The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Minimizing development and maintenance costs in supporting persistently optimized BLAS
Abstract
The Basic Linear Algebra Subprograms (BLAS) define one of the most heavily used performance-critical APIs in scientific computing today. It has long been understood that the most important of these routines, the dense Level 3 BLAS, may be written efficiently given a highly optimized general matrix multiply routine. In this paper, however, we show that an even larger set of operations can be efficiently maintained using a much simpler matrix multiply kernel. Indeed, this is how our own project, ATLAS (which provides one of the most widely used BLAS implementations in use today), supports a large variety of performance-critical routines. Copyright © 2004 John Wiley & Sons, Ltd.
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Citations
Cites
Automated empirical optimizations of software and the ATLAS project
Clint Whaley, R., Petitet, A., & Dongarra, J. J. (2001) · Parallel Computing · doi:10.1016/s0167-8191(00)00087-9 · Cited by 1,317
Self-citation
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Shabalin, A. A. (2011) · arXiv (Cornell University) · doi:10.17615/g28n-r219 · Cited by 452
Self-Adapting Linear Algebra Algorithms and Software
Demmel, J., Dongarra, J., Eijkhout, V., Fuentes, E., Petitet, A., Vuduc, R., Whaley, R. C., & Yelick, K. (2005) · Proceedings of the IEEE · doi:10.1109/jproc.2004.840848 · Cited by 204
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Delor, M., Scattergood, P. A., Sazanovich, I. V., Parker, A. W., Greetham, G. M., Meijer, A. J. H. M., Towrie, M., & Weinstein, J. A. (2014) · Science · doi:10.1126/science.1259995 · Cited by 199
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Metadata
- Authors
- Whaley, R. C., & Petitet, A.
- Venue
- Software: Practice and Experience
- Publisher
- Wiley
- Published
- 2005
- Volume
- 35
- Issue
- 2
- Pages
- 101-121
- ISSN
- 0038-0644 (ISSN-L)
- 1097-024X
- OpenAlex
- W2119395117
- Cited by
- 254
- References
- 1
- FWCI
- 16.88
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
