Screen Savers of the World Unite!

this article Download to Citation Manager Collections under which this unparallelizable to be performed on hundreds or thousands of computers with very little communication between the processors. Even if an algorithm can be parallelized, it may still be poorly suited for distributed computing. Consider, for example, simulations of the dynamics of biomolecules at the atomic level. Such simulations are traditionally limited to the nanosecond time scale. Duan and Kollman have demonstrated that traditional parallel molecular dynamics simulations can break the microsecond barrier (3), provided that one uses many tightly connected processors running on an expensive supercomputer for many months. This style of calculation requires, however, that the processors frequently communicate information and is thus poorly suited for worldwide distributed computing, where computer communication is thousands of times slower than the interprocessor communication in today's supercomputers. Recently, an algorithm has been developed that helps address the problems of both parallelization and communication by allowing loosely connected multiple processors to be used for molecular dynamics (4, 5). The Folding@home project (5) has shown that this algorithm can reach orders of magnitude longer time scales than have previously been achieved when used for distributed atomistic biomolecular dynamics simulations. The design of similar algorithms for parallelization will likely play a major role in adapting other problems in computational biophysics (such as the design of more effective drugs) and other fields for distributed computing. The ability to engage users to run the simulation software is central to the success of worldwide distributed computing. First, the user must have some interest in v..