The matrix template library: A generic programming approach to high performance numerical linear algebra

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1505, Issue , 1998, Pages 59-70

  Siek, Jeremy G ^a   Lumsdaine, Andrew ^a  

^a University of Illinois at Urbana Champaign   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CODES (SYMBOLS); DATA STRUCTURES; OBJECT ORIENTED PROGRAMMING;

ALGORITHMS AND DATA STRUCTURES; GENERIC PROGRAMMING; HIGH PERFORMANCE CODES; NUMERICAL LINEAR ALGEBRA; PERFORMANCE PORTABILITY; STANDARD TEMPLATE LIBRARY; TEMPLATE LIBRARIES; UNIFIED APPROACH;

MATRIX ALGEBRA;

EID: 84947577532     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-49372-7_6     Document Type: Conference Paper

References (19)

1. Meng Lee and Alexander Stepanov. The standard template library. Technical report, HP Laboratories, February 1995.
2. J. Bilmes, K. Asanovic, J. Demmel, D. Lam, and C.-W. Chin. Optimizing matrix multiply using PHiPAC: A portable, high-performance, ANSI C coding methodo-logy. Technical Report CS-96-326, University of Tennessee, May 1996.
3. Jack J. Dongarra R. Clint Whaley. Automatically tuned linear algebra software (ATLAS). Technical report, U. Tennessee and ORNL, 1997.
4. Todd Veldhuizen. Using C++ template metaprograms. C++ Report, May 1995.
5. Basic Linear Algebra Subprograms Technical Forum. BLAS standard draft chap-ter 3: Sparse BLAS. Technical report, University of Tennessee, December 1997.
6. Karen A. Remington and Roldan Pozo. NIST Sparse BLAS User's Guide. Na-tional Institute of Standards and Technology.
7. Brian C. McCandless and Andrew Lumsdaine. The role of abstraction in high-performance computing. In Scientific Computing in Object-Oriented Parallel En-vironments. ISCOPE, December 1997.
8. C. Lawson, R. Hanson, D. Kincaid, and F. Krogh. Basic linear algebra subpro-grams for fortran usage. ACM Trans. Mathematical Software, 5(3): 308-323, 1979.
9. J. Dongarra, J. Du Croz, I. Duff, and S. Hammarling. A set of level 3 basic linear algebra subprograms. ACM Trans. Mathematical Software, 16(1): 1-17, 1990.
10. J. Dongarra, J. Du Croz, S. Hammarling, and R. Hanson. Algorithm 656: An extended set of basic linear algebra subprograms: Model implementations and test programs. ACM Trans. Mathematical Software, 14(1): 18-32, 1988.
11. Roldan Pozo. Template Numerical Toolkit (TNT) for Linear Algebra. National Insitute of Standards and Technology.
12. Kuck and Associates. Kuck and Associates C++ User's Guide.
13. Steven Muchnick. Advanced Compiler Design and Implementation. Morgan Kauf-mann, 1997.
14. Todd Veldhuizen and M. Ed Jernigan. Will C++ be faster than Fortran. In Scientific Computing in Object-Oriented Parallel Environments. ISCOPE, December 1997.
15. Monica S. Lam, Edward E. Rothberg, and Michael E. Wolf. The cache perfor-mance and optimizations of blocked algorithms. In ASPLOS IV, April 1991.
16. NIST. MatrixMarket. http://gams. nist. gov/MatrixMarket/.
17. Youcef Saad. SPARSKIT: a basic tool kit for sparse matrix computations. Tech-nical report, NASA Ames Research Center, 1990.
18. Roldan Pozo Jack Dongarra, Andrew Lumsdaine and Karin A. Remington. Ite-rative Methods Library Reference Guide, v. 1. 2 edition, April 1997.
19. E. Anderson, Z. Bai, C. Bischoff, J. Demmel, J. Dongarra, J. DuCroz, A. Gre-enbaum, S. Hammarling, A. McKenney, and D. Sorensen. LAPACK: A portable linear algebra package for high-performance computers. In Proceedings of Super-computing '90, pages 1-10. IEEE Press, 1990.