Abstract
Parallelizing irregular scientific computation efficiently is a challenging open research area. In this paper we investigate the applicability of graph scheduling techniques to solving irregular problems in distributed memory machines Our approach is to express irregular computation in terms of a macro-dataflow task model and use an automatic scheduling system to map task graphs and also generate parallel code based on the scheduling result. We study the performance of run-time execution of an irregular static schedule and report our solutions with the automatic scheduling system for sparse matrix computation and hierarchical 2D N-body simulations. We also examine the run-time performance of static mapping for the adaptive n-body simulation. Our preliminary experiments in nCUBE-2 have produced promising results with regard to the practicality of automatic scheduling for irregular problems.
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References
F.L. Alvarado, The spares matrix manipulation system users manual, University of Wisconsin, Oct. 1990.
S. Bokhari, On the mapping problem, IEEE Trans. Comput. C-30 3 (1981), 207–214.
D. Y. Cheng and S. Ranka, An optimization approach for static scheduling of directed-acyclic graphs on distributed memory multiprocessors, Report, Syracuse Univ, 1992
Frederic T. Chong and Robert Schreiber, Parallel sparse triangular solution with partitioned inverses and prescheduled DAGs, Tech Report, 1994.
Frederic T. Chong, Shamik D. Sharma, Eric A. Brewer and Joel Saltz, Multiprocessor Runtime Support for Fine-Grained Irregular DAGs, To appear in Toward Terafâop Computing and New Grand Challenge Applications. Eds. Rajiv K. Kalia and Priya Vashishta. Nova Science Publishers, Inc. New York. 1995.
Ph. Chretienne, Task Scheduling over Distributed Memory Machines, Proc. of Inter. Workshop on Parallel and Distributed Algorithms, ( North Holland, Ed. ), 1989.
E.G. Coffman and R.L. Graham, Optimal scheduling for two-processors systems, Acta Informatica, 3 (1972), 200–213.
J.J. Dongarra,. and D. C. Sorensen, SCHEDULE: Tools for Developing and Analyzing Parallel Fortran Programs, in The Characteristics of Parallel Algorithms, D.B. Gannon, L.H. Jamieson and R.J. Douglass (Eds), MIT Press, 1987, pp 363–394.
H. El-Rewini and T.G. Lewis, Scheduling parallel program tasks onto arbitrary target machines, J. of Parallel and Distributed Computing, 9 (1990), 138–153.
A. George,, M.T. Heath, and J. Liu, Parallel Cholesky factorization on a shared memory processor, Lin. Algebra Appl., 77 (1986), pp. 165–187.
A. Gerasoulis and T. Yang, On the granularity and clustering of directed acyclic task graphs, IEEE Trans. on Parallel and Distributed Systems., Vol 4, No 6, June 1993 pp. 686–701.
A. Gerasoulis and T. Yang, A comparison of clustering heuristics for scheduling DAGs on multiprocessors, J. of Distributed and Parallel Computing, Vol. 16, No. 4, pp. 276–291 (Dec. 1992).
A. Gerasoulis, J. Jiao, and T. Yang, A multistage approach to scheduling task graphs. To appear in DIAMCS Book Series on Parallel Processing of Discrete Optimization Problems. AMS publisher. Edited by P.M. Pardalos, K.G. Ramakrishnan, and M.G.C. Resende.
Leslie Greengard, The Rapid Evaluation of Potential Fields in Particle Systems Ph.D thesis, Yale University, 1987.
J.A. Hoogeveen, S.L. van de Velde, and B. Veltman, Complexity of scheduling multiprocessor tasks with prespecified processor allocations, CWI, Report BS-R9211 June 1992, Netherlands.
J. J. Hwang, Y. C. Chow, F. D. Anger, and C. Y. Lee, Scheduling precedence graphs in systems with interprocessor communication times, SIAM J. Comput., pp. 244–257, 1989.
N. Karmarkar, A new parallel architecture for sparse matrix computation based on finite project geometries, Proc. of Supercomputing ‘81,IEEE, pp. 358–369.
S.J. Kim and J.0 Browne, A general approach to mapping of parallel computation upon multiprocessor architectures, Proc. of Int’l Conf. on Parallel Processing, vol 3, pp. 1–8, 1988.
C.L. McCreary and D.H. Gill, Automatic determination of grain size for efficient parallel processing, Communications of ACM, vol. 32, pp. 10731078, Sept., 1989.
S. Pande, D. Agrawal and Jon Mauney A threshold Scheduling Strategy for Sisal on distributed Memory Machines IEEE Parallel and Distributed Technology, vol. 21, pp. 223–236, 1994.
C. D. Polychronopoulos, M. Girkar, M. Haghighat,C. Lee, B. Leung, and D. Schouten, The Structure of Parafrase-2: An advanced parallelizing compiler for C and Fortran, in Languages and Compilers for Parallel Computing, D. Gelernter, A. Nicolau and D. Padua (Eds.), 1990.
Ravi Ponnusamy, Yuan-Shin Hwang, Joel Saltz, Alok Choudhary, Geoffrey Fox. Supporting Irregular Distributions in FORTRAN 90D/HPF Compilers, University of Maryland, Department of Computer Science and UMIACS Technical Reports CS-TR-3268, UMIACS-TR-94–57
R. Pozo, Performance modeling of sparse matrix methods for distributed memory architectures, in Lecture Notes in Computer Science, No. 63.4, Parallel Processing: CONPAR 92–VAPP V, Springer-Varlag, 1992, pp. 677–688.
Saltz, J., Crowley, K., Mirchandaney, R. and Berryman,H., Run-time scheduling and execution of loops on message passing machines, J. of Parallel and Distributed Computing, Vol. 8, 1990, pp. 303–312.
V. Sarkar, Partitioning and Scheduling Parallel Programs for Execution on Multiprocessors, The MIT Press, 1989.
M. Y. Wu and D. Gajski, Hypertool: A programming aid for message-passing systems, IEEE Trans. on Parallel and Distributed Systems, vol. 1, no. 3, pp. 330–343, 1990.
T. Yang and A. Gerasoulis, PYRROS: Static task scheduling and code generation for message-passing multiprocessors, Proc. of 6th ACM Inter. Conf. on Supercomputing, Washington D.C., July, 1992, pp. 428–437.
T. Yang and A. Gerasoulis, List scheduling with and without communication delay, Parallel Computing, Vol 19, 1993, pp. 1321–1344.
T. Yang and A. Gerasoulis, DSC: Scheduling parallel tasks on an unbounded number of processors, IEEE Trans. on Parallel and Distributed Systems., Vol. 5, No. 9, 951–967, 1994.
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Gerasoulis, A., Jia, J., Tao, Y. (1995). Applications of Graph Scheduling Techniques in Parallelizing Irregular Scientific Computation. In: Ferreira, A., Rolim, J.D.P. (eds) Parallel Algorithms for Irregular Problems: State of the Art. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-6130-6_13
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