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Talk for XSEDE day at Johns Hopkins

3ee44f53c39bcd4bc663a2ea0e21d526?s=47 James Taylor
September 11, 2014

Talk for XSEDE day at Johns Hopkins

Talk on Galaxy and specifically activities related to using XSEDE. Much help from Nate Coraor (@natefoo) and John Chilton (@jmchilton) for the slides and the work described.

3ee44f53c39bcd4bc663a2ea0e21d526?s=128

James Taylor

September 11, 2014
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  1. Galaxy Data intensive biology for everyone. www.galaxyproject.org @jxtx / #usegalaxy

  2. I ❤ SEQUENCING! High-Throughput v

  3. High-throughput sequencing is transformative

  4. Resequencing De novo genome sequencing Direct RNA sequencing Open Chromatin

    assays (DNase, FAIRE) Transcription factors (ChIP-seq) Histones variants (ChIP-seq, MNase-seq) Long range interactions (5C, Hi-C, ChIA-PET Methylation (Bisulfite-seq)
  5. High-throughput sequencing is democratizing

  6. (http://omicsmaps.com/) It is widely available...

  7. ...and practically free! (NHGRI / Nature 497:546–547)

  8. Making sense of this data requires sophisticated methods ! How

    can we ensure that these methods are accessible to researchers? ! ...while also ensuring that scientific results remain reproducible?
  9. Galaxy: accessible analysis system

  10. A free (for everyone) web service integrating a wealth of

    tools, compute resources, terabytes of reference data and permanent storage Open source software that makes integrating your own tools and data and customizing for your own site simple An open extensible platform for sharing tools, datatypes, workflows, ...
  11. Describe analysis tool behavior abstractly Analysis environment automatically and transparently

    tracks details Workflow system for complex analysis, constructed explicitly or automatically Pervasive sharing, and publication of documents with integrated analysis
  12. Visualization and visual analytics

  13. The free service is still the easiest way for users

    with no informatics infrastructure to analyze their data ! How can we possibly sustain this?
  14. ounded with a $1.5 million initial award, NCGAS dened and

    optimized genome analysis softw
  15. New Data per Month (TB) 0 30 60 90 120

    2008-04 2008-08 2008-12 2009-04 2009-08 2009-12 2010-04 2010-08 2010-12 2011-04 2011-08 2011-12 2012-04 2012-08 2012-12 2013-04 2013-08 usegalaxy.org data growth +128 cores for NGS/multicore jobs Data quotas implemented... Nate Coraor
  16. usegalaxy.org frustration growth Jobs Deleted Before Run (% of submitted)

    0% 2% 5% 7% 9% Total Jobs Completed (count) 0 40,000 80,000 120,000 160,000 2008-04 2008-08 2008-12 2009-04 2009-08 2009-12 2010-04 2010-08 2010-12 2011-04 2011-08 2011-12 2012-04 2012-08 2012-12 2013-04 2013-08 Nate Coraor
  17. How can this possibly scale? ! 1. Leverage exisiting public

    cyber-infrastructure ! 2. Decentralize, provide many deployment models (cloud and local — not talking about this today)
  18. Best place to build this robust entry point is clearly

    a national supercomputing center ! The Texas Advanced Computing Center (TACC) has already built substantial infrastructure in the context of the iPlant project ! (Including multi petabyte online storage, cloud infrastructure, collocated with some of the worlds largest HPC machines) ! However, the iPlant and TACC cyber-infrastructure was underused; thus we established a collaboration ! Since October 2013 Galaxy Main has run from TACC
  19. Transparent Migrations using Galaxy’s Hierarchical Object Store Galaxy Server Processes

    Corral Corral Staging Penn State Read Data In Corral? In Staging? In PSU? Yes Yes Yes No No No Object Not Found Write Data Nate Coraor
  20. Expanding to more XSEDE resources

  21. Galaxy can already run jobs on almost any batch system,

    but most XSEDE resources do not provide direct access for job submission…
  22. Pulsar ! Galaxy job runner that can run almost anywhere

    ! No shared filesystem, stages all necessary Galaxy components John Chilton
  23. Blacklight (PSC) Messaging Server Pulsar Galaxy Server Processes Stampede (TACC)

    Galaxy Server VMs (TACC) Pulsar Job control (AMQP) Data transfer (HTTPS) Data transfer (HTTPS) Nate Coraor
  24. Moving long running jobs out to XSEDE • Problem: •

    Jobs wait in the queue for a long time • Jobs may fail immediately upon run due to bad parameters • Most jobs run quickly! Can we relocate the long ones? ! • Goals: • Shorten wait from submission to start • Allow testing params without waiting ! • Solutions: • Set a short walltime, resubmit jobs to bigger resources (new code) • User selection of resources (Stampede - longer wait to start, but more concurrent jobs allowed) • Create “development” queues w/ short walltime Nate Coraor and John Chilton
  25. State of Affairs • Today • Galaxy Test jobs to

    Stampede and Blacklight • Galaxy Main jobs to Stampede ! • Up next • Galaxy Main jobs to Blacklight • Optimize Trinity tools for Blacklight • Linking XSEDE allocations to Galaxy accounts
  26. Credits • Texas Advanced Computing Center • Dan Stanzione •

    Matt Vaughn • Chris Jordan • Mike Packard • Nathaniel Mendoza ! • iPlant Collaborative • Stephen Goff
 • Pittsburgh Supercomputing Center • Philip Blood • Kathy Benninger • Robert Budden • Jared Yanovich • Josephine Palencia • J. Ray Scott • Joe Lappa ... and the Galaxy Team and community ! Galaxy is supported in part by NSF, NHGRI, Pennsylvania Department of Public Health, The Huck Institutes of the Life Sciences, The Institute for CyberScience at Penn State, and Johns Hopkins University
  27. Dan Blankenberg Nate Coraor Dannon Baker Jeremy Goecks Anton Nekrutenko

    James Taylor Dave Clements Jennifer Jackson Engineering Support and outreach Leadership Carl Eberhard Dave Bouvier John Chilton Sam Guerler Martin Čech Enis Afgan Supported by the NHGRI (HG005542, HG004909, HG005133, HG006620), NSF (DBI-0850103), Penn State University, Johns Hopkins University, and the Pennsylvania Department of Public Health Nick Stoler