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An updated set of basic linear algebra subprograms (BLAS)

Published: 01 June 2002 Publication History
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References

[1]
HP BLAS. http://www.compaq.com/math/documentation/cxml/dxml.3dxml.html.
[2]
IBM BLAS. http://www-1.ibm.com/servers/eserver/pseries/library/sp_books/essl.html.
[3]
Intel BLAS. http://developer.intel.com/software/products/mkl/mkl52/index.htm.
[4]
SGI BLAS. http://www.sgi.com/software/scsl.html.
[5]
SUN BLAS. http://docs.sun.com/htmlcoll/coll.118.3/iso-8859-1/PERFLIBUG/plug_bookTOC.html.
[6]
Anderson, E., Bai, Z., Bischof, C., Blackford, S., Demmel, J., Dongarra, J., Du Croz, J., Greenbaum, A., Hammarling, S., McKenney, A., and Sorensen, D. 1999. LAPACK Users' Guide. SIAM, Philadelphia, PA, USA, third edition. (Also available in Japanese, published by Maruzen, Tokyo, translated by Dr Oguni).
[7]
ANSI/IEEE Std 754--1985. IEEE Standard for Binary Floating Point Arithmetic.
[8]
Blackford, S., Corliss, G., Demmel., J., Dongarra, J., Duff, I., Hammarling, S., Henry, G., Heroux, M., Hu, C., Kahan, W., Kaufmann, L., Kearfott, B., Krogh, F., Li, X., Maany, Z., Petitet, A., Pozo, R., Remington, K., Walster, W., Whaley, C., Wolff, V., Gudenberg, J., and Lumsdaine, A. 2002. Basic Linear Algebra Subprograms Technical (BLAST) Forum Standard. Int. J. High Perform. Comput. 16, 1--2. (also available at www.netlib.org/blas/blast-forum).
[9]
Demmel, J. 1997. Applied Numerical Linear Algebra. SIAM, Philadelphia, Pa.
[10]
Dodson, D. S. 1983. Corrigendum: Remark on "Algorithm 539: Basic linear algebra subroutines for FORTRAN usage". ACM Trans. Math. Software 9, 140. (See also Lawson et al. {1979} and Dodson and Grimes {1982}).
[11]
Dodson, D. S. and Grimes, R. G. 1982. Remark on algorithm 539: Basic linear algebra subprograms for Fortran usage. ACM Trans. Math. Softw. 8, 403--404. (See also Lawson et al. {1979} and Dodson {1983}).
[12]
Dodson, D. S., Grimes, R. G., and Lewis, J. G. 1991. Sparse extensions to the FORTRAN basic linear algebra subprograms. ACM Trans. Math. Software 17, 253--272. (Algorithm 692).
[13]
Dongarra, J. J., Bunch, J. R., Moler, C. B., and Stewart, G. W. 1979. LINPACK Users' Guide. Society for Industrial and Applied Mathematics, Philadelphia, Pa.
[14]
Dongarra, J. J., Du Croz, J., Duff, I. S., and Hammarling, S. 1990. A set of Level 3 basic linear algebra subprograms. ACM Trans. Math. Softw. 16, 1--28. (Algorithm 679).
[15]
Dongarra, J. J., Du Croz, J., Hammarling, S., and Hanson, R. J. 1988. An extended set of FORTRAN basic linear algebra subprograms. ACM Trans. Math. Softw. 14, 1--32, 399. (Algorithm 656).
[16]
Duff, I. S., Heroux, M. A., and Pozo, R. 2002. An overview of the sparse basic linear algebra subprograms: The new standard from the BLAS Technical Forum. ACM Trans. Math. Softw. 28, 2 (June), 000--000.
[17]
Duff, I. S., Marrone, M., Radicati, G., and Vittoli, C. 1997. Level 3 basic linear algebra subprograms for sparse matrics: A user-level interface. ACM Trans. Math. Softw. 23, 379--401.
[18]
Golub, G. and van Loan, C. 1996. Matrix Computations. 3rd ed. Johns-Hopkins, Baltimore, Md.
[19]
Higham, N. J. 1996. Accuracy and Stability of Numerical Algorithms. SIAM, Philadelphia, Pa.
[20]
Kåagström, B., Ling, P., and Van Loan, C. 1998a GEMM-based level 3 BLAS: High-performance model implementations and performance evaluation benchmark. ACM Trans. Math. Softw. 24, 3, 268--302.
[21]
Kåagström, B., Ling, P., and Van Loan, C. 1998b. Algorithm 784: GEMM-based level 3 BLAS: Portability and optimization issues. ACM Trans. Math. Softw. 24, 3, 303--316.
[22]
Lawson, C. L., Hanson, R. J., Kincaid, D., and Krogh, F. T. 1979. Basic linear algebra subprograms for FORTRAN usage. ACM Trans. Math. Softw. 5, 308--323. (Algorithm 539. See also Dodson and Grimes {1982} and Dodson {1983}.).
[23]
Li X. S., Demmel, J. W., Bailey, D. H., Henry, G., Hida, Y., Iskandar, J., Kahan, W., Kang, S. Y., Kapur, A., Martin, M. C., Thompson, B. J., Tung, T., and Yod, D. J. 2002. Design, implementation and testing of extended and mixed precision BLAS. ACM Trans. Math. Softw. 28, 2 (June), 000--000.
[24]
Robert III, H. M., Evans, W. J., Honemann, D. H., and Balch, T. J. 2000. Robert's Rules of Order 10th ed. Perseus Book Group

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Jesse Louis Barlow

The basic linear algebra subroutines (BLAS) have become an essential part of the development of numerical software in Fortran, and in other languages that have versions of them. Their beauty has always been that computer manufacturers have been encouraged to implement the BLAS as efficiently as possible. The BLAS began with the simple observation that a number of vector operations (dot product, Euclidean norm, vector scale, and add) were commonly implemented in numerical software, and thus a set of Fortran subroutines for them with standardized names was proposed [1]. The linear algebraic equation package (LINPACK) project [2] was built around these routines for the sake of modularity and portability. The vector BLAS are now called level-1 BLAS. Level-2 BLAS (matrix-vector operations) [3], and level-3 BLAS (matrix-matrix operations) [4] were developed in tandem with another linear algebra package (LAPACK) project [5]. Conventional wisdom is that numerical algorithm design should take advantage of level-3 BLAS operations to the greatest extent possible, since this reduces the ratio of (costly) memory references to (cheap) arithmetic operations. This paper updates the ongoing BLAS effort, and summarizes what types of operations are now available. We now have flavors of BLAS for dense, banded, and sparse vector and matrix operations. Some BLAS are also supported in extended and mixed precision. That effort is carefully chronicled here, by some of the many contributors to the BLAS. Online Computing Reviews Service

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Published In

cover image ACM Transactions on Mathematical Software
ACM Transactions on Mathematical Software  Volume 28, Issue 2
June 2002
151 pages
ISSN:0098-3500
EISSN:1557-7295
DOI:10.1145/567806
Issue’s Table of Contents

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 2002
Published in TOMS Volume 28, Issue 2

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  1. BLAS
  2. linear algebra
  3. standards

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  • (2024)Temporal-Difference Graph-Based Optimization for High-Quality Reconstruction of MODIS NDVI DataRemote Sensing10.3390/rs1615271316:15(2713)Online publication date: 24-Jul-2024
  • (2024)Solving Millions of Eigenvectors in Large-Scale Quantum-Many-Body-Theory ComputationsISC High Performance 2024 Research Paper Proceedings (39th International Conference)10.23919/ISC.2024.10528945(1-11)Online publication date: May-2024
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