1. The Ibis Project: Simplifying Grid Programming & Deployment Henri Bal bal@cs.vu.nl Vrije Universiteit Amsterdam

2. The ‘Promise of the Grid’ Efficient and transparent (i.e. easy-to-use) wall-socket computing over a distributed set of resources [Sunderam ICCS’2004, based on Foster/Kesselman]

3. ● Performance & scalability ● Heterogeneous ● Low-level & changing programming interfaces ● writing & deploying grid applications is hard Reality: ‘Problems of the Grid’ ● Connectivity issues ● Fault tolerance ● Malleability Wide-Area Grid SystemsUser !

4. The Ibis Project ● Goal: ● drastically simplify grid programming/deployment ● write and go!

5. Approach ● Minimal assumptions about execution environment ● Virtual Machines (Java) deal with heterogeneity ● Use middleware-independent APIs ● Different programming abstractions ● Designed for dynamic/hostile grid environments ● Modular and flexible: can replace Ibis components by external ones

6. Global picture

7. Grid programming ● Programming models: ● Low-level message passing (RMI, MPJ) ● High-level divide-and-conquer (Satin) ● IPL (Ibis Portability Layer) ● Java-centric “run-anywhere” library, sent with application ● Can handle fault-tolerance, malleability ● SmartSockets ● Solve connectivity problems automatically (firewalls, NAT, addressing problems)

8. Grid deployment ● Zorilla P2P system ● Jobs management, gossiping, clustering, flood scheduling ● JavaGAT: Java Grid Application Toolkit ● Make applications independent of underlying grid ● Used for file copying, resource discovery, job submission & monitoring, user authentication ● API is currently standardized (SAGA)

9. Java GAT GAT Engine Remote Files Monitoring Info service Resource Management GridLabGlobusUnicoreSSHP2PLocal GAT Grid Application File.copy(...)‏ submitJob(...)‏ gridftp globus Intelligent dispatching [van Nieuwpoort et al., SC’07 ]

10. Ibis applications ● e-Science (VL-e) ● Brain MEG-imaging ● Mass spectroscopy ● Multimedia content analysis, video processing ● Various parallel applications ● SAT-solver ● N-body ● Grammar learning ● …

11. European users ● D-Grid: Workflow engine for astronomy ● U. Erlangen: grid file system ● INRIA: ProActive on Ibis RMI ● U. Patras: Jylab scientific computing system ● HITACHI: Peta-scale data management

12. DAS-3DAS-3 272 nodes (AMD Opterons) 792 cores 1TB memory LAN: Myrinet 10G Gigabit Ethernet WAN (StarPlane): 20-40 Gb/s OPN See CCGrid’08 session 11 (Verstoep)

13. Gene sequence comparison in Satin (on DAS-3) Speedup on 1 cluster Run times on 5 clusters Divide&conquer scales much better than master-worker 78% efficiency on 5 clusters (with 1462 WAN-msgs/sec)

14. Multimedia content analysis ● Analyzes video streams to recognize objects ● Extract feature vectors from images ● Describe properties (color, shape) ● Data-parallel task implemented with C++/MPI ● Compute on consecutive images ● Task-parallelism on a grid See CCGrid’08 SCALE challenge & sessions 12+16

15. High Resolution Video Processing ● Realtime processing of CineGrid movie data ● 3840x2160 (4xHD) @ 30 fps = 1424 MB/sec ● Multi-cluster processing pipeline ● Using DAS-3, StarPlane and Ibis

16. Summary ● Goal: Simplify grid programming/deployment ● Key ideas in Ibis ● Virtual machines (JVM) deal with heterogeneity ● High-level programming abstractions (Satin) ● Handle fault-tolerance, malleability, connectivity problems automatically (Satin, SmartSockets) ● Middleware-independent APIs (JavaGAT) ● Modular

17. Acknowledgements Current members Rob van Nieuwpoort Jason Maassen Thilo Kielmann Frank Seinstra Niels Drost Ceriel Jacobs Kees Verstoep Roelof Kemp Kees van Reeuwijk Past members John Romein Gosia Wrzesinska Rutger Hofman Maik Nijhuis Olivier Aumage Fabrice Huet Alexandre Denis

18. More information ● Ibis can be downloaded from ● http://www.cs.vu.nl/ibis http://www.cs.vu.nl/ibis ● Papers: ● Satin [PPoPP’07], SmartSockets [HPDC’07], Gossiping [HPDC’07], JavaGAT [SC’07], MMCA [IEEE Multimedia’07] Ibis tutorials CCGrid’08