UOA11-05: Boinc – Volunteer Computing
Submitting InstitutionUniversity of Oxford
Unit of AssessmentComputer Science and Informatics
Summary Impact TypeTechnological
Research Subject Area(s)
Information and Computing Sciences: Computation Theory and Mathematics, Computer Software, Information Systems
Summary of the impact
Research in the UoA has underpinned the development of the current
version of BOINC (Berkeley Open Infrastructure for Network Computing), a
technology to enable secure volunteer computing. The research was done as
part of the climateprediction.net project that is currently managed as
CPDN through the UoA, supporting international climate modelling. CPDN
models climate change using donated cycles on users' computers, with
almost 700,000 users registered by 2013. Significant work to develop BOINC
in CPDN has enabled the public to engage with science more easily and
conveniently. BOINC has become recognised as the key open-source tool for
volunteer computing and is also available to companies to create their own
grid networks. It has been used for a range of applications from driving
experiments to find the Higgs particle to using home PCs to detect
The initial launch of climateprediction.net used SETI@HOME, an early
implementation of the BOINC base platform, and highlighted a series of
deficiencies with this technology. A concern from users of volunteer
computing was security and assurance that their home PC would not be
affected by having others run simulations on their machines. This
potential vulnerability was highlighted in a paper by Oxford computer
scientists in 2004 . It was therefore imperative that BOINC was
enhanced to ensure that assurances could be provided, or the concept of
volunteer computing would not succeed. Deficiencies were also highlighted
in the effectiveness of communication techniques between the individual
simulation cycles and the controlling system to ensure dynamic evolution
of the simulations. Details were highlighted in a paper focusing on the
challenges of volunteer computing with lengthy simulations , as well as
the design of an infrastructure for distributed servers to manage the data
communication . The former paper presented various issues with running
lengthy work-units and large, complex applications in volunteer computing.
It discussed the challenges to be overcome in constructing the
climateprediction.net project, in terms of: porting the scientific models;
ensuring the model produces checkpoints; the breaking up of the models
into smaller, more manageable chunks; creating the infrastructure and
building; and retaining the user community.
Oxford University staff were involved in the CPDN project from both an
Atmospheric Physics perspective for the model development and a Computer
Science perspective for the work on BOINC, with the latter team comprising
Andrew Martin, Andrew Simpson, Carl Christiansen and Tolu Aina from the
UoA. Christiansen oversaw the major redevelopment of BOINC; Aina left the
UoA in 2010 and is now the BOINC chief developer. Drs Martin and Simpson
are academic staff in the UoA whose expertise lies in distributed
computing and security.
The major CPDN contributions to BOINC have been:
- Integration of the LibCurl HTTP library. This library is used for the
transferring of files via HTTP to and from the project servers, and as
such is fundamental to BOINC as a distributed computing project. It was a
huge task to integrate this into BOINC, and all current projects using
- Support for 3-D fonts in OpenGL.This is used by almost all projects
that offer graphics and have 3D visual models running on users' machines.
- Adapting zip/unzip libraries to BOINC. Many projects use zip/unzip to
handle large numbers of files more efficiently and enhance data
communication. The files that are distributed to participants are in a
zipped form, which reduces both the total size of the data held by the
project and the volume of data transferred to the participants. The
zip/unzip libraries enable the files to be automatically handled on the
participant's side both prior to the start of the computational model, and
whilst uploading the results to the project servers. Many projects use
this feature to handle the large numbers of files commonly produced in a
BOINC project more efficiently and to enhance their data communications.
The UoA and their collaborators also worked on the porting of the
scientific codes as the original codes were meant to be run on clusters or
large infrastructures, not single processors. This involved taking code
developed by physicists over many years in, typically, a million lines of
Fortran code, and rewriting or modifying it to run across multiple
platforms for individual processors. Whilst BOINC is a community developed
open-source tool to date, the early work for CPDN was instrumental in its
transformation into the widely used tool that it is today. In particular,
by developing the security aspects of this platform, it has been able to
offer the security assurances required by the users.
References to the research
* David Stainforth, Andrew Martin, Andrew Simpson, Carl Christensen,
Jamie Kettleborough, Tolu Aina, and Myles Allen. Security Principles for
Public-Resource Modeling Research, Proceedings of the 13th IEEE Conference
on Enabling Grid Technologies (ENTGRID), Modena, Italy, June 2004.
In this paper, the crucial steps taken in the climateprediction.net
project to address the security concerns inherent in the design of a
volunteer computing project are described.
* Carl Christensen, Tolu Aina, David Stainforth. The Challenge of
Volunteer Computing With Lengthy Climate Modelling Simulations,
Proceedings of the 1st IEEE Conference on e-Science and Grid Computing,
Melbourne, Australia, 5-8 Dec 2005.
This paper presents various issues with running lengthy workunits and
large, complex applications in volunteer computing.
* N. Massey, T. Aina, M. Allen, C. Christensen, D. Frame, D. Goodman,
J. Kettleborough, A. Martin, S. Pascoe and D. Stainforth. Data access
and analysis with distributed federated data servers in
climateprediction.net , Advances in Geosciences, 8, p49-56, 2006.
This paper discusses the project data handling in terms of the
distribution of computational work, the collection and storage of the
results, and the subsequent analysis.
Details of the impact
The primary impact is that the UoA's underpinning research enabled large-scale
public engagement with science by improving the security and
usability of BOINC: allowing users to be confident of BOINC's ability to
harvest compute cycles without compromising the security of their PCs, and
making modellers able to develop more complex codes to run out in the
community and return timely results. It enabled the public to engage in
science in a way that had not been achieved before with thousands of users
observing a changing globe graphic on their machines, showing the results
of their own models running on behalf of the climate scientists [A]. CPDN
was, and still is, producing climate modelling results which are used by
the Met Office.
BOINC [B] is managed as a community developed open-source tool from
Berkeley University. The UoA's contribution is acknowledged by the current
head of this group [C]. BOINC is now widely used by scientific communities
across the world. According to www.boincstats.com,
2,599,338 volunteers have installed the BOINC software on their machines
and there are currently 272,459 active users.
The global reach of the CPDN project using BOINC is significant. CPDN has
20,000 active users contribute approximately 27,000 active hosts, with a
combined power of 35 TFlops. Of the 82 BOINC projects, in May 2012
climateprediction.net was the 4th most popular by work-units in progress
and 5th in attracting new users [B]. Over 129 million simulation-years
have been performed since the project's inception and registered users are
located in 221 countries. Although the project has been running since
September 2003, 9 of the 10 busiest days have been since January 2008, and
currently around 30-40 new users join each day. Since 2008, over 100,000
users have joined and over 60% of the total computational cycles in the
project have been donated [A]; 40,702 distinct individual users have
successfully completed one or more model simulations. The computing time
required for all the model simulations run successfully since 2008 is
equivalent to a 32,220 core machine running full time for one year and
producing 100% successful results. An estimate of the value of this CPU
time is $22.5M, based on the rate of the Amazon Elastic Compute Cloud
Standard Spot instance ($0.08/hour default).
The following quote [C] from David Anderson, Director of the BOINC
Project, indicates his belief in the impact of CPDN:
`I'd like to congratulate and thank all the people at Oxford who made
it happen, and all the volunteers who courageously ran huge climate
models on their PCs. CPDN has been a huge success. There's no more
worthwhile scientific goal than investigating the fate of Earth, and
CPDN has made critical contributions to this investigation. CPDN
inspired BOINC; when I read Myles Allen's original (1999) paper it got
me very excited, and I immediately contacted him, wanting to get
involved. CPDN's unique requirements had a big impact on BOINC's design.
Carl Christensen, who for several years did the heavy lifting of getting
CPDN working and keeping [it] going, has also contributed greatly to
BOINC, and more recently so has Tolu Aina. I'm extremely proud to have
worked with these guys and the rest of the CPDN group. Congratulations
BOINC has enabled industry to utilise a technology to create huge
computing resources (exemplified by the World Community Grid) without the
high cost of procuring conventional supercomputing facilities. It has also
enabled the public to play a crucial role in solving challenging
scientific problems by allowing them to sign up as volunteers to run
models on their machines with results often viewable through graphical
interfaces and by joining communities of volunteers through the use of
portals and websites. The BOINC website details uses of the technology for
an international array of projects, of which the following are examples:
GPUgrid.net is a distributed computing infrastructure devoted to
biomedical research. Thanks to the contribution of volunteers, GPUGRID
scientists can perform molecular simulations to understand the function of
proteins in health and disease. In 2012, a team of scientists using
GPUGRID announced that they had made crucial steps in simulating the AIDS
virus maturation for the first time. Using computational techniques,
researchers have shown how a protein responsible for the maturation of the
virus releases itself to initiate infection. This event is at the root of
the whole maturation process and if HIV protease can be stopped while it
is still becoming mature, then the virus particle as a whole cannot become
mature. Accessing the nascent structures of HIV protease provides a novel
and critical target for the development of ARVs in the fight against
HIV/AIDS [F]. GPUGrid currently has 1,994 active users with BOINC
installed on their machines providing compute cycles to simulate cancer,
AIDS and neural disorders.
LHC@home is a platform for volunteers to help physicists develop
and exploit particle accelerators such as CERN's Large Hadron Collider,
and to compare theory with experiment in the search for new fundamental
particles. By contributing spare processing capacity on their home and
laptop computers, volunteers may run simulations of beam dynamics and
particle collisions in the LHC's giant detectors [D]. This project
currently has 13,794 active users with BOINC installed on their machines
providing compute cycles.
The Quake Catcher Network (QCN) is a project that uses
Internet-connected computers to do research and outreach in seismology.
Users can participate by downloading and running a simulation program on
their computers, and this project currently has 1,199 active users with
BOINC installed on their machines providing compute cycles [D]. Laptops
connect to the QCN over the Internet. The laptop monitors the data locally
for new high-energy signals and only sends a single time and a single
significance measurement for strong new signals. If the QCN server
receives a series of these times and significance measurements all at
once, then it is likely that an earthquake is happening. The website for
this project shows the location and triggered results from seismic
activity, including recent activity on the west coast of America. This
real time monitoring of activity using PCs as the base for detecting
movement enables the public to be engaged in the detection of earthquakes
[G]. A version of QCN is currently being used in Taiwan to enable them to
benefit from volunteer computing to detect seismic activity as
conventional earthquake monitoring techniques are known to be expensive.
Rosetta@home determines the 3-dimensional shapes of proteins in
research that may ultimately lead to finding cures for some major human
diseases. By running the Rosetta program on home computers, it speeds up
and extends the research in ways that wouldn't be possible otherwise. It
is also used to design new proteins to fight diseases such as HIV,
Malaria, Cancer, and Alzheimer's. This project currently has 27,471 active
users with BOINC installed on their machines providing compute cycles. The
findings allow the Rosetta lab, run by David Baker at the University of
Washington, to design proteins that do not exist in nature. Some new
proteins could deactivate viruses such as the flu—as Dr. Baker's lab is
trying to do for this year's H1N1 strain—by attaching to and smothering
the sections of the pathogens that harm human cells. Dr. Baker has stated
that the project's biggest recent breakthroughs have been in creating
catalysts, which selectively speed up chemical reactions and which
regulate almost every biological process. One catalyst in development, for
instance, is an enzyme that could slice apart genes in female mosquitoes,
potentially preventing malaria transmission without using toxic chemicals.
It is estimated that the total CPU time donated to run models using BOINC
is 1,016,099,474,571 seconds. This is equal to 32,220 years of CPU time
(equivalent to running a 32,220 core machine full-time for one year). The
examples above are indicative of how BOINC and `citizen science' have
enabled the public to engage with science and to assist with the
scientific breakthroughs achievable by using knowledge and modelling to
drive experimental activity, thus reducing experimental costs.
Such is the definition of REF impact that while some of the scientific
results of BOINC projects are admissible, such as the contribution of CPDN
to the global warming debate, others might be classed as being purely of
academic interest. It is, however, clear that public engagement with
science, the thing most directly enabled by the UoA's research, is
covered by the definition.
Sources to corroborate the impact
[A] Website for the Climate Prediction project:http://www.climateprediction.net.
[B] Website detailing uses and publications for BOINC:
[C] Email from David Anderson (February 2013) stating the three main
contributions by the Oxford CPDN team, held on file.
[D] Lopez-Perez, Juan Antonio. Distributed computing and farm management
with application to the search for heavy gauge bosons using the ATLAS
experiment at the LHC. PhD thesis, January 2008.
Provides details of the results from using volunteer computing for the
[E] Cochran, E.S., J.F. Lawrence, C. Christensen, and R. Jakka, The
Quake-Catcher Network: Citizen science expanding seismic horizons, Seismological
Research Letters, 80, 26-30, 2009.
Provides details of results from using volunteer computing for the
quake catcher activity.
[F] S. K. Sadiq, F. Noé, and G. De Fabritiis, Kinetic characterization of
the critical step in HIV-1 protease maturation, PNAS, published online
November 26, 2012.
This publication describes the work using BOINC on HIV research.
[G] The Quakecatcher website shows results from the remote sensors
installed on users machines: http://qcn.stanford.edu/qcn-map.