Design theory
Shortest-path problems and molecular conformation
Discrete Applied Mathematics - Applications of Graphs in Chemistry and Physics
A bridging model for parallel computation
Communications of the ACM
Introduction to algorithms
Scalability of parallel algorithms for the all-pairs shortest-path problem
Journal of Parallel and Distributed Computing
Distributed computation on graphs: shortest path algorithms
Communications of the ACM
Communications of the ACM
MPI: The Complete Reference
A Parallel Algorithm for Bound-Smoothing
IPPS '99/SPDP '99 Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing
A Coming of Age for Beowulf-Class Computing
Euro-Par '99 Proceedings of the 5th International Euro-Par Conference on Parallel Processing
Parallel algorithms for the molecular conformation problem
Parallel algorithms for the molecular conformation problem
Parallel graph algorithms for molecular conformation and tree codes
Parallel graph algorithms for molecular conformation and tree codes
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Determining the three-dimensional structure of proteins is crucial to efficient drug design and understanding biological processes. One successful method for computing the molecule's shape relies on inter-atomic distance bounds provided by Nuclear Magnetic Resonance spectroscopy. The accuracy of computed structures as well as the time required to obtain them are greatly improved if the gaps between the upper and lower distance-bounds are reduced. These gaps are reduced most effectively by applying the tetrangle inequality, derived from the Cayley-Menger determinant, to all atom-quadruples. However, tetrangle-inequality bound-smoothing is an extremely computation intensive task, requiring O(n4) time for an n-atom molecule. To reduce computation time, we propose a novel coarse-grained parallel algorithm intended for a Beowulf-type cluster of PCs. The algorithm employs p 驴 n/6 processors and requires O(n4/p) time and O(p2) communications, where n is the number of atoms in a molecule. The number of communications is at least an order of magnitude lower than in the earlier parallelizations. Our implementation utilized processors with at least 59% efficiency (including the communication overhead)--an impressive figure for a non-embarrassingly parallel problem on a cluster of workstations.