1. David P. Anderson Space Sciences Laboratory University of California – Berkeley davea@ssl.berkeley.edu Designing Middleware for Volunteer Computing

2. Why volunteer computing? ● 2006: 1 billion PCs, 55% privately owned ● If 100M people participate: – 100 PetaFLOPs, 1 Exabyte (10^18) storage ● Consumer products drive technology – GPUs (NVIDIA, Sony Cell) your computers academic business home PCs

3. Volunteer computing history 95 96 97 98 99 00 01 02 03 04 05 06 GIMPS, distributed.net SETI@home, folding@home commercial projects climateprediction.net BOINC Einstein@home Rosetta@home Predictor@home LHC@home BURP PrimeGrid...

4. Scientific computing paradigms Grid computing Supercomputers Volunteer computing Cluster computing ControlBang/buck least most

5. BOINC SETIphysics Climate biomedical Joe Alice Jens volunteers projects

6. Participation in >1 project ● Better short-term resource utilization – communicate/compute in parallel – match applications to resources ● Better long-term resource utilization – project A works while project B thinks project computing needs think work think work time

7. Server performance How many clients can a project support?

8. Task server architecture MySQL TransitionerScheduler Feeder File deleter DB purger Assimilator Validator Work creator Shared mem clients

9. Server load (CPU)

10. Server load (disk I/O)

11. Server limits ● Single server (2X Xeon, 100 Mbps disk) – 8.8 million tasks/day – 4.4 PetaFLOPS (if 12 hrs on 1 GFLOPS CPU) – CPU is bottleneck (2.5% disk utilization) – 8.2 Mbps network (if 10K request/reply) ● Multiple servers (1 MySQL, 2 for others) – 23.6 million tasks/day – MySQL CPU is bottleneck – 21.9 Mbps network

12. Credit

13. Credit display

14. Credit system goals ● Retain participants – fair between users, across projects – understandable – cheat-resistant ● Maximize utility to projects – hardware upgrades – assignment of projects to computers

15. Credit system ● Computation credit – benchmark-based – application benchmarks – application operation counting – cheat-resistance: redundancy ● Other resources – network, disk storage, RAM ● Other behaviors – recruitment – other participation

17. Benchmarks not whole story

18. Limits of Volunteer Computing ● How much processing/disk/RAM is out there? ● Combinations of resources ● Data from 330,000 SETI@home participants

24. Goals of BOINC ● > 100 projects, some churn ● Handle big data better – BitTorrent integration – Use GPUs and other resources – DAGs ● Participation – 10-100 million – multiple projects per participant