1. University of California, Davis Daniel Zinn 1 University of California, Davis Daniel Zinn 1 Parallel Virtual Machines in Kepler Daniel Zinn Xuan Li Bertram Ludaescher Thursday, April 16, 2009, Berkeley, California Eighth Biennial Ptolemy Mini-conference

2. University of California, Davis Daniel Zinn 2 Outline Motivation & Related Work Lightweight Parallel PN Engine Kepler PPN Director Demo Future Directions & Conclusion

3. University of California, Davis Daniel Zinn 3 Motivation Kepler used to automate and build scientific apps maybe compute intensive maybe data intensive long-running Speed-up executions to save scientists time … by leveraging distributed resources

4. University of California, Davis Daniel Zinn 4 Distribution Efforts in Kepler / PTII Remote execution of a complete workflow Hydrant (Tristan King) Web service for remote execution (Jianwu Wang) Parameter sweeps with Nimrod/K (Colin Enticott, David Abramson, Ilkay Altintas) Distribution within actors “Plumping Workflows” with ad-hoc ssh-control (Nortbert Podhorszki) Globus actors in Kepler: GlobusJob, GlobusProxy, GridFTP, GridJob. GLite actors available through ITER Webservice executions by actors Distribution of few or all actors Distributed SDF Director (Daniel Cuadrado) Pegasus Director (Daniel Cuadrado and Yang Zhao) Master-Slave Distributed Execution (Chad Berkley and Lucas Gilbert) with DistributedCompositeActor PPN Director (Daniel Zinn and Xuan Li) Thanks to Jianwu for help with overview

5. University of California, Davis Daniel Zinn 5 Outline Motivation & Related Work Parallel PN Engine Kepler PPN Director Demo Future Directions & Conclusion

6. University of California, Davis Daniel Zinn 6 Lightweight Parallel PN Engine (LPPN) Motivation PN as inherently parallel MoC Build simple, efficient distributed PN-engine Design Requirements KISS Avoid centralization as much as possible Provide Actor and Port abstractions Allow actors being written in different languages “Experimentation Platform” for scheduling, data routing, … Design Priniciples One actor = one process Communication between actors Central component only for setup, termination detection, …

7. University of California, Davis Daniel Zinn 7 LPPN – Technology Choices C++ for core libraries Actor, Port, Token as C++ classes Parallel Virtual Machine (PVM) for parallelization Thin layer on top of machine clusters (pool of hosts) Message passing Implemented simple RPC on top of this SWIG for adding higher-languages above core Perl/Python interfaces for writing actors Perl interfaces for composing and starting workflow Java interface for composing, starting, monitoring workflows

8. University of California, Davis Daniel Zinn 8 LPPN – C++ Core Library: Actor

9. University of California, Davis Daniel Zinn 9 LPPN – C++ Core Library: Ports Ports are parameterized by the data type sent through the port. Data types: string int, double, … Custom structs BLOB Transfer via PVM messages

10. University of California, Davis Daniel Zinn 10 LPPN – C++ Core Library: Tokens BLOB_Token to encapsulate BLOB as files Construct from files LinkTo(path) File data is known to the workflow system Data is sent via rsync/scp by the LPPN system Each actor has private workspace in file system Generic Token Polymorphic Tokens for COMAD workflows Open, Close, BLOB, …

11. University of California, Davis Daniel Zinn 11 LPPN – Actor Communication (Ports) During Setup-Time Connect OutPorts to InPorts (1:1 mapping) During Runtime Port implementation sends data from port to port BlobToken-Ports handle file movement Block on read Block on write when buffer full (still fixed-size) Tokenbuffers in PVM, file-buffers in actor directory Gathering of statistics Actor status, token counts, …

12. University of California, Davis Daniel Zinn 12 Command-line Actor and Actors in Perl Example: ConvertResize Actor Automatically create input and output ports Read from input ports, call command, write to output ports

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14. University of California, Davis Daniel Zinn 14 Workflow Setup Start actors Connect all ports Unleash actors

15. University of California, Davis Daniel Zinn 15 Workflow-Script (sneak preview) Simple DSL for defining workflows Create Composite Actors Specify partial parameterizations Connect ports easily Check sanity (all ports connected, are types ok,…) Give deployment directives (hostname, co-locations) Run workflow

16. University of California, Davis Daniel Zinn 16 Workflow-Script Example

17. University of California, Davis Daniel Zinn 17 Outline Motivation & Related Work Parallel PN Engine Kepler PPN Director Demo Future Directions & Conclusion

18. University of California, Davis Daniel Zinn 18 Kepler PPN Director Idea: Use Kepler as sophisticated GUI Create, run and monitor LPPN workflows Marrying LPPN and Kepler – The PPN Director Drag’n’drop workflow creation (1:1 mapping for actors) Parameter support Hints for deployment from user Monitor token sending and receiving Monitor actor status …

19. University of California, Davis Daniel Zinn 19 PPN Director – Architecture Overview Kepler LPPN Local Machine

20. University of California, Davis Daniel Zinn 20 PPN Director – Design Decisions Proxy-Actors in Kepler represent Actors in LPPN Repository of available LPPN Actors in XML file (next slide) Actor-name Parameters and default values Ports Generic PPN-Actor is configured using this information Monitor actor state Send data from Kepler Actors to LPPN actors and vice versa PPN Director Start Actors with parameters, deployment info Connect Actors according to Kepler workflow Unleash and stop workflow execution

21. University of California, Davis Daniel Zinn 21 LPPN Actor Repository

22. University of California, Davis Daniel Zinn 22 Monitoring Support PPN Actors periodically probe LPPN actors for info Number of tokens sent and received Current actor state: Working Block on receive Block on write Sending BLOB tokens Displayed on actor while workflow is running …

23. University of California, Davis Daniel Zinn 23 Communication with Regular PN Actors? Sending data from regular Kepler Actors to LPPN and vice versa

24. University of California, Davis Daniel Zinn 24 Communication with Regular PN Actors

25. University of California, Davis Daniel Zinn 25 Communication with Regular PN Actors! Sending data from regular Kepler Actors to LPPN and vice versa

26. University of California, Davis Daniel Zinn 26 Outline Motivation & Related Work Lightweight Parallel PN Engine Kepler PPN Director Demo Future Directions & Conclusion

27. University of California, Davis Daniel Zinn 27 University of California, Davis Daniel Zinn 27

28. University of California, Davis Daniel Zinn 28 University of California, Davis Daniel Zinn 28

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30. University of California, Davis Daniel Zinn 30 Outline Motivation & Related Work Lightweight Parallel PN Engine Kepler PPN Director Demo Future Directions & Conclusion

31. University of California, Davis Daniel Zinn 31 Future Directions Adding Black-box (Java) actors as actors in LPPN Detailed measurements when actors need time for what Automatic movement of actors for CPU congestions (deploying spring/mass model) Automatic data parallelism (actor cloning and scatter+gather) Overhaul of LPPN, maybe in Java, RMI, JNI Better resource management

32. University of California, Davis Daniel Zinn 32 Conclusions LPPN – a simple, fast and extensible PN engine Kepler successfully used as front-end for LPPN Kepler for staging & monitoring Interoperability between Kepler and LPPN

33. University of California, Davis Daniel Zinn 33 University of California, Davis Daniel Zinn 33