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Now, he's created Popular Power, a Silicon Valley company dedicated to linking cycle-wasting idle computers together to form virtual supercomputers. Popular Power will provide a source of income to the computer owners, and high-test computing power to Popular Power customers.
JavaWorld columnist Mark Johnson recently had the opportunity to speak with Minar about his company's business model, the technological challenges facing Popular Power, and Java's role in answering those challenges. You'll find numerous informative URLs, including a link to Popular Power, in the Resources section.
JavaWorld: What's the mission of Popular Power?
Nelson Minar: Our goal is to take all the computers out there on the Internet, make use of their idle resources, and resell to those who have large computation or network jobs.
JavaWorld: Tell me more about your first application, the influenza virus study.
Nelson Minar: Part of our business plan is to do a mix of nonprofit and for-pay applications. We're starting out with a couple of nonprofit applications, the first of which is this influenza research. The goal is to develop computer models and to do computer simulation of effective vaccines for the flu on the human immune system to help people develop more effective flu vaccines in the future.
JavaWorld: And so there's a human immune system model and a flu vaccine model, and the two models crunch against one another in this big distributed supercomputer?
Nelson Minar: Exactly.
JavaWorld: It seems that most distributed supercomputing projects like this focus on one of three kind of main areas: either mathematical problems like crypto cracking, prime number searches, and obscure number-theoretic problems; distributed rendering; or signal processing, like SETI@Home. Why are there so many of these projects in just these small areas and what new categories of projects do you envision for the future?
Nelson Minar: One of the early challenges of building this type of system was to find large problems that were easy to break up into lots of little bits of work. And in particular, with the earliest projects, like the key cracking, they were also trying to keep the code size and data size down, to make the networking problem simpler.
These problems we mentioned, like key cracking, were great examples of that. SETI@Home changed the model a little bit in that they started shipping around a fair amount of data. The average data set size in SETI@Home is about 300K. There we started to see more complex data processing and distributed computing. Popular Power brings a new capability to this idea. We're using mobile code to change the kinds of jobs that your computer runs.