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| Introduction to Pfortran Introduction to PfortranThe Pfortran programming approach eases the task of writing parallel programs for massively parallel computers by providing constructs to coordinate non-local memoryaccesses. At Pfortran's center is an operator that specifies the locationof off-processor variables and an operator for aggregate operations.Portability and ease of programming are achievedby unifying off-processor accesses with the guarded-memory model.Because the programmer writes low-levelnode code with Pfortran, the loss in performance compared to usingthe lowest-level primitives is typically negligible.The P-language notion subtending Pfortran was first conceived in a collaboration between University of Michigan and ArgonneNational Laboratories in 1986. The first P-languagecompiler, PC, was implemented in 1988 at Penn State.Later, in 1991, at the University of Houston, Pfortran was implemented.Also at this time, a University of Houston group ported the molecular-dynamics program, GROMOS, to the Intel hypercube for the first industrial-strength application of Pfortran.A number of well-known computational chemistry programs parallelized with Pfortran are now in production use on massively parallelcomputers, with several research groups now contributing to the ongoingdevelopment. Recently, a prototype of PC++ has been developed, with further refinements to the P-language concept.Pfortran is now available for Intel MPPs,networks of workstations using PVM, Cray multiprocessorsusing PVM, multiprocessor SGIs, IBM's SP1 and SP2,and the Kendall Square Research KSR-1. Pfortran can be installedon the target platform, or used as a cross compiler. SincePfortran produces FORTRAN77 native to the target MPP, codesdeveloped with Pfortran may be distributed without Pfortranby providing the Pfortran output to end users.Alternatives to the Pfortran approach include global namespace compilers, such as HPF, or machine specific compiler directives. In their early stage of development, global namespace compilers hold great promise for future parallel computing.Today, however, most parallel programmers of massively parallelcomputers resort to macro systems or native-compiler directives towrite node code. Native-compiler directives clearly restrict portability.Macro systems, such as the ANL Fortran macros, are related to Pfortranin spirit. However, Pfortran provides a slightly higher-levelabstraction along with determinism and the opportunity for sophisticated analysis such as deadlock detectionand code movement optimizations.For more information about Pfortran, contact tclark@kacha.chem.uh.edu.Suggested ReadingL.R. Scott, J.M. Boyle and B. Bagheri.``Distributed data structures for scientific computation.''Proceedings of the 3rd Hypercube Multiprocessors Conference,M.T. Heath, editor, Philadelphia, PA, SIAM, 1987, 55-66.B. Bagheri, B. Raghavachari, and L. R. Scott.``Sharing variables in parallel programs.'' Research Report UH/MD-79, Dept. of Math., University of Houston, 1990. Available via anonymous ftp from karazm.math.uh.edu as pub/Reports/UHMD79.ps.Babak Bagheri, Terry Clark, and L. Ridgway Scott.``Pfortran: A parallel dialect of Fortran.'' ACM Fortran Forum, 11(3), 1992, 20-31. Available via anonymous ftp from kacha.chem.uh.edu aspub/articles/fforum92.ps.T.W. Clark, J.A. McCammon and L.R. Scott,``Parallel Molecular Dynamics.'' Proceedings of the Fifth SIAM Conference on ParallelProcessing for Scientific Computing,'' SIAM, J. Dongarra et al.,editors, Houston, March, 1991, 338-344.Available via anonymous ftp from kacha.chem.uh.edu aspub/articles/siam91.ps.T. W. Clark, R. v. Hanxleden, K. Kennedy, C. Koelbel, and L. R. Scott.``Evaluating parallel languages for molecular dynamicscomputations.'' Proceedings Scalable High Performance Computing Conference,IEEE Computer Society, Williamsburg, VA, 1992, 98-105.Available via anonymous ftp from softlib.rice.edu as pub/CRPC-TRs/reports/CRPC-TR992202-S.Babak Bagheri, ``Parallel Programming with Guarded Objects.'' Ph.D. Dissertation, Pennsylvania State University, 1994.T. W. Clark, R. v. Hanxleden, J. A. McCammon, and L. R. Scott.Parallelizing molecular dynamics using spatial decomposition.In Proceedings of the Scalable High Performance Computing Conf erence, Knoxville, TN, May 1994.B. Bagheri, A. Ilin, and L. R. Scott.Parallel 3-d MOSFET simulation.In Proceedings of the Twenty-Seventh Annual Hawaii International Conference on System Sciences, Maui, HI, January 1994.4A. Ilin, B. Bagheri, L.R.Scott, J.M.Briggs, and J.A.Mc Cammon.Parallelization of Poisson-Boltzmann and Brownian Dynamics calculation.In Parallel Computing in Computational Chemistry, pages 170-185,Washington D.C., 1995. ACS Books.5J.D.Madura, J.M.Briggs, R.C.Wade, M.E.Davis, B.A.Luty, A. Ilin, J.Antosciewicz, M.K.Gilson, B.Bagheri, L.R.Scott and J.A.McCammon.Electrostatics and Diffusion of Molecules in Solution: Simulations with the Universityof Houston Brownian Dynamics ProgramComp. Phys. Commun., 91, pages 57-95, 1995.Clark, T.W., L.R. Scott, S.T. Wlodek, and J.A. McCammon. I/O Limitations in Parallel Molecular Dynamics. In "Proceedings of the 1995 ACM/IEEE Supercomputing Conference" (refereed), F. Baker and J. Wehmer, eds., IEEE Computer Society Press, pp. 1-15, 1995.Terry W. Clark, Parallel Programming Approach For Scientific Application, Dissertation, December 1996, University of Houston. postscript (6176 kB) |
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