Abstract.
We have developed a parallel programming environmentcalled the “Distributed Shared Array” (DSA), which provides a shared global array abstract across different machines connected by a network. The DSA provides array-specific operations and fine-grained data consistency based on arrays. It allows a user to explicitly manage array area allocation, replication, and migration. This paper also describes the use of our model for gene cluster analysis, multiple alignment, and molecular dynamics simulation. Global arrays are used in these applications for storing the distance matrix, alignment matrix and atom coordinates, respectively. Large array areas, which cannot be stored in the memory of individual machines, are made available by the DSA. Scalable performance of DSA was obtained and compared to that of conventional parallel programs written in MPI.
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References
Message Passing Interface Forum, MPI: A Message-Passing Interface Standard 1.1 edition (1995)
Geist, A., et al.: PVM: A Users’ Guide and Tutorial for Networked Parallel Computing. MIT Press, Cambridge (1994)
Durbin, E., Eddy, S., Krogh, A., Mitchison, G.: Biological sequential analysis. Cambridge University Press, Cambridge (1998)
Kal, L., et al.: NAMD2: Greater scalability for parallel molecular dynamics. Journal of Computational Physics 151, 283–312 (1999)
Nieplocha, J., Harrison, R.J., Littlefield, R.J.: Global Arrays: A nonuniform memory access programming model for high-performance computers. The Journal of Supercomputing 10, 197–220 (1996)
Nieplocha, J., Foster, I.: Disk Resident Arrays: An array-oriented I/O library for out-of-core computations. In: Proceedings of IEEE Conference on Frontiers of Massively Parallel Computing, pp. 196–204 (1996)
Carter, J.B., Bennett, J.K., Zwaenepoel, W.: Implementation and performance of MUNIN. In: Proceedings of 13th ACM Symposium on Operating Systems Principles, pp. 152–164 (1991)
Bershad, B.N., Zekauskas, M.J., Sawdon, W.A.: Midway: Shared Memory Parallel Programming with Entry Consistency for Distributed Memory Multiprocessors, Technical Report CMU-CS-91-170, Carnegie Mellon University (1991)
Castro, M., Guedes, P., Sequeira, M., Costa, M.: Efficient and flexible object sharing. In: Proceedings of 1996 International Conference on Parallel Processing, pp. 128–137 (1996)
Keleher, P., Cox, A.L., Dwarkadas, S., Zwaenepoel, W.: TreadMarks: Shared memory computing on networks of workstations. IEEE Computer 29(2), 18–28 (1996)
Xu, C., Wims, B., Jamal, R.: Distributed shared array: an integration of message passing and multithreading on SMP clusters. In: Proceedings of the 11th IASTED International Conference on Parallel and Distributed Computing and Systems, pp. 305–310 (1999)
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Kaneko, W., Nomoto, A., Watanabe, Y., Nakamura, S., Shimizu, K. (2003). Design and Implementation of a Parallel Programming Environment Based on Distributed Shared Arrays. In: Veidenbaum, A., Joe, K., Amano, H., Aiso, H. (eds) High Performance Computing. ISHPC 2003. Lecture Notes in Computer Science, vol 2858. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39707-6_35
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DOI: https://doi.org/10.1007/978-3-540-39707-6_35
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