Satisfying your dependencies with SuperMatrix

Proceedings - IEEE International Conference on Cluster Computing, ICCC

Volumn , Issue , 2007, Pages 91-99

  Chan, Ernie ^a   Van Zee, Field G ^a   Quintana Ortí, Enrique S ^b   Quintana Ortí, Gregorio ^b   Van Geijn, Robert De ^a  

^a University of Texas at Austin   (United States)

^b UNIVERSITAT JAUME I   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ALGEBRA; COMPUTER ARCHITECTURE; COMPUTER SCIENCE; COMPUTER SYSTEMS; MATRIX ALGEBRA;

CLUSTER COMPUTING; DATA DEPENDENCIES; DATA-DEPENDENCY ANALYSIS; EMPIRICAL EVIDENCES; FUNDAMENTAL UNIT; HIGH-LEVEL ABSTRACTIONS; INTERNATIONAL CONFERENCES; LINEAR ALGEBRA OPERATIONS; MICRO-ARCHITECTURES; OUT-OF-ORDER; OUT-OF-ORDER EXECUTION; PERFORMANCE RESULTS; SUB-MATRICES; SUPER MATRIX; SUPER SCALAR;

LINEAR ALGEBRA;

EID: 51049099053     PISSN: 15525244     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CLUSTR.2007.4629221     Document Type: Conference Paper

References (29)

1. C. Addison, Y. Ren, and M. van Waveren. OpenMP issues arising in the development of parallel BLAS and LAPACK libraries. Scientific Programming, 11(2), 2003.
2. R. C. Agarwal and F. G. Gustavson. Vector and parallel algorithms for Cholesky factorization on IBM 3090. In SC '89: Proceedings of the 1989 ACM/IEEE Conference on Supercomputing, pages 225-233, New York, NY, USA, 1989.
3. E. Anderson, Z. Bai, C. Bischof, L. S. Blackford, J. Demmel, Jack J. Dongarra, J. Du Croz, S. Hammarling, A. Greenbaum, A. McKenney, and D. Sorensen. LAPACK Users' guide (third ed.). Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 1999.
4. Pieter Bellens, Josep M. Perez, Rosa M. Badia, and Jesus Labarta. CellSs: A programming model for the Cell BE architecture. In SC '06: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing, pages 5-15, Tampa, FL, USA, November 2006.
5. Paolo Bientinesi, Brian Gunter, and Robert van de Geijn. Families of algorithms related to the inversion of a symmetric positive definite matrix. ACM Transactions on Mathematical Software. Submitted.
6. Paolo Bientinesi, Enrique S. Quintana-Ortí, and Robert A. van de Geijn. Representing linear algebra algorithms in code: The FLAME application programming interfaces. ACM Transactions on Mathematical Software, 31(1):27-59, March 2005.
7. Ernie Chan, Enrique S. Quintana-Ortí, Gregorio Quintana-Ortí, and Robert van de Geijn. SuperMatrix out-of-order scheduling of matrix operations for SMP and multi-core architectures. In SPAA '07: Proceedings of the Nineteenth Annual ACM Symposium on Parallelism in Algorithms and Architectures, pages 116-125, San Diego, CA, USA, June 2007.
8. S. Chatterjee, A. R. Lebeck, P. K. Patnala, and M. Thottethodi. Recursive array layouts and fast matrix multiplication. IEEE Transactions on Parallel and Distributed Systems, 13(11): 1105-1123, 2002.
9. Timothy Collins and James C. Browne. Matrix++: An object-oriented environment for parallel high-performance matrix computations. In Proceedings of the Hawaii International Conference on Systems and Software, 1995.
10. Timothy Scott Collins. Efficient Matrix Computations through Hierarchical Type Specifications. PhD thesis, The University of Texas at Austin, 1996.
11. Jack J. Dongarra, Jeremy Du Croz, Sven Hammarling, and Iain Duff. A set of level 3 Basic Linear Algebra Subprograms. ACM Transactions on Mathematical Software, 16(1): 1-17, March 1990.
12. Kazushige Goto. http://www.tace.utexas.edu/resources/software.
13. Kazushige Goto and Robert A. van de Geijn. Anatomy of high-performance matrix multiplication. ACM Transactions on Mathematical Software. To appear.
14. W. Gropp, E. Lusk, and A. Skjellum. Using MPI. The MIT Press, 1994.
15. Michael Gschwind, H. Peter Hofstee, Brian Flachs, Martin Hopkins, Yukio Watanabe, and Takeshi Yamazaki. Synergistic processing in Cell's multicore architecture. IEEE Micro, 26(2): 10-24, 2006.
16. John A. Gunnels, Fred G. Gustavson, Greg M. Henry, and Robert A. van de Geijn. FLAME: Formal linear algebra methods environment. ACM Transactions on Mathematical Software, 27(4):422-455, December 2001.
17. F. G. Gustavson, L. Karlsson, and B. Kagstrom. Three algorithms on distributed memory using packed storage. B. Kagstrom, E. Elmroth, editors, Computational Science - PARA '06, Lecture Notes in Computer Science. Springer-Verlag, 2007. To appear.
18. Greg Henry. BLAS based on block data structures. Theory Center Technical Report CTC92TR89, Cornell University, February 1992.
19. José Ramón Herrero. A framework for efficient execution of matrix computations. PhD thesis, Polytechnic University of Catalonia, Spain, 2006.
20. Jakub Kurzak and Jack Dongarra. Implementing linear algebra routines on multi-core processors with pipelining and a look ahead. LAPACK Working Note 178 UT-CS-06-581, University of Tennessee, September 2006.
21. Charles Leiserson and Aske Plaat. Programming parallel applications in Cilk. SINEWS: SIAM News, 31, 1998.
22. Tze Meng Low and Robert van de Geijn. An API for manipulating matrices stored by blocks. FLAME Working Note #12 TR-2004-15, The University of Texas at Austin, Department of Computer Sciences, May 2004.
23. Honghui Lu, Alan L. Cox, Sandhya Dwarkadas, Ramakrishnan Rajamony, and Willy Zwaenepoel. Compiler and software distributed shared memory support for irregular applications. In PPOPP '97: Proceedings of the Sixth ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, pages 48-56, New York, NY, USA, 1997.
24. N. Park, B. Hong, and V. K. Prasanna. Tiling, block data layout, and memory hierarchy performance. IEEE Transactions on Parallel and Distributed Systems, 14(7):640-654, 2003.
25. Peter Strazdins. A comparison of lookahead and algorithmic blocking techniques for parallel matrix factorization. International Journal of Parallel and Distributed Systems and Networks, 4(1):26-35, June 2001.
26. R. Tomasulo. An efficient algorithm for exploiting multiple arithmetic units. IBM Journal of Research and Development, 11(1), 1967.
27. Vinod Valsalam and Anthony Skjellum. A framework for high-performance matrix multiplication based on hierarchical abstractions, algorithms and optimized low-level kernels. Concurrency and Computation: Practice and Experience, 14(10):805-840, 2002.
28. Robert A. van de Geijn. Using PLAPACK: Parallel Linear Algebra Package. The MIT Press, 1997.
29. Reinhard von Hanxleden, Ken Kennedy, Charles H. Koelbel, Raja Das, and Joel H. Saltz. Compiler analysis for irregular problems in Fortran D. In 1992 Workshop on Languages and Compilers for Parallel Computing, number 757, pages 97-111, New Haven, CT, USA, 1992.