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Grid Application Deployment

Grid Application Deployment. Adam Birnbaum Grid Applications Group -- SDSC birnbaum@sdsc.edu. Outline. Grid Promises and Reality NPACI and Teragrid Resources Costs of Distribution/Parallelism Good Candidates for Grid Deployment. Grid Promises. Interoperation of Distributed Resources

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Grid Application Deployment

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  1. Grid Application Deployment Adam Birnbaum Grid Applications Group -- SDSC birnbaum@sdsc.edu

  2. Outline • Grid Promises and Reality • NPACI and Teragrid Resources • Costs of Distribution/Parallelism • Good Candidates for Grid Deployment

  3. Grid Promises • Interoperation of Distributed Resources • Seamless Virtual Organizations • Computing as a Commodity • Transparent Computing • Harvesting of Idle Compute Time

  4. Grid Reality • Problems • Emerging Middleware • Confusing Hype • Difficulty of Application Development • Local Accounting and Scheduling Policies • No meta-schedulers or co-allocation • Grid: Distributed Computing, or HPC? (SETI@Home vs NPACI Grid?) • Opportunities • Some apps are well-suited to distributed resources • New types of systems are possible

  5. Grid Reality: Submitting Jobs jimbob.foo.edu peanutcluster.foo.edu bigiron.bar.edu

  6. Grid Reality: Submitting Jobs (SSH)1. Setup authorized keys jimbob.foo.edu peanutcluster.foo.edu bigiron.bar.edu ~/.ssh/authorized_keys ~/.ssh/identity.pub ~/.ssh/authorized_keys

  7. Grid Reality: Submitting Jobs (SSH)2. Write Batch Submission Script jimbob.foo.edu peanutcluster.foo.edu bigiron.bar.edu PBS script (submit.pbs): LoadLeveler script (submit.ll): #! /bin/sh #PBS –l nodes=80 #PBS –l walltime=00:10:00 ~/proj/doit #! /bin/sh #@ node=10 #@ wall_clock_limit=00:10:00 #@ <other special commands> ~/proj/doit

  8. Grid Reality: Submitting Jobs (SSH)3. Submit and monitor the jobs ssh ssh jimbob.foo.edu peanutcluster.foo.edu bigiron.bar.edu > qsub submit.pbs 8553.peanutcluster > qstat 8553 > llsubmit submit.ll llsubmit: The job “bigiron.7993” has been submitted > llq 7993

  9. Grid Reality: Submitting Jobs (Globus) jimbob.foo.edu peanutcluster.foo.edu bigiron.bar.edu

  10. Grid Reality: Submitting Jobs (Globus)1. Get in the remote grid-mapfiles jimbob.foo.edu peanutcluster.foo.edu bigiron.bar.edu email email > grep ‘Subject:’ ~/.globus/usercert.pem | mail theadmin@bar.edu > grep ‘Subject:’ ~/.globus/usercert.pem | mail sysadmin@foo.edu

  11. Grid Reality: Submitting Jobs (Globus)2. Write RSL Submission Script jimbob.foo.edu peanutcluster.foo.edu bigiron.bar.edu Globus RSL script (submit.rsl): &(executable=$(HOME)/doit) (count=80)(maxtime=10)

  12. Grid Reality: Submitting Jobs (Globus)3. Authenticate and Submit globus globus jimbob.foo.edu peanutcluster.foo.edu bigiron.bar.edu > grid-proxy-init > globus-job-submit peanutcluster.foo.edu submit.rsl https://peanutcluster.foo.edu:44159/30282/1061323349/ > globus-job-submit bigiron.foo.edu submit.rsl https://bigiron.foo.edu:44159/33242/1068476352/ > globus-job-status https://bigiron.foo.edu:44159/33242/1068476352/

  13. Grid Reality: Submitting Jobs • SSH Advantages • Ubiquitous • Can set up keys without involving sysadmins • Richness of batch scheduler syntax • Globus Advantages • Single batch submission syntax • Single signon • Certificates work transparently on good systems (like NPACI Grid and Teragrid) • Interface with portals

  14. Outline • Grid Promises and Reality • NPACI and Teragrid Resources • Costs of Distribution/Parallelism • Good Candidates for Grid Deployment

  15. NPACI Grid and NPACKage • NPACI Grid • BlueHorizon (SDSC, 1152 CPU’s, LoadLeveler) • Longhorn (TACC, 224 CPU’s, LoadLeveler) • Morpheus (U Mich., 134 CPU’s, PBS) • Hypnos (U Mich., 256 CPU’s, PBS) • http://npacigrid.npaci.edu • http://hotpage.npaci.edu • Software – NPACKage

  16. NPACKage • Grid Middleware packaging effort • Easy Installation • Included software: • NMI (Globus, GSI-SSH, Condor-G, NWS…) • NPACI products (SRB client, DataCutter, Ganglia, APST, LaPACK for Clusters) • http://npackage.npaci.edu

  17. Teragrid • Machines (all PBS) • SDSC (256 CPUs, 500 TB) • CalTech (64 Itanium 2 CPUs, 80 TB) • NCSA (512 CPUs, 230 TB) • Pittsburgh (3000 CPUs + 128 CPUs, 221 TB) • ANL (198 CPUs, 20TB) • Very fast backbone! But 50ms latency. • http://www.teragrid.org • Available Q1 ‘04 • Software – NMI

  18. Outline • Grid Promises and Reality • NPACI and Teragrid Resources • Costs of Distribution/Parallelism • Good Candidates for Grid Deployment

  19. Parallel Application Scalability • Speedup: ratio of serial to parallel runtime • Amdahl’s law: upper limit on speedup (ts/tp) ts = serial runtime tp = parallel runtime fs = serial fraction of program fp = parallel fraction of program N = number of CPU’s

  20. Amdahl’s Laww/ Extra Communication Costs, fp = .95

  21. Parallelizing: Keep in mind… • Scale, not speed, may be biggest advantage of parallelizing • Programming & debugging: tricky! • Keep inter-process communication within a single cluster. • Same issues apply to Grid apps, with heavier emphasis on communication NPACI Consultants can help!

  22. Costs of Distribution • Jim Gray, Microsoft Research (http://www.clustercomputing.org/content/tfcc-5-1-gray.html) • A dollar buys roughly: • 10 Tops (2 GHz CPU for $2000, 666 day lifetime) • 1 GB sent over a WAN (1 Mbps link @ $100/mo) • Conclusion: breakeven at 10,000 ops / byte • But: time on NPACI Grid & Teragrid is “free” • Metrics: time-to-solution, throughput, problem size • Time Costs: data transfer, queue, execution • Nmax cpu’s ~ texecution / ttransfer

  23. Grid Software Challenges • Tracking task states • Managing data files and dependencies • Failure detection and mitigation • Accessing heterogeneous resources • Application performance modeling • Application-specific issues

  24. Deploy on the Grid if… • Your app has limited inter-process communication • Bag-of-tasks or Parameter Sweeps • Workflow of Parallel Tasks • You have no other choice • Expensive or distributed data sources (detector, electron microscope) • Requirement is for a service or portal. • Insufficient allocations on any one cluster Otherwise, keep everything on one cluster!

  25. Good Grid App: Bag of Tasks • “Embarassingly Parallel”: Lots of single-CPU jobs, 1 process per task • Performance limited by file transfer times • Systems to look at • APST (http://grail.sdsc.edu/projects/apst) • Condor (http://www.cs.wisc.edu/condor) • MOSIX (http://www.mosix.org)

  26. Good Grid App: Workflow • Series of independent tightly-coupled codes • New performance factor: Queue time. • No silver bullets, but expect rapid progress • System to look at: Condor-G / DAGMan

  27. Portal • Hides complexity of distributing applications from users. • User interfaces for data management • Sharing of experiments and data • Systems to look at • GridPort (http://gridport.npaci.edu) • MyProxy (http://grid.ncsa.uiuc.edu/myproxy/) • GPDK (http://doesciencegrid.org//projects/GPDK/)

  28. Grid Application Deployment: Conclusions • Recommendations • Justify parallelization and distribution • Plan communication and data transfers carefully • Measure and monitor performance, utilization, throughput • Keep expectations of available software realistic • References • Parallel Computing: http://www.npaci.edu/PCOMP • NPACI Grid: http://npacigrid.npaci.edu • Teragrid: http://www.teragrid.org • NPACI Resources & User Manuals: http://hotpage.npaci.edu • GGF: http://www.gridforum.org

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