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Modeling the benefits of mixed data and task parallelism
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Source ACM Symposium on Parallel Algorithms and Architectures archive
Proceedings of the seventh annual ACM symposium on Parallel algorithms and architectures table of contents
Santa Barbara, California, United States
Pages: 74 - 83  
Year of Publication: 1995
ISBN:0-89791-717-0
Authors
Soumen Chakrabarti  Computer Science Division, U. C. Berkeley, CA
James Demmel  Computer Science Division and Mathematics Department, U. C. Berkeley, CA
Katherine Yelick  Computer Science Division, U. C. Berkeley, CA
Sponsors
European Theoretical :
IEEE : Institute of Electrical and Electronics Engineers
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 2,   Downloads (12 Months): 31,   Citation Count: 15
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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Z. Bat and J. Demmel. Design of a parallel nonsymmetric eigenroutine toolbox, Part I. In Proceedings of the Sixth SIAM Conference on Parallel Proceesmg for Scientific Computing. SIAM, 1993.
 
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K. BelkhaIe and P. Banerjee. An approximate algorithm for the partitionable independent task scheduling problem. in International Conference on Parallel Processing (ICPP). IEEE, August 1990. Full version in technical reports UILU-ENG-90-2253 and CRHC-90-15, University of illinois, Urbana.
 
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C. Bischof, S. Huss-Lederman, X. Sun, A. Tsao, and T. TurnbulI. Parallel performance of a symmetric eigensolver based on the invariant subspace decomposition approach. In Scalable High Performance Computing Conference, pages 32-39, Knoxville, TN, May 1994. IEEE.
 
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S. Chatterjee. Compiling data-parallel programs for efficient execution on shared-memory multiprocessors. Technical Report CMU-CS-91-189, CMU, Pittsburgh, PA 15213, October 1991.
 
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J. Cuppen. A divide and conquer method for the symmetric tridiagonal eigenproblem. Numer. Math., 36:177-195, 1981.
 
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J. Demmel, J. Dongarra, R. van de Geijn, and D. Walker. LAPACK for distributed memory machines: the next generation. In Proceedings of the Sixth SIAM Conference on Parallel Proceesing for Scientific Computing. SIAM, 1993.
 
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J. Demmel and K. Stanley. The performance of finding eigenvalues and eigenvectors of dense symmetric matrices on distributed memory computers. In Proceedings of the Seventh SIAM Conference on Parallel Proceesing .for Scientific Computing. SIAM, 1994.
 
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I. Foster, M. Xu, B. Avalani, and A. Chowdhary. A compilation system that integrates high performance Fortran and Fortran M. in Scalable High Performance Computing Conference, pages 293-300. IEEE, 1994.
 
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C. R. Mechoso, C.-C. Ma, J. Farrara, J. A. Spahr, and R. W. Moore. Parallelization and distribution of a coupled atmosphere-ocean general circulation model. Monthly Weather Review, 121(7):2062-2076, 1993.
 
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S. Ramaswamy, S. Sapatnekar, and P. Banerjee. A convex programming approach for exploiting data and functional parallelism on distributed memory multiprocessors. In International Conference on Parallel Processing (ICPP). IEEE, 1994.
 
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J. P#utter. A serial implementation of Cuppen's divide and conquer algorithm for the symmetric eigenvalue problem. Mathematics Dept. Master's Thesis available by anonymous ftp to tr-ftp.cs.berkeley.edu, directory pub/techreports/cs/csd-94-799, file all.ps, University of California, 1994.
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K. Stanley and J. Demmel. Modeling the performance of linear systems solvers on distributed memory multiprocessots. Technical report, University of California, Berkeley, CA 94720, 1994. In preparation.
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CITED BY  15

Collaborative Colleagues:
Soumen Chakrabarti: colleagues
James Demmel: colleagues
Katherine Yelick: colleagues