Development of a Parallel Programming Environment based on Distributed Shared Arrays with Application-Specific Resource Management

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We have developed a parallel programming environment called "Distributed Shared Array (DSA)," which provides a shared global array abstract across different machines connected by a network. In DSA, users can define and use global arrays that can be accessed uniformly from any machines in the network. Explicit management of array area allocation, replication, and migration is achieved by explicit calls for array manipulation defining array regions, reading and writing array regions, synchronization, and control of replication and migration. The DSA is integrated with Grid (Globus) services. We also develop the bioinformatics applications such as gene cluster analysis, multiple sequence alignment, and molecular dynamics simulation. In these applications, global arrays are used for storing the distance matrix, alignment matrix and atom coordinates, respectively. Large array areas, which cannot be stored in the memory of individual machines, will be made available by this system. Scalable performance of DSA was obtained compared to that of conventional parallel programs written in MPI.