“Our raw data sets generate about 1,000 individual data sets, and each of those processes requires about 12 hours of computer processing,” says Jim Cordes, professor of Astronomy at Cornell and a developer of the project. “Five minutes of data takes about 10,000 hours of computing time to process. No typical university computer center can analyze that data to search for these kinds of objects.”

But it can be done via the 1 million host computers now participating in the project via the BOINC (Berkeley Open Infrastructure for Network Computing; boinc.berkeley.edu) platform, which was a by-product of the SETI@Home project. Aside from Folding@Home, which has its own distributed computing platform, most academic projects now use the BOINC system to let your desktop CPU and GPU share cycles with an ongoing project.

For Cordes, BOINC lets him send a small batch of observatory data to a single computer. “[The receiving computer] churns away at [the data] for hours or a day and sends it back.” And there is no dearth of jobs to send. Einstein@Home currently has 200TB of raw observatory data and plans to grow that to 1 petabyte. The project has already confirmed and discovered pulsars.

“Volunteer computing provides me with cheap access to a lot of computers,” says Michela Taufer. “I can compute as much as I need.” Taufer, an assistant professor at University of Delaware’s Department of Computer and Information Sciences, directs the Docking@Home project, which is testing new drug concepts by simulating how small molecules “dock” with proteins. This requires simulating hundreds of thousands of potential models. For a junior faculty member, acquiring an institution’s own computing time requires lengthy applications and only small windows of actual usage on the college supercomputer. But by deploying BOINC, she has 13,000 volunteers for Docking@Home dedicating 26,000 computers to the task.

“It is very tough to get all of this computation done easily,” she says. The emergence of a free and user-friendly system such as BOINC has not only opened up new levels of computing power but also helped to fuel innovation. “Volunteer computing provides me with cheap access to a lot of computers, so I can compute as much as I need.”

People Power

The distributed computing concept has expanded in recent years to engage more than just computer cycles. Now, some researchers are using humans themselves for distributed tasks. In 2001, NASA initiated a “Clickworkers” project that had volunteers visually scan hi-res images of Mars to map craters. In late 2009, the space agency joined with Microsoft to launch the Be A Martian! online project (beamartian.jpl.nasa.gov/welcome) that turns Mars mapping into a game. The model resembles the Galaxy Zoo (galaxyzoo.org) project in the UK, where more than 150,000 people help review telescope images of the cosmos and classify the galaxies by their shape and features.

“People are computers, too,” says Landon Curt Noll, cryptologist and security architect at Cisco Systems and a member of the Electronic Frontier Foundation’s Cooperative Computing Award team. “That kind of hybrid approach is exciting. Astronomy has a massive amount of data just waiting for someone to analyze. You don’t need to build an artificial intelligence engine, but you can take advantage of people volunteering time and using back-end computing to make sense of the research.”

One hybrid project that is contributing to our understanding of very down-to-earth events is the Quake-Catcher Network (qcn.stanford.edu/), which uses BOINC coupled with motion sensors to record earthquake activity. (See sidebar.) “We have over 1,000 sensors in any given week that are sending us data back,” says Elizabeth Cochran, assistant professor at the University of California, Riverdale. Using motion detectors both in and attached to PCs clustered in California and Europe, the network of volunteers has gathered data on seismic events.

“We have a number of records from the recent magnitude 6.5 in northern California,” she says. A number of Quake-Catcher sensors at Stanford picked up another lower-level magnitude 4. “The value comes in getting a high density of sensors in places like Los Angeles and California.”

Distributing Science

As many distributed computing project leaders have discovered over the years, however, engaging people power of any sort requires more community outreach and communications skills than many academics are prepared for. These programs succeed not merely because projects such as quake catching or galaxy mapping are cool.

“[Success] is a combination of user interest, funding, and the ability to communicate with volunteers,” says Rom Walton, computer programmer/analyst at the University of California, Berkeley’s Space Sciences Laboratory and one of three full-time programmers of the BOINC infrastructure. “If a project is unable to communicate with its volunteers, they go away and it ends up dying.”

One of the biggest programs associated with BOINC in the last year has been the Intel-sponsored Progress Thru Processors (www.facebook.com/progressthruprocessors) initiative, which tries to popularize distributed computing projects among everyday users.

“The primary communication mechanism is Facebook,” says Walton. “People can see how their friends are doing in terms of how much computing time they’ve contributed.”

Walton sees social media as fertile ground for distributed computing because it maps so well against the distributed computing idea. The computer grid is learning to use the online social grid. People tell others about the projects that interest them and share bragging rights over how much they contribute to various computing causes. Intel’s Facebook page has 125,000 fans. In coming years, the BOINC software may work directly with Facebook APIs so that new projects coming online will automatically create their own Facebook page and link and recruit users on the social networks the volunteers have already embraced.

“Our idea is to make BOINC more social network-friendly,” says Walton.

But in becoming more community-friendly, distributed computing projects are also learning to spread the word about science. Cochran’s Quake-Catcher project is reaching beyond seismic enthusiasts into K-12 classrooms.

“We can provide educational activities and teachers with information about earthquakes to teach in class,” she says. The Quake Catchers can come to class and give live demonstrations of the sensor at work. In exchange they ask the class to maintain it for a year. “Any earthquakes they record can be shown to the class,” she says.

Taufer believes that adding functions for communicating with the user base and sharing data on social networks through the BOINC platform will help turn some of these distributed computing projects into great opportunities to retain volunteers by educating them about science.

“The volunteers are more actively learning and becoming scientists,” she says.

The technology of distributed computing continues to make advances. Walton says that BOINC now supports both Nvidia and AMD GPUs, but it’s up to each project to make greater use of this enormous untapped power. Noll says that highly complex projects, such as calculating a prime number with 100 million digits, will require new algorithms that let many PCs work more cooperatively on a single large calculation. The Electronic Frontier Foundation recently awarded $100,000 to a GIMPS member machine that discovered the first prime number with more than 10 million digits. The next level of award, $150,000 for a 100 million-digit prime, was designed to force computer scientists to advance the art of distributed computing.

“It is going to require that we either wait for machines to get fast enough or for people to get smart enough about how to make computers cooperate,” says Noll.

But the biggest advance and benefit for science in these volunteer projects could be in giving scientists a broader audience with whom to speak.

“It has so many payoffs,” says Cordes. “It makes the case for our projects and for people being involved. They are a great vehicle for education. They attract people to Web sites to read and digest information. It is just a win-win.”

In the end, researchers hope that what really is being distributed in voluntary computing projects is not just processing power but a deeper and broader understanding of science itself.

by Steve Smith