Empirical Installation of Linear Algebra Shared-Memory Subroutines for Auto-Tuning

Author:

Cámara Jesús,Cuenca Javier,Giménez Domingo,García Luis Pedro,Vidal Antonio M.

Publisher

Springer Science and Business Media LLC

Subject

Information Systems,Theoretical Computer Science,Software

Reference29 articles.

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2. Alberti, P., Alonso, P., Vidal, A.M., Cuenca, J., Giménez, D.: Designing polylibraries to speed up linear algebra computations. Int. J. High Perform. Comput. Netw. 1/2/3(1), 75–84 (2004)

3. Anderson, E., Bai, Z., Bischof, C., Demmel, J., Dongarra, J.J., Du Croz, J., Grenbaum, A., Hammarling, S., McKenney, A., Ostrouchov, S., D. Sorensen, S.: LAPACK User’s Guide. Society for Industrial and Applied Mathematics, Philadelphia (1995)

4. Bernabé, G., Cuenca, J., Giménez, D.: Optimization techniques for 3D-FWT on systems with manycore GPUs and multicore CPUs. In: ICCS (2013)

5. Buttari, A., Langou, J., Kurzak, J., Dongarra, J.: A class of parallel tiled linear algebra algorithms for multicore architectures. Parallel Comput. 35(1), 38–53 (2009)

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3. On Guided Installation of Basic Linear Algebra Routines in Nodes with Manycore Components;Proceedings of the 7th International Workshop on Programming Models and Applications for Multicores and Manycores;2016-03-12

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