Abstract
Scientific codes which use iterative methods are often difficult to parallelize well. Such codes usually contain while loops which iterate until they converge upon the solution. Problems arise since the number of iterations cannot be determined at compile time, and tests for termination usually require a global reduction and an associated barrier. We present a method which allows us avoid performing global barriers and exploit pipelined parallelism when processors can detect nonconvergence from local information.
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J.-F. Collard. Space-time transformation of while-loops using speculative execution. In Proc. of the 1994 Scalable High Performance Computing Conf., pages 429–436, Knoxville, TN, May 1994. IEEE.
J.-F. Collard. Automatic parallelization of while-loops using speculative execution. Int. J. of Parallel Programming, 23(2):191–219, April 1995.
M. Griebl and J.-F. Collard. Generation of synchronous code for automatic parallelization of while loops. In N.N., editor, EuroPar 95, Lecture Notes in Computer Science. Springer-Verlag, 1995.
M. Griebl and C. Lengauer. On scanning space-time mapped while loops. In B. Buchberger and J. Volkert, editors, Parallel Processing: CONPAR 94 — VAPP VI, Lecture Notes in Computer Science 854, pages 677–688. Springer-Verlag, 1994.
M. Griebl and C. Lengauer. On the space-time mapping of WHILE-loops. Parallel Processing Letters, 4(3):221–232, September 1994.
David Kincaid and Ward Cheney. Numerical Analysis. Brooks/Cole Publishing Company, 1991.
C. Lengauer and M. Griebl. On the parallelization of loop nests containing while loops. In N. N. Mirenkov, Q.-P. Gu, S. Peng, and S. Sedukhin, editors, Proc. 1st Aizu Int. Symp. on Parallel Algorithm/Architecture Synthesis (pAs'95), pages 10–18. IEEE Computer Society Press, 1995.
William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery. Numerical Recipes in C: The Art of Scientific Computing. Cambridge University Press, second edition, 1992.
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© 1997 Springer-Verlag Berlin Heidelberg
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Pugh, W., Rosser, E., Shpeisman, T. (1997). Exploiting monotone convergence functions in parallel programs. In: Sehr, D., Banerjee, U., Gelernter, D., Nicolau, A., Padua, D. (eds) Languages and Compilers for Parallel Computing. LCPC 1996. Lecture Notes in Computer Science, vol 1239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0017246
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DOI: https://doi.org/10.1007/BFb0017246
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