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Shikha Mehrotra Centre for Development of Advanced Computing CDAC, Bangalore, India

Shikha Mehrotra Centre for Development of Advanced Computing CDAC, Bangalore, India {shikham@cdac.in}. AN INGENIOUS APPROACH FOR IMPROVING TURNAROUND TIME OF GRID JOBS WITH RESOURCE ASSURANCE AND ALLOCATION MECHANISM. Outline. Indian National grid GARUDA Need for Reservation in Grid

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Shikha Mehrotra Centre for Development of Advanced Computing CDAC, Bangalore, India

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  1. ShikhaMehrotra Centre for Development of Advanced Computing CDAC, Bangalore, India {shikham@cdac.in} AN INGENIOUS APPROACH FOR IMPROVING TURNAROUND TIME OF GRID JOBS WITHRESOURCE ASSURANCE AND ALLOCATION MECHANISM IEEE HPEC'12

  2. Outline • Indian National grid GARUDA • Need for Reservation in Grid • Approach followed in realizing reservation in Garuda Grid • Architecture • Features • Performance analysis • Job flow in Garuda grid • Performance metrics • Turnaround time of grid jobs • Case-study • Turn-around time without reservation • Turn-around time with reservation • Data analysis • Results • Conclusion IEEE HPEC'12

  3. Grid Computing • Distributed Computing taken to the next level • Aggregation of Resources from many participants (geographically distributed in general) • Compute resources • Data resources • Special instruments (Telescopes, microscopes, so on..) • Unified, Seamless access to these resources • Analogous to the “Power Grid” IEEE HPEC'12

  4. India’s National Grid Computing Initiative: GARUDA • Motivation • To Collaborate on Research and Engineering of Technologies, Architectures, Standards and Applications in Grid Computing • To Contribute to the aggregation of resources in the Grid • Currently • Connects more than 60 institutions • Academic & Research labs • Spans across 17 cities of India • Supports 10 Virtual Organizations • Bioinformatics, Seismic engineering, Climate modeling, Drug discovery …. • Production infrastructure with • Gigabit networking backbone (NKN) • Large HPC computing resources • Massive Storage • Tools and Services for Unified Access IEEE HPEC'12

  5. Problem Statement • As the demand for the resources increases more and more, it becomes really difficult to manage the jobs and allocate resources to them and hence most of the jobs will be in the queued state waiting for the resource to be free. IEEE HPEC'12

  6. Our Approach • Reduce waiting time • Solution : Advance Reservation of resources • An advance reservation is a reservation that a user or administrator can request and the scheduler can create. • It guarantees the availability of resources at specified future time slot. IEEE HPEC'12

  7. Compute Reservation • An advance reservation is essentially defined by the following: • Start time which is defined using the standard date-time format • An end time, which is either defined using the standard date-time format or computed from the start time plus a duration value, • Number and type of resource to be reserved. IEEE HPEC'12

  8. APPLICATIONS COMMANDS API GARUDA GRID LEVEL RESERVATION COMPONENT RESERVATION DB GRIDWAY META-SCHEDULER GLOBUS MIDDLEWARE GARUDA MIDDLEWARE RESERVATION COMPONENT GARUDA LRM RESERVATION COMPONENT RESERVATION REPLICA DB RESERVATION MANAGER AND SCHEDULER FAILOVER LOCAL RESOURCE MANAGER Garuda Reservation Architecture

  9. Garuda Reservation Features • Advanced and Immediate Reservation of resources across multiple clusters • Ensure resource availability • GSI based reservation: Garuda Reservation • Grid Reservation Failover mechanism: • Application Programming Interface • Intelligent resource allocation based on QoS Parameters • Virtual Organization support • Avoiding resource under utilization • Integration with Gridway Meta-scheduler and Globus Middleware

  10. Performance Analysis IEEE HPEC'12

  11. Performance Metrics • Mean waiting time • Execution time • Turnaround time IEEE HPEC'12

  12. Turnaround Time • Turnaround time (total time taken between the submission of a program/process/thread/task (Linux) for execution and the return of the complete output to the customer/user) Job Submission Job Output User IEEE HPEC'12

  13. Performance Analysis IEEE HPEC'12

  14. Turn-around time without reservation IEEE HPEC'12

  15. Turn-around time without reservation IEEE HPEC'12

  16. Turn-around time with reservation IEEE HPEC'12

  17. Turn-around time with reservation IEEE HPEC'12

  18. Comparison of Turnaround times IEEE HPEC'12

  19. Conclusion • Guarantees the availability of resources • Eliminates the waiting time • Reduces Turnaround time considerably • Well integrates into the Grid Middleware • Built for the production infrastructure • Analysis has shown results that are really encouraging. IEEE HPEC'12

  20. Thank You IEEE HPEC'12

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