BOINC: A System for Public-Resource Computing and Storage

1. BOINC:A System for Public-Resource Computing and Storage David P. Anderson University of California, Berkeley

2. Paper overview • Defines public-resource computing • Introduces the BOINC platform • Lists public-resource computing projects using the BOINC platform • Discusses BOINC implementation

3. Public-resource computing • AKA global computing or P2P computing • Combines the resources of personal computers and game consoles belonging to the general public to perform scientific computations • Started with • Great Internet Mersenne Prime Search (GIMPS) (1996) • Distributed.net (1997)

4. Contrast with grid computing • Grid computing involves "organizationally-owned resources" • Centrally managed by IT professionals • Powered on most of the time • Connected by high-speed links • Malicious behavior handled by organization • None of that is true for public-resource computing.

5. Specific requirements ofpublic-computing systems • Redundant computing • Against result falsification/fabrication • Cheat-resistant accounting • Support for user-configurable application graphics

6. BOINC • Berkeley Open Infrastructure for Network Computing • Developed at UCB Space Science Laboratory by the SETI@home group • SETI@home started in 1999 and still runs today

7. Goals of BOINC (I) • Reduce the barriers of entry to public-resource computing: • A project can be run from a single computer running standard open-source software • Share resources among autonomous projects: • Each PC owner can join multiple projects • Results in better resource utilization

8. Goals of BOINC (II) • Support diverse applications: • Offer various data distribution mechanisms • Support various programming languages • … • Reward participants: • Mostly by giving them credits • System must be cheating-resistant • Also by offering nice graphics • Great screensavers!

9. Projects using BOINC (I) • SETIi@home:search for intelligent extra-terrestrial life • Predictor@home:protein behavior • Folding@home:protein folding, misfolding, aggregation and related diseases • Climateprediction.net:long term-climate prediction

10. Projects using BOINC (II) • Climate@home.net:long term-climate prediction • CERN projects:were to use in-house PCs • Einstein@home:gravitational waves • UCB/Intel study of Internet resources

11. BOINC overview (I) • Projects: • Have a single master URL • Can involve one or more applications • They may change over time • Server complex of a BOINC project • Centered around a relational database containing most project data • Scheduling server daemons handles RPC from by clients • Data server daemons manage uploads

12. BOINC overview (II) • BOINC offers tools for • Creating, starting, stopping and querying projects • Adding new applications, new platforms, … • Creating workunits • Monitoring server performance • Conceived to be used by scientists, not IT professionals

13. BOINC overview (III) • Participants join by registering with web site of project and downloading the BOINC client • Client can run as • Screensaver (with fancy graphics) • Window service (running in the background) • Application (displaying results in tabular form)

14. Describing computations and data • Applications: • Can have different versions for different participant platforms • Consist of one or more files • Workunits: • Represent inputs to a computation • Include parameters specifying computational step requirements • Results (obvious)

15. More details • Files associated with • Application versions • Workunits • Results are immutable • Files have numerous BOINC-specific attributes

16. Client/scheduler interactions • When a client interacts with a scheduling server, it • Reports completed work • Gets a collection of workunits

17. Redundant computing (I) • BOING supports redundant computing • Projects can specify each workunit should be executed N times • If M  N executions agree on a particular result, it becomes canonical

18. Redundant computing (II) • Issues: • Must prevent cheaters to create quorums of fabricated results • Each user can provide at most one result for each workunit • Must distinguish between erroneous results and mere numerical variations • Homogeneous redundancy:Same workunit only sent to clients with identical platforms

19. Failure and backoff • Must prevent server overload after a failure • Everyone wants to reconnect • All client/server communication uses exponential backoff after a failure • Preents avalanches of requests

20. Participant preferences • User general preferences let users specify numerous parameters • Including transfer limits (for participants having monthly transfer limits) and CPU duty cycles (for participants having overclocked CPUs)

21. Credit and accounting • To reward participants

22. User community features • To motivate participant emulation

23. Platform diversity issues • Maintains multiple versions of application executables • Participants may also request to recompile applications before running them • Anonymous platform mechanism • Useful for • Non standard platforms • Paranoiac participants

24. Graphics and screensavers • Client software appears monolithic to BOINC participants but comprises four components: • Core client: does the work • Client GUI: provides a user-interface showing computation progress and letting participants quit and join projects • API: report CPU usage and fraction done, handle requests to provide graphics, … • Screensaver

25. Local scheduling • Decides which projects to run • Goals include • Maximizing resource usage • Meeting result deadlines; • Respecting resource share allocation among projects of each participant • Ensuring some ”variety” among projects • Participants want to see progress in all the projects they have joined

26. Conclusions • It works • More work still needs to be done

27. If you want to hear more • David Anderson speaks about SETI@home and BOINC http://www.youtube.com/watch?v=8iSRLIK-x6A