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Real-World Distributed Computing with Ibis Henri Bal bal@cs.vu.nl Vrije Universiteit Amsterdam

Explore distributed systems, applications, and the Ibis programming system. Learn about high-performance applications and integrating resources for real-world systems. Discover fundamental problems and solutions with Ibis.

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Real-World Distributed Computing with Ibis Henri Bal bal@cs.vu.nl Vrije Universiteit Amsterdam

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  1. Real-World Distributed Computing with Ibis Henri Balbal@cs.vu.nlVrije Universiteit Amsterdam

  2. Outline • Distributed systems • Distributed applications • The Ibis distributed programming system • Ibis in the mobile networked world

  3. Distributed Systems: 1980s • Networks of Workstations (NOWs) • Collections of Workstations (COWs) • Processor pools (Amoeba) • Condor pools • (Beowulf) clusters

  4. Distributed Systems: 1990s • Metacomputing (Smarr & Catlett, CACM) • Flocking Condor (Epema) • DAS (Distributed ASCI Supercomputer) • Grid Blueprint (Foster & Kesselman) • Desktop grids, SETI@home DAS-3

  5. Distributed Systems: 2000s • Cloud computing • Infrastructure as a service • Virtualization • Mobile computing • Sensor networks • Smart phones • The Networked World

  6. Problem • How to write high-performance applications for real-world distributed systems? • How to integrate many different resources?

  7. Our approach • Study fundamental underlying problems • … hand-in-hand with realistic applications • … integrate solutions in one system: Ibis ! User Distributed Systems

  8. Fundamental problems • Performance – efficiency on wide-area systems • Heterogeneity – different systems & APIs • Malleability – resources come and go • Fault tolerance - crashes • Connectivity – firewalls, NAT, etc.

  9. Applications • Scientific applications • Imaging (VU Medical Center, AMOLF) • Bioinformatics (sequence analysis, cell modeling) • Astronomy (data analysis challenge) • Multimedia content analysis • Games and model checking • Semantic web (distributed reasoning)

  10. Awards Astronomy DACH 2008 – BS DACH 2008 - FT (Cluster/Grid’08) SCALE 2008 (CCGrid’08) ISWC 2008 Multimedia Computing Semantic Web (van Harmelen et al.) AAAI-VC 2007

  11. Multimedia content analysis • Automatically extract information from images & video • Extract feature vectors from images • Describe properties (color, shape) • Data-parallel task on a cluster • Compute on consecutive images • Task-parallelism on a grid

  12. ‘Most Visionary Research’ award at AAAI 2007, (Frank Seinstra et al.) MMCA

  13. Games and Model Checking • Cansolve entire Awari game on wide-area DAS-3 • Needs 10G private optical network (StarPlane) • Distributed model checking has very similar communication pattern • Search huge state spaces, random work distribution, bulk asynchronous transfers • Can efficiently run DeVinE model checker on wide-area DAS-3, use up to 1 TB memory • See IPDPS’09 (May 2009)

  14. Distributed reasoning • MaRVIN (Frank van Harmelen et al, VU): • a distributed platform for massive RDF inferencing (deductive closure) • ``a brain the size of a planet’’ • Uses Ibis to run on heterogeneous systems (clusters, desktop grids) • 3rd prize at Billion Triple trackof Semantic Web Challenge 2008

  15. Grid’5000 European users • D-Grid: Workflow engine for astronomy • U. Erlangen: grid file system • INRIA: ProActive on Ibis RMI • U. Patras: Jylab scientific computing • UPC Barcelona: Grid Superscalar • HITACHI: Peta-scale data management

  16. Outline • Distributed systems • Distributed applications • The Ibis distributed programming system • Ibis in the mobile networked world

  17. Ibis Philosophy • Real-world distributed applications should be developed and compiled on a local workstation, and simply be launched from there

  18. Ibis Approach • Virtual Machines (Java) deal with heterogeneity • Provide range of programming abstractions • Designed for dynamic/faulty environments • Easy deployment through middleware-independent programming interfaces • Modular and flexible: can replace Ibis components by external ones

  19. Ibis Design • Functionality from programming languages • High-Performance Application Programming System • Functionality fromoperating systems • Distributed Application Deployment System

  20. Ibis System

  21. Programming system • Programming models: • Message passing (RMI, MPJ) • Divide-and-conquer (Satin) • Jorus: (multimedia applications) • Dataflow framework (Maestro)  see HPDC09 Sat 14.30 • IPL (Ibis Portability Layer) • Java-centric “run-anywhere” library • Point-to-point, multicast, streaming, …. • Simple model (Join-Elect-Leave ) for tracking resources, supports malleability & fault-tolerance

  22. SmartSockets library • Detects connectivity problems • Tries to solve them automatically • With as little help from the user as possible • Integrates existing and several new solutions • Reverse connection setup, STUN, TCP splicing, SSH tunneling, smart addressing, etc. • Uses network of hubs as a side channel

  23. Example

  24. Example

  25. Deployment system • IbisDeploy GUI • JavaGAT: • Java Grid Application Toolkit • Make applications independent of underlying middleware • Zorilla P2P system • Job management, gossiping,clustering, flood scheduling

  26. JavaGAT Grid Application submitJob(...)‏ File.copy(...)‏ • For simple grid operations there are many ways of implementing them • different middleware available on different sites fork pbs condor unicore globus cp ftp gridftp scp http

  27. JavaGAT Grid Application submitJob(...)‏ File.copy(...)‏ • Which should you use ? • Some may not be available on all sites • Many combinations ? fork pbs condor unicore globus cp ftp gridftp scp http ?

  28. JavaGAT Grid Application submitJob(...)‏ File.copy(...)‏ GAT Remote Files Monitoring Info service Resource Management GAT Engine GridLab Globus Unicore SSH P2P Local gridftp globus

  29. Multimedia Content Analysis Ibis (Java) Client • Runs simultaneously on clusters (DAS-3, Japan, Australia), Desktop Grid, Amazon EC2 Cloud • Connectivity problems solved automatically by Ibis SmartSockets Servers Broker

  30. Connection management Standard sockets: only local VU machines can be reached due to firewalls problems With SmartSockets: run everywhere

  31. Ibis movie (part 1)

  32. Performance on 1 DAS-3 cluster • Relative speedups of Java/Ibis and C++/MPI • Using TCP or Myricom’s MX protocol • Sequential performance Java: 80% of C++

  33. Speedup (wide-area) • Homogeneous wide-area systems (DAS-3): • Frame rate increases linearly with #clusters • World-wide experiment: • 24 frames per second • Speed limited by camera,not computing infrastructure

  34. Outline • Distributed systems • Distributed applications • The Ibis distributed programming system • Ibis in the mobile networked world

  35. Smart Phones • GSM + PC + GPS + camera + networks + …. • Location-aware • What if everyone always carries a smart phone (like a GSM now)? • Next wave in computing?

  36. Ibis on Smart Phones • Our focus: distributed smart phone applications • Applications running on multiple phones • Integration with distributed computing backbone • Use Android for development • Google’s open-source platform • Java-based

  37. Distributed applications • Disaster management (Katrina) • Use ad-hoc Wifi network when GSM network fails • Finding nearby people with certain skills • Bus drivers, CPR • Distributed decision support • Moving people to shelters (logistics) • Social networks • Similar issues • Find nearby friends, decide on restaurant

  38. Yes, on 23 Oct 2010, 3.48 pm atN 52°22.688´ E 004°53.990´ Haven’t we met before? Wild example • Track position => automatic diary of your life • Cross-comparisons between diaries

  39. eyeDentify • Object recognition on a G1 smartphone • Smartphone is a limited device: • Can run only 64 x 48 pixels (memory bound) • 1024 x 768 pixels would take 5 minutes • Distributed Ibis version: = + + 2.0 seconds 1024 x 768 pixels

  40. Ibis movie (part 2)

  41. Interdroid Novel Mobile Distributed Applications Data Management Context Sensitive Programming Models Distributed Communication

  42. Current work • Raven: API for Viable Episodic Networking • Decentralized synchronization API • Fine grained control over data sharing • Bluetooth support for ad-hoc communication • Discovery of devices using multiple networks • Context Aware Programming Models • Supporting distributed decision making • Representing and using context (location etc.) • Exploiting social relationships (Hyves, Facebook)

  43. Summary • Ibis provides integrated solutions for many hard problems • performance, heterogeneity, malleability, fault tolerance, connectivity • It combines functionality from programming languages and operating systems • Used for many applications on real-world distributed systems • Download from http://www.cs.vu.nl/ibis/

  44. Acknowledgements Niels Drost Ceriel Jacobs Roelof Kemp Timo van Kessel Thilo Kielmann Jason Maassen Rob van Nieuwpoort Nick Palmer Kees van Reeuwijk Frank J. Seinstra Kees Verstoep Gosia Wrzesinska

  45. Questions?

  46. DAS-3

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