Abstract
The EDMC (electrostatically driven Monte Carlo) method has proven to be an effective computational tool for searching the potential energy hypersurface of polypeptide molecules consisting of up to 20 amino acid residues. Such a Monte Carlo search combined with gradient-based energy minimization of molecular conformations results in the need for 100 gigaflop or higher performance levels. The parallel EDMC algorithm has been designed to exploit currently available supercomputing technology. The implementation on the iPSC/2 described appears to represent an improvement over the original version for the IBM 3090. A performance analysis indicates that the attainable parallelism is limited by the underlying acceptance rate of search. It is demonstrated that a coarse-grained approach is suitable for architectures such as the CRAY-XMP, particularly if vectorization techniques can be exploited. Tests on the Intel iPSC/2-VX computer have shown, however, that even the easily vectorized parts of the computation may not overcome a large vector pipeline latency. >
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