Parallel clustering algorithm

Find the list L, of K nearest neighbors j of each particle i in / ciust radius and sort out the list in ascending order according to the distance between i and j particles. Thus L,(k) = j and k is the position of the particle j in the list. This procedure can be performed in parallel along with computation of forces in FPM code. To reduce the communication overhead, we use the parallel clustering algorithm off-line after simulation. 

A. P. Rendell, M. F. Guest, and R. A. Kendall,/. Comput. Chem., 14, 1429 (1993). Distributed Data Parallel Coupled Cluster Algorithm Application to the 2-Hydroxypyridine/2-Pyridone Tautomerism. 

Kobayashi, R., and A. P. Rendell. A direct coupled cluster algorithm for massively parallel computers. Chem. Phys. Lett. 265 1-11,1997. 

An improved parallel evolutionary algorithm [84] and basin hopping combined with vibrational modes [50] are examples of successful approaches to the problem of global optimization of water clusters. However, these methods are not able to find the lowest energy geometry for systems with more than 30 water molecules. A detailed comparison of results for each cluster size can be found in our publication that describes an application of minima hopping to water clusters [41]. 

Parallel Evolutionary Algorithms for Optimizing the Unifac Matrix on Workstation Clusters... 

This completes the outline of FAMUSAMM. The algorithm has been implemented in the MD simulation program EGO VIII [48] in a sequential and a parallelized version the latter has been implemented and tested on a number of distributed memory parallel computers, e.g., IBM SP2, Cray T3E, Parsytec CC and ethernet-linked workstation clusters running PVM or MPI. 

Our multipole code D-PMTA, the Distributed Parallel Multipole Tree Algorithm, is a message passing code which runs both on workstation clusters and on tightly coupled machines such as the Cray T3D/T3E [11]. Figure 3 shows the parallel performance of D-PMTA on a moderately large simulation on the Cray T3E the scalability is not affected by adding the macroscopic option. 

NAMD [7] was born of frustration with the maintainability of previous locally developed parallel molecular dynamics codes. The primary goal of being able to hand the program down to the next generation of developers is reflected in the acronym NAMD Not (just) Another Molecular Dynamics code. Specific design requirements for NAMD were to run in parallel on the group s then recently purchased workstation cluster [8] and to use the fast multipole algorithm [9] for efficient full electrostatics evaluation as implemented in DPMTA [10]. 

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