Abstract
New features of our DSC system for distributing a symbolic computation task over a network of processors are described. A new scheduler sends parallel subtasks to those compute nodes that are best suited in handling the added load of CPU usage and memory. Furthermore, a subtask can communicate back to the process that spawned it by a co-routine style calling mechanism. Two large experiments are described in this improved setting. We have implemented an algorithm that can prove a number of more than 1,000 decimal digits prime in about 2 months elapsed time on some 20 computers. A parallel version of a sparse linear system solver is used to compute the solution of sparse linear systems over finite fields. We are able to find the solution of a 100,000 by 100,000 linear system with about 10.3 million non-zero entries over the Galois field with 2 elements using 3 computers in about 54 hours CPU time.
This material is based on work supported in part by the National Science Foundation under Grant No. CCR-90-06077, CDA-91-21465, and under Grant No. CDA-88-05910.
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© 1993 Springer-Verlag Berlin Heidelberg
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Diaz, A., Hitz, M., Kaltofen, E., Lobo, A., Valente, T. (1993). Process scheduling in DSC and the large sparse linear systems challenge. In: Miola, A. (eds) Design and Implementation of Symbolic Computation Systems. DISCO 1993. Lecture Notes in Computer Science, vol 722. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0013169
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DOI: https://doi.org/10.1007/BFb0013169
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