Abstract
In this talk we will present the SUPRENUM multiprocessor system and some implementations of parallelized sparse matrix algorithms. The SUPRENUM multiprocessor system was delivered late in 1989 for the first time. It is the result of a research project where German research institutes, universities and industrial companies worked together to built a 256 processor distributed memory machine. In parallel with the construction of the SUPRENUM a lot of time and man power was invested for the software support of the project. As an important application in scientific computation we parallelized the solution of systems of linear equations Ax=b. For realistic problems the large coefficient matrix A is sparse most of the time, i.e. a large number of its entries are zero. We show how direct algorithms based on Gauss Elimination and semi-iterative algorithms (Conjugate Gradient Methods) can be implemented on SUPRENUM. Especially the Conjugate Gradient Methods which are very well suited for parallelization and vectorization proved to be very efficient on multiprocessor architectures.
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Literature
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© 1990 Springer-Verlag Berlin Heidelberg
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Brehm, J., Böhm, A., Volkert, J. (1990). Sparse matrix algorithms for SUPRENUM. In: Burkhart, H. (eds) CONPAR 90 — VAPP IV. VAPP CONPAR 1990 1990. Lecture Notes in Computer Science, vol 457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-53065-7_93
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DOI: https://doi.org/10.1007/3-540-53065-7_93
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