1. Exa-Scale Volunteer Computing David P. Anderson Space Sciences Laboratory U.C. Berkeley

2. Outline Volunteer computing BOINC Applications Research directions

3. High-throughput computing High-performance computing program runs too slow on PC cluster (MPI) supercomputer cluster (batch) Grid Commercial cloud Volunteer computing single job # processors multiple jobs 10K-1M 1000 100 1

4. Volunteer computing Early projects – 1997: GIMPS, distributed.net – 1999: SETI@home, Folding@home Today – ~50 projects – 500K volunteers – 1M computers, 2.4M cores – 10 PetaFLOPS

5. The potential of volunteer computing The volunteer resource pool Current PetaFLOPS breakdown: Potential: ExaFLOPS by 2010 – 4M GPUs * 1 TFLOPS * 0.25 availability

6. BOINC Middleware for volunteer computing – client, server, web Based at UC Berkeley Space Sciences Lab Open source (LGPL) NSF-funded since 2002 http://boinc.berkeley.edu

7. BOINC: volunteers and projects volunteers projects CPDN LHC@home WCG attachments

8. The Utopian vision Better research gets more computing power An enlightened public decides what’s better Scientific research The public resources education/outreach

9. Science areas using BOINC Biology – protein study, genetic analysis Medicine – drug discovery, epidemiology Physics – LHC, nanotechnology, quantum computing Astronomy – data analysis, cosmology, galactic modeling Environment – climate modeling, ecosystem simulation Math Graphics rendering

10. Application types Computing-intensive analysis of large data Physical simulations Genetic algorithms – GA-based optimization

11. Climateprediction.net

12. Einstein@home Gravitational waves; gravitational pulsars

13. SETI@home

14. Milkyway@home

15. GPUGRID.net

16. AQUA@home D-Wave Systems Simulation of “adiabatic quantum algorithms” for binary quadratic optimization

17. Quake Catcher Network

18. Account managers

19. BOINC software overview client apps screensaver GUI scheduler MySQL data server daemons volunteer host project server HTTP

20. Client: job scheduling Queue multiple jobs – avoid starvation – minimize communication – variety Job scheduling – Round-robin time-slicing – Earliest deadline first

21. Client: work fetch policy When? From which project? How much? Goals – maintain enough work – minimize scheduler requests – honor resource shares per-project “debt” CPU 0 CPU 3 CPU 2 CPU 1 max min

22. BOINC scheduler applications Win32 + NVIDIA Win64 Mac OS X app versions jobs instances Win32 N-core Win32 - HW, SW description - existing workload - per resource type: # of instances requested # of seconds requested - app version descriptions - job descriptions

23. Anonymous platform mechanism Volunteer supplies app versions. – security – optimization – unsupported platforms

24. Umbrella projects Example: IBM World Community Grid Project publicity web development sysadmin app porting

25. The Berkeley@home model A university has – scientists – a powerful “brand” – PR resources – IT infrastructure – lots of alumni (UCB: 500,000)

26. Hubs nanoHUB: “science portal” for nanoscience – social network + “app store” – sharing of ideas, data, software – computational portal HUBzero: generalization to other areas – currently ~20 hubs Integration of BOINC with HUBzero – each hub has a volunteer computing project

27. Volunteer computing research Host characterization Simulation-based performance study MPI-type apps Apps in VMs Data-intensive computing Volunteer motivation

28. Conclusion Volunteer computing: Exa-scale potential – GPUs are crucial BOINC: enabling technology Bottlenecks – the culture of scientific computing – organizational models