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BOINC: Progress and Plans
David P. Anderson
Space Sciences LabUniversity of California, Berkeley
BOINC:FASTAugust 2013
Computing resources
PCslaptops
mobile devicesappliances
Consumer
desktop data center
Organizational
volunteer computing
desktopgridcomputing
cluster,cloud,Grid,supercomputing
BOINC
Why volunteer computing?
Consumer > 1 billion PCs
most w/GPU > 2 billion mobile devices Low cost to scientists
Organizational ~10 million
cluster/cloud nodes High cost
Volunteer computing status
Volunteers: 400K people, 600K computers > 15 PetaFLOPS, many million jobs/day > 50 science projects, e.g.
IBM World Community Grid CERN@home Einstein@home Climateprediction.net Folding@home
Capacity in 5 years
Participation: 50M devices? Processing
CPU: 50M * 1 TFLOPS = 50 ExaFLOPS GPU: 50M * 20 TFLOPS = 1000 ExaFLOPS
Storage: 50M * 10 TB = 500 ExaBytes
Network bandwidth 50M * 100Mbps = 5 Petabit/sec
My talk
VM-based applications Remote job submission BOINC on Android Volunteer storage
Using VM technology
Consumer platforms: 85% Windows 7% Linux 7% Mac OS X
Developing/maintaining versions for different platforms is hard
Even making a portable Linux executable is hard
BOINC VM-based applications
You supply: A VM image for your favorite environment
can use the same one for many apps An executable for that environment An XML configuration file
BOINC supplies: The VBox Wrapper
How it works on the client
BOINCclient
VirtualBoxexecutive
Vboxwrapper
VM instanceshared directory:executableinput, output files
VirtualBox “snapshots” provide checkpointing
Remote job submission
scienceportalor PC
BOINCserver
Scientists(users)
sysadmins
job submission
file management
Managing multiple users
User access control User quotas Sharing limited processing resources
handle small batches first don’t starve large batches enforce user quotas long-term
BOINC on Android
Available in Google, Amazon app stores 7 projects have Android/ARM apps Battery, WiFi considerations
GUI(Java)
BOINCclient
(native)
RPCapps
(native)
BOINC storage architecture
Data archivalApplications
Locality scheduling
Dataset storage
BOINC storageinfrastructure
Result archival
Storage-related features
Client: allocating space among projects Client: support for large (multi-GB) files
efficient transfer, verification, copying Scheduler: storage policy plug-ins Example: volunteer data archival
multi-level erasure coding
Research opportunities
Many job scheduling issues Big-data issues Simulation tools
client emulator server emulator (Simba) storage emulator
