MADNESS calms chemistry on computers

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The computational chemistry algorithms Fann and Beylkin have developed with Harrison “scale linearly” – they allow scientists to model larger and larger systems without sacrificing speed or precision.  In addition, they are especially well adapted for parallel processing, the approach that lets high-performance computers run thousands of processors at once.

“We’ve demonstrated that it scales up to at least 4,000 processors,” Fann says.  His latest research, through SciDAC, is aimed at preparing the algorithms to run on the petascale computers coming on line in the next few years – computers capable of one quadrillion calculations per second.  That’s almost 3.5 times faster than today’s fastest computer.

The programming tools that run underneath MADNESS will be released in late March or early April 2007, Fann says.  A general release of the mathematics and operators is slated for September 2007.

There’s still work to be done, however.  The researchers must collaborate with scientists in each field to adapt the code for their use.  The code currently runs time-independent problems – taking into consideration only space, not changes over time.  And Fann and his colleagues believe they can make their algorithms run as much as three times faster than they do now.

“Speeding up the code is one of our goals but it’s not the main goal,” Fann says.  “The main focus is on extending the approach to problems with more complicated mathematics.  For example, introducing boundary conditions for arbitrary regions, without losing the high order of accuracy, allows our methods to solve more difficult problems.  Another example is taking advantage of multiresolution representation for time-evolving problems.

He adds, “It all starts with the math,” but “If we don’t get the mathematical representations and algorithms right and then the parallel computing it’s not going to work. … Without the scientists, Robert Harrison and others, we would not have been able to get” the physics, chemistry and other factors right.  The practical demands of those computational scientists also help to focus the math research on relevant directions.

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