Sequences: A Maximum Likelihood Approach. J. Mol. Evol. 17, 368–376 (1981)CrossRefGoogle Scholar
  6. 6.
    Gascuel, O.: BIONJ: An improved version of the NJ algorithm based on a simple model of sequence data. Mol. Biol. Evol. 14, 685–695 (1997)Google Scholar
  7. 7.
    Guindon, S., Gascuel, O.: A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood. Syst. Biol. 52(5), 696–704 (2003)CrossRefGoogle Scholar
  8. 8.
    Gusfield, D., Eddhu, S., Langley, C.: Efficient Reconstruction of Phylogenetic Networks with Constrained Recombination. In: Proceedings of 2nd IEEE Computer Society Bioinformatics Conference, pp. 363–371 (2003)Google Scholar
  9. 9.
    Huelsenbeck, J.P., Ronquist, F., Nielsen, R., Bollback, J.P.: Bayesian Inference and its Impact on Evolutionary Biology. Science 294, 2310–2314 (2001)CrossRefGoogle Scholar
  10. 10.
    Huelsenbeck, J.P., Larget, B., Miller, R.E., Ronquist, F.: Potential Applications and Pitfalls of Bayesian Inference of Phylogeny. Syst. Biol. 51(5), 673–688 (2002)CrossRefGoogle Scholar
  11. 11.
    Hyper Transport Technology, www.hypertransport.org
  12. 12.
    Keane, T.M., Naughton, T.J., Travers, S.A.A., McInerney, J.O., McCormack, G.P.: DPRml: Distributed Phylogeny Reconstruction by Maximum Likelihood. Bioinformatics 21(7), 969–974 (2005)CrossRefGoogle Scholar
  13. 13.
    Olsen, G., Matsuda, H., Hagstrom, R., Overbeek, R.: fastdnaml: A Tool for Construction of Phylogenetic Trees of DNA Sequences using Maximum Likelihood. Comput. Appl. Biosci. 10, 41–48 (1994)Google Scholar
  14. 14.
  15. 15.
    PAUP project site, paup.csit.fsu.edu
  16. 16.
    Portland Group High-Performance Compilers and Tools, www.pgroup.com
  17. 17.
    PHYLIP downlaod site and list of phylogeny software, evolution.genetics.washington.edu
  18. 18.
    Schmidt, H.A., Strimmer, K., Vingron, M., Haeseler, A.v.: TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing. Bioinformatics 18, 502–504 (2002)CrossRefGoogle Scholar
  19. 19.
    Stamatakis, A., Ludwig, T., Meier, H.: RAxML-III: A Fast Program for Maximum Likelihood-based Inference of Large Phylogenetic Trees. Bioinformatics 21(4), 456–463 (2005)CrossRefGoogle Scholar
  20. 20.
    Stamatakis, A.: An Efficient Program for phylogenetic Inference Using Simulated Annealing. In: Proceedings of 19th International Parallel and Distributed Processing Symposium (2005); To be publishedGoogle Scholar
  21. 21.
    Stewart, C., Hart, D., Berry, D., Olsen, G., Wernert, E., Fischer, W.: Parallel Implementation and Performance of fastdnaml - a Program for Maximum Likelihood Phylogenetic Inference. In: Proceedings of SC 2001 (2001)Google Scholar
  22. 22.
    Strimmer, K., Haeseler, A.v.: Quartet Puzzling: A Maximum-Likelihood Method for Reconstructing Tree Topologies. Mol. Biol. Evol. 13, 964–969 (1996)Google Scholar
  23. 23.
    Swofford, D.L., Olsen, G.J., Wadell, P.J., Hillis, D.M.: Phylogenetic Inference. In: Hillis, D.M., Moritz, C., Mabel, B.K. (eds.) Molecular Systematics, ch. 11, Sinauer Associates, Sunderland, MA (1996)Google Scholar
  24. 24.
    Tang, J., Moret, B.M.E., Cui, L., de Pamphilis, C.W.: Phylogenetic reconstruction from arbitrary gene-order data. In: Proc. 4th IEEE Conf. on Bioinformatics and Bioengineering BIBE 2004, pp. 592–599 (2004)Google Scholar
  25. 25.
    The TreadMarks Distributed Shared Memory (DSM) System, www.cs.rice.edu/~willy/TreadMarks/overview.html
  26. 26.
  27. 27.
    Vinh, L.S., Haeseler, A.v.: IQPNNI: Moving fast through tree space and stopping in time. Mol. Biol. Evol. 21(8), 1565–1571 (2004)CrossRefGoogle Scholar
  28. 28.
    Williams, T.L., Moret, B.M.E.: An Investigation of Phylogenetic Likelihood Methods. In: Proceedings of 3rd IEEE Symposium on Bioinformatics and Bioengineering (2003)Google Scholar
  29. 29.
    Williams, T.L., Berger-Wolf, B.M., Roshan, U., Warnow, T.: The relationship between maximum parsimony scores and phylogenetic tree topologies. Tech. Report, TR-CS-2004-04. Department of Computer Science, The University of New Mexico (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Alexandros Stamatakis
    • 1
  • Michael Ott
    • 2
  • Thomas Ludwig
    • 3
  1. 1.Institute of Computer ScienceFoundation for Research and Technology-HellasHeraklion, CreteGreece
  2. 2.Department of Computer ScienceTechnical University of MunichGarching b. MünchenGermany
  3. 3.Department of Computer ScienceRuprecht-Karls UniversityHeidelbergGermany

Personalised recommendations