Transcript siam_10
Exa-Scale Volunteer Computing
David P. Anderson
Space Sciences Laboratory
U.C. Berkeley
The potential of volunteer computing
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The volunteer resource pool
Current PetaFLOPS breakdown:
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Potential: ExaFLOPS by 2010
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4M GPUs * 1 TFLOPS * 0.25 availability
Why did F@h and S@h work?
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Technology-savvy leaders
Technical resources
Funding
So they were able to develop their own software
stack. But few research groups can do this.
BOINC
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Middleware for volunteer computing
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client, server, web
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Based at UC Berkeley Space Sciences Lab
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Open source (LGPL)
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NSF-funded since 2002
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http://boinc.berkeley.edu
BOINC: volunteers and projects
projects
volunteers
LHC@home
CPDN
attachments
WCG
The Utopian vision
resources
Scientific
research
The public
education/outreach
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Better research gets more computing power
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An enlightened public decides what’s better
Science areas using BOINC
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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
Climateprediction.net
Einstein@home
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Gravitational waves; gravitational pulsars
Milkyway@home
GPUGRID.net
AQUA@home
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D-Wave Systems
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Simulation of “adiabatic quantum algorithms”
for binary quadratic optimization
Quake Catcher Network
Success: modest at best
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Only ~25 significant projects, few new ones
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Why?
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Even with BOINC, it’s hard to operate a
volunteer computing project
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Volunteer computing ignored by the HPC world
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It doesn’t provide ownership or control
Umbrella projects
Project
publicity
web development
sysadmin
app porting
Example: IBM World Community Grid
The Berkeley@home model
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A university has
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scientists
a powerful “brand”
PR resources
IT infrastructure
lots of alumni (UCB: 500,000)
Hubs
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nanoHUB: “science portal” for nanoscience
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social network + “app store”
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sharing of ideas, data, software
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computational portal
HUBzero: generalization to other areas
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currently ~20 hubs
Integration of BOINC with HUBzero
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each hub has a volunteer computing project
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use VMs to deal with security, heterogeneity
issues
Conclusion
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Volunteer computing + GPUs = Exa-scale
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How to increase adoption?
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Organizational level matters
email me: [email protected]