Exploiting locality in the run-time parallelization of irregular loops

Proceedings of the International Conference on Parallel Processing

Volumn 2002-January, Issue , 2002, Pages 27-34

  Martin M J ^a   Singh, D E ^b   Tourino J ^a   Rivera, F F ^b  

^a UNIVERSITY OF A CORUÑA   (Spain)

^b UNIVERSITY OF SANTIAGO DE COMPOSTELA   (Spain)

Author keywords

Computer science; Data mining; Degradation; Finite element methods; Fluid dynamics; Fluid flow; Parallel processing; Pattern analysis; Runtime; Sparse matrices

Indexed keywords

COMPUTER SCIENCE; DEGRADATION; FINITE ELEMENT METHOD; FLOW OF FLUIDS; FLUID DYNAMICS; PARALLEL FLOW;

BLOCK-CYCLIC DISTRIBUTION; GRAPH PARTITIONING; PARALLEL EXECUTIONS; PARALLEL PROCESSING; PARALLELIZING COMPILER; PATTERN ANALYSIS; RUNTIMES; SPARSE MATRICES;

DATA MINING;

EID: 84948457540     PISSN: 01903918     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPP.2002.1040856     Document Type: Conference Paper

References (23)

1. th Int'l Parallel Processing Symposium, Orlando, FL, 1998.
2. D.-K. Chen, J. Torrellas, and P.-C. Yew. An Efficient Algorithm for the Run-Time Parallelization of DOACROSS Loops. In Supercomputing Conference, pages 518-527, Washington DC, 1994.
3. C. Ding and K. Kennedy. Improving Cache Performance in Dynamic Applications through Data and Computation Reorganization at Run Time. In ACM SIGPLAN'99 Conference on Programming Language Design and Implementation, pages 229-241, Atlanta, GA, 1999.
4. I. S. Duff, R. G. Grimes, and J. G. Lewis. User's Guide for the Harwell-Boeing Sparse Matrix Collection. Technical Report TR-PA-92-96, CERFACS, 1992.
5. M. Gupta and R. Nim. Techniques for Speculative Run-Time Parallelization of Loops. In Supercomputing Conference, Orlando, FL, 1998.
6. H. Han and C.-W. Tseng. Efficient Compiler and Run-Time Support for Parallel Irregular Reductions. Parallel Computing, 26(13-14):1861-1887, 2000.
7. th Int'l Workshop on Languages and Compilers for Parallel Computing, pages 173-188, Yorktown Heights, NY, 2000.
8. Y. C. Hu, A. L. Cox, and W. Zwaenepoel. Improving Fine-Grained Irregular Shared-Memory Benchmarks by Data Reordering. In Supercomputing Conference, Dallas, TX, 2000.
9. st Annual IEEE/ACM Int'l Symposium on Microarchitecture, pages 285-297, Dallas, TX, 1998.
10. G. Karypis and V. Kumar. A Fast and High Quality Multi-level Scheme for Partitioning Irregular Graphs. SIAM Journal on Scientific Computing, 20(1):359-392, 1999.
11. S.-T. Leung and J. Zahorjan. Restructuring Arrays for Efficient Parallel Loop Execution. Technical Report 94-02-01, Department of Computer Science and Engineering, University of Washington, 1994.
12. S.-T. Leung and J. Zahorjan. Extending the Applicability and Improving the Performance of Runtime Parallelization. Technical Report 95-01-08, Department of Computer Science and Engineering, University of Washington, 1995.
13. K. S. McKinley, S. Carr, and C.-W. Tseng. Improving Data Locality with Loop Transformations. ACM Trans. on Programming Languages and Systems, 18(4):424-453, 1996.
14. J. M. Mellor-Crummey, D. B. Whalley, and K. Kennedy. Improving Memory Hierarchy Performance for Irregular Applications. In ACM Int'l Conference on Supercomputing, pages 425-433, Rhodes, Greece, 1999.
15. S. P. Midkiff and D. A. Padua. Compiler Algorithms for Synchronization. IEEE Transactions on Computers, 36(12):1485-1495, 1987.
16. th Int'l Conference on Compiler Construction, pages 183-197, Amsterdam, The Netherlands, 1999.
17. Y. Saad. SPARSKIT: a Basic Tool Kit for Sparse Matrix Computations (Version 2), 1994.
18. J. H. Saltz, R. Mirchandaney, and K. Crowley. Run-Time Parallelization and Scheduling of Loops. IEEE Transactions on Computers, 40(5):603-612, 1991.
19. th Int'l Conference on Parallel Processing Workshops, pages 17-22, Valencia, Spain, 2001.
20. M. E. Wolf and M. S. Lam. A Data Locality Optimizing Algorithm. In ACM SIGPLAN'91 Conference on Programming Language Design and Implementation, pages 30-44, Toronto, Canada, 1991.
21. st Hawaii Int'l Conference on System Sciences, Kohala Coast, HI, 1998.
22. C. Xu and V. Chaudhary. Time Stamp Algorithms for Runtime Parallelization of DOACROSS Loops with Dynamic Dependences. IEEE Transactions on Parallel and Distributed Systems, 12(5):433-450, 2001.
23. C.-Q. Zhu and P.-C. Yew. A Scheme to Enforce Data Dependence on Large Multiprocessor Systems. IEEE Transactions on Software Engineering, 13(6):726-739, 1987.