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Abstract: . We present a unified approach for expressing high performance numerical linear algebra routines for a class of dense and sparse matrix formats and shapes. As with the Standard Template Library [7], we explicitly separate algorithms from data structures through the use of generic programming techniques. We conclude that such an approach does not hinder high performance. On the contrary, writing portable high performance codes is actually enabled with such an approach because the performance... (Update)
Context of citations to this paper: More
...imperative languages. 1 Introduction In our experience developing high performance numerical libraries for objectoriented languages [17, 14] we have found that industrial compilers fail to eliminate abstraction reliably. In fact, the best optimizing compilers, while achieving...
...is generic programming using templates that support meta programming. This is in some way a typed extension to C macros, cf. [103, 105, 113, 120]. Templates enable parameterization in ways not supported by regular classes. Template parameters can be seen as place holders that...
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BibTeX entry: (Update)
Jeremy G. Siek and Andrew Lumsdaine. The matrix template library: A unifying framework for numerical linear algebra. In Parallel Object Oriented Scientific Computing. ECOOP, 1998. http://citeseer.ist.psu.edu/siek98matrix.html More
@inproceedings{ siek98matrix,
author = "Jeremy G. Siek and Andrew Lumsdaine",
title = "The Matrix Template Library: A Unifying Framework for Numerical Linear Algebra",
booktitle = "{ECOOP} Workshops",
pages = "466-467",
year = "1998",
url = "citeseer.ist.psu.edu/siek98matrix.html" }
Citations (may not include all citations):
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