Multiprocessors and run-time compilation

Run-time preprocessing plays a major role in many efficient algorithms in computer science, as well as playing an important role in exploiting multiprocessor architectures. We give examples that elucidate the importance of run-time preprocessing and show how these optimizations can be integrated into compilers. To support our arguments, we describe transformations implemented in prototype multiprocessor compilers and present benchmarks from the iPSC2/860, the CM-2 and the Encore Multimax/320.

[1]  Joel H. Saltz,et al.  Principles of runtime support for parallel processors , 1988, ICS '88.

[2]  Ellis Horowitz,et al.  Fundamentals of Data Structures , 1984 .

[3]  E. D. Dahl,et al.  Mapping and Compiled Communication on the Connection Machine System , 1990, Proceedings of the Fifth Distributed Memory Computing Conference, 1990..

[4]  P. Sadayappan,et al.  An approach to synchronization for parallel computing , 1988, ICS '88.

[5]  Joel H. Saltz,et al.  Run-Time Parallelization and Scheduling of Loops , 1991, IEEE Trans. Computers.

[6]  Charles Koelbel,et al.  Supporting shared data structures on distributed memory architectures , 1990, PPOPP '90.

[7]  Pen-Chung Yew,et al.  A Scheme to Enforce Data Dependence on Large Multiprocessor Systems , 1987, IEEE Trans. Software Eng..

[8]  Harry Berryman,et al.  Krylov Methods Preconditioned with Incompletely Factored Matrices on the CM-2 , 1990, J. Parallel Distributed Comput..

[9]  Joel H. Saltz,et al.  Parallel preconditioned iterative methods for the compressible Navier-Stokes equations , 1990 .

[10]  Joseph W. H. Liu,et al.  Computational models and task scheduling for parallel sparse Cholesky factorization , 1986, Parallel Comput..

[11]  Gita Alaghband.  Parallel pivoting combined with parallel reduction and fill-in control , 1989, Parallel Comput..

[12]  Joel H. Saltz,et al.  The Preprocessed Doacross Loop , 1991, ICPP.

[13]  Joel H. Saltz,et al.  Aggregation Methods for Solving Sparse Triangular Systems on Multiprocessors , 1990, SIAM J. Sci. Comput..

[14]  Bobby Schnabel,et al.  An Overview of Dino - A New Language for Numerical Computation on Distributed Memory Multiprocessors , 1987, PPSC.

[15]  Charles Koelbel,et al.  Compiling global name-space programs for distributed execution , 1990 .

[16]  Harry Berryman,et al.  Run-Time Scheduling and Execution of Loops on Message Passing Machines , 1990, J. Parallel Distributed Comput..

[17]  Anne Rogers,et al.  Process decomposition through locality of reference , 1989, PLDI '89.

[18]  S. Eisenstat,et al.  An experimental study of methods for parallel preconditioned Krylov methods , 1989, C3P.

[19]  David Lee Whitaker.  Two-dimensional Euler computations on a triangular mesh using an upwind, finite-volume scheme , 1988 .

[20]  Ron Cytron,et al.  Doacross: Beyond Vectorization for Multiprocessors , 1986, ICPP.

[21]  Yousef Saad,et al.  Solving Sparse Triangular Linear Systems on Parallel Computers , 1989, Int. J. High Speed Comput..

[22]  Iain S. Duff,et al.  Parallel implementation of multifrontal schemes , 1986, Parallel Comput..

[23]  D. Mavriplis.  Multigrid solution of the two-dimensional Euler equations on unstructured triangular meshes , 1987 .

[24]  I. Duff,et al.  Direct Methods for Sparse Matrices , 1987 .

[25]  R. Walters,et al.  Solution algorithms for the two-dimensional Euler equations on unstructured meshes , 1990 .