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The University of Texas at Austin

GridShell/Condor: A virtual login Shell for the NSF TeraGrid (How do you run a million jobs on the NSF TeraGrid?). The University of Texas at Austin. The NSF TeraGrid.

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The University of Texas at Austin

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  1. GridShell/Condor: A virtual login Shell for the NSF TeraGrid(How do you run a million jobs on the NSF TeraGrid?) The University of Texas at Austin

  2. The NSF TeraGrid • Links nine resource provider sites via a high speed 10/30 Gbps network backbone, providing, in aggregate, 20 teraflops of computing power, 1 petabyte of storage capacity, and high-end facilities for remote visualization of computing results. • Compute resources composed of a heterogeneous mix of clusters with different architectures and operating systems, running different workload management systems, with different local configuration, specifying different queues, with different job submission and run-time limits.

  3. What is GridShell? • GridShell extends TCSH, and BASH, to invoke interposition agents to perform explicit, as well as implicit actions, on behalf of the user. • Agents persists during the lifetime of the action, or of the gridshell login session.

  4. Example – A site independent script

  5. Motivation – Parametric Sweep Jobs are Common on the TeraGrid

  6. Motivation – Providing a persistent and robust environment across the Grid

  7. Example – A virtual login session from a client

  8. Features: GridShell/Condor on the TeraGrid • Automatically throttles condor_startd job submissions based on configurable local site policies. • Tolerates and recovers in the presence of transient faults in the WAN and login nodes. • Balances condor_startd jobs between sites based on queue wait times. • Shunts condor_startd jobs off temporary faulty sites. • Automatically renews grid proxy credentials across sites within the command environment. • Current users: Caltech CMS and NVO. SUBMITTED 70,000 jobs through clusters on TeraGrid to date.

  9. GridShell/Condor Process Architecture

  10. Why GridShell/Condor? • scalability - the actual parametric job submission is done directly to the compute nodes and not through the front-end node of the cluster; • fault-tolerance –agents at a front-end node of a cluster maintain the condor_startd submissions locally, allowing transient WAN outages and periodic front-end node reboots to be resolved independently, in isolation from the rest of the system; and • usability – the entire Condor submission, monitor, and control infrastructure is leveraged as a common job management environment for the user.

  11. Condor Pool created using NCSA, SDSC, CACR and TACC resources on the TeraGrid

  12. Condor pool created using NCSA, SDSC, CACR and TACC resources with pending job “balancing”

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