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Auto-tuning techniques for linear algebra routines on hybrid platforms

  • Published:2015-09 Issue: Volume:10 Page:299-310
  • ISSN:1877-7503
  • Container-title:Journal of Computational Science
  • language:en
  • Short-container-title:Journal of Computational Science

Author:

Bernabé Gregorio,Cuenca Javier,García Luis-Pedro,Giménez Domingo

Funder

Spanish MINECO

European Commission FEDER funds

Publisher

Elsevier BV

Subject

Modelling and Simulation,General Computer Science,Theoretical Computer Science

Reference35 articles.

1. Optimizing matrix multiply using PHiPAC: a portable, high-performance, ANSI C coding methodology;Bilmes,1997

2. Optimización automática de software paralelo de álgebra lineal (in Spanish);Cuenca Muñoz,2005

3. Automatic tuning of PDGEMM towards optimal performance;Hunold,2005

4. Fiber: a generalized framework for auto-tuning software;Katagiri;Springer LNCS,2003

5. Automated empirical optimizations of software and the ATLAS project;Whaley;Parallel Comput.,2001

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1. Matrix-Based Evolutionary Computation;IEEE Transactions on Emerging Topics in Computational Intelligence;2021

2. On the Autotuning of Task-Based Numerical Libraries for Heterogeneous Architectures;Parallel Computing: Technology Trends;2020-03-20

3. Integrating software and hardware hierarchies in an autotuning method for parallel routines in heterogeneous clusters;The Journal of Supercomputing;2020-03-07

4. A self-optimized software tool for quantifying the degree of left ventricle hyper-trabeculation;The Journal of Supercomputing;2018-12-17

5. Guided installation of basic linear algebra routines in a cluster with manycore components;Concurrency and Computation: Practice and Experience;2017-03-03
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