2010 06 pre_show_computing_lifesciences_stokesrees

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2010 06 pre_show_computing_lifesciences_stokesrees

  1. 1. Advancing Life Sciences Research with High Performance Computing and Cyberinfrastructure Ian Stokes-Rees Harvard Medical School SHOW - Making Biology Binary, June 2010
  2. 2. Dengue Virus Movie animation, not simulation, informed by science
  3. 3. digizyme.com
  4. 4. Science Behind the Movie Multi-scale Data intensive Dynamic Models Simulation Analysis Ian Stokes-Rees, NEBioGrid, Harvard Medical School June 23rd, 2010
  5. 5. Water channel through aquaporin tetramere in lipid bilayer Tajkhorshid, E., Nollert, P., Jensen, M.O., Miercke, L.J., O'Connell, J., Stroud, R.M., and Schulten, K. (2002). Science 296, 525-530
  6. 6. Molecular Dynamics Computationally intensive Necessarily parallel Nanosecond scale today Millisecond to second tomorrow Rapidly growing interest Ian Stokes-Rees, NEBioGrid, Harvard Medical School June 23rd, 2010
  7. 7. 48 cores, single system image
  8. 8. GPU Computing 200-800 stream processing cores per card
  9. 9. NextGen Sequencing
  10. 10. Collaborations and Communities
  11. 11. Boston Life Sciences Universities Hospitals Pharmaceuticals Research Institutes Tufts Universit y School of Medicin e Ian Stokes-Rees, NEBioGrid, Harvard Medical School June 23rd, 2010
  12. 12. Washington U. School of Med. Cornell U. R. Cerione NE-CAT T. Ellenberger B. Crane R. Oswald D. Fremont S. Ealick C. Parrish Rosalind Franklin NIH M. Jin H. Sondermann D. Harrison M. Mayer A. Ke UMass Medical U. Washington T. Gonen U. Maryland W. Royer E. Toth Brandeis U. UC Davis N. Grigorieff H. Stahlberg Tufts U. K. Heldwein UCSF Columbia U. JJ Miranda Q. Fan Y. Cheng Rockefeller U. Stanford R. MacKinnon A. Brunger Yale U. K. Garcia T. Boggon K. Reinisch T. Jardetzky D. Braddock J. Schlessinger Y. Ha F. Sigworth CalTech E. Lolis F. Zhou P. Bjorkman Harvard and Affiliates W. Clemons N. Beglova A. Leschziner G. Jensen Rice University S. Blacklow K. Miller D. Rees E. Nikonowicz B. Chen A. Rao Y. Shamoo Vanderbilt J. Chou T. Rapoport Y.J. Tao Center for Structural Biology J. Clardy M. Samso WesternU W. Chazin C. Sanders M. Eck P. Sliz M. Swairjo B. Eichman B. Spiller B. Furie T. Springer M. Egli M. Stone R. Gaudet G. Verdine UCSD B. Lacy M. Waterman M. Grant G. Wagner T. Nakagawa M. Ohi S.C. Harrison L. Walensky H. Viadiu Thomas Jefferson J. Hogle S.Walker J. Williams D. Jeruzalmi T.Walz Ian Stokes-Rees, NEBioGrid, Harvard Medical School D. Kahne June 23rd, 2010 J. Wang Not Pictured: University of Toronto: L. Howell, E. Pai, F. Sicheri; NHRI (Taiwan): G. Liou; Trinity College, Dublin: Amir Khan T. Kirchhausen S. Wong
  13. 13. If the particle physicists can use it...
  14. 14. Open Science Grid opensciencegrid.org
  15. 15. Grid Computing Federated and scalable Secure Standardized Compute sharing & cycle scavenging Dynamic formation of collaborations Data sharing Ian Stokes-Rees, NEBioGrid, Harvard Medical School June 23rd, 2010
  16. 16. Protein Structure Studies
  17. 17. Acknowledgements Piotr Sliz PI and SBGrid team leader Ian Levesque Systems Architect Ben Eisenbraun Software Curator Peter Doherty Grid Administrator Caitlin Colgrove Intern Software Engineer Steve Jahl System Administrator Ian Stokes-Rees, http://sbgrid.org
  18. 18. Summary Compute power increasingly affordable New computational techniques New hardware (multi-core, GPU) Grid and cloud computing Fast networking, cheap storage Scientists developing necessary skills Be in touch - ijstokes@hkl.hms.harvard.edu Ian Stokes-Rees, NEBioGrid, Harvard Medical School June 23rd, 2010
  19. 19. Extras
  20. 20. How to get a structural biologist using CI Ease of use No command line X.509 (initial request, VOs, proxies, Roles, etc.) are really complicated Support infrastructure (mailing lists, tickets, phone, training) Killer apps They will use it if they see peers using it to advance scientific goals They will use it if some novel workflows or workflow patterns are established Data management is a big problem for everyone (see bonus, time permitting) -- we believe grid infrastructure could provide a solution Security Data needs to be secure ... ... but users still want to control sharing/access Roadblocks Reliability of underlying infrastructure and difficulty in debugging Applications tied to GUIs, rudimentary interfaces Ian Stokes-Rees, SBGrid, Harvard Medical School October 13th, 2009
  21. 21. Security Challenges Identity Management Mixture of .htpasswd, PAM, X.509, and application-specific IDs Complexity of X.509 (and associated paraphernalia) confuses users account creation, use, and management Virtual Organization hierarchies and user-driven collaborations Inheritance of rights/policies How to allow users to easily create and manage groups Merging security policies Site/resource, VO, and user policies need to be merged Encryption and Privacy Preservation Generic mechanisms for encryption and key management Preserving privacy of actions and data in federated grid environment Ian Stokes-Rees, NEBioGrid, Harvard Medical School June 23rd, 2010
  22. 22. Security Work Meta data system Provide more generic pointers to ACLs and encryption keys Extension of GACL system Include non-X.509 ID tokens as policy principals Allow GACL policies to apply to web framework objects (pyGACL) Simple replicated key system for file encryption Use of meta-data framework to point to encryption key (and replicas) Use GACL to control key access (regular file) Libraries to automatically read/write encrypted files Future VO hierarchies Tools for user driven ACL management Tools for policy management (merging site, VO and user policies) Ian Stokes-Rees, NEBioGrid, Harvard Medical School June 23rd, 2010
  23. 23. Ian Stokes-Rees, http://sbgrid.org
  24. 24. Ian Stokes-Rees, http://sbgrid.org
  25. 25. Ian Stokes-Rees, http://sbgrid.org
  26. 26. Ian Stokes-Rees, http://sbgrid.org
  27. 27. Ian Stokes-Rees, http://sbgrid.org

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