Software automatic tuning : from concepts to state-of-the-art results
Software Automatic Tuning: From Concepts to State-of-the-Art Results Ken Naono Keita Teranishi John Cavazos Reiji Suda It is well known that carefully tuned programs run much faster than ones consisting of simply written code, and sometimes the difference of speed is more 100X. To make things more c...
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| Otros Autores: | , , , |
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| Formato: | Livre numérique |
| Lenguaje: | Anglais |
| Publicado: |
New York, NY :
Springer New York : Imprint: Springer
[20..].
Cham : Springer Nature |
| Acceso en línea: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Software Automatic Tuning, Texte imprimé, 9781441969347 |
| LEADER | 04685nam a22003497a 4500 | ||
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| 245 | 0 | 0 | |a Software automatic tuning : |b from concepts to state-of-the-art results |c edited by Ken Naono, Keita Teranishi, John Cavazos, Reiji Suda. |
| 260 | |a New York, NY : |b Springer New York : |b Imprint: Springer. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Software Automatic Tuning: Concepts and State-of-the-Art Results Achievements in Scientific Computing ATLAS Version 3.9: Overview and Status Autotuning Method for Deciding Block Size Parameters in Dynamically Load-Balanced BLAS Automatic Tuning for Parallel FFTs Dynamic Programming Approaches to Optimizing the Blocking Strategy for Basic Matrix Decompositions Automatic Tuning of the Division Number in the Multiple Division Divide-and-Conquer for Real Symmetric Eigenproblem Automatically Tuned Mixed-Precision Conjugate Gradient Solver Automatically Tuned Sparse Eigensolvers Systematic Performance Evaluation of Linear Solvers Using Quality Control Techniques Application of Alternating Decision Trees in Selecting Sparse Linear Solvers Toward Automatic Performance Tuning for Numerical Simulations in the SILC Matrix Computation Framework Exploring Tuning Strategies for Quantum Chemistry Computations Automatic Tuning of CUDA Execution Parameters for Stencil Processing Static Task Cluster Size Determination in Homogeneous Distributed Systems Evolution to a General Paradigm Algorithmic Parameter Optimization of the DFO Method with the OPAL Framework A Bayesian Method of Online Automatic Tuning ABCLibScript: A Computer Language for Automatic Performance Tuning Automatically Tuning Task-Based Programs for Multicore Processors Efficient Program Compilation Through Machine Learning Techniques Autotuning and Specialization: Speeding up Matrix Multiply for Small Matrices with Compiler Technology | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a Software Automatic Tuning: From Concepts to State-of-the-Art Results Ken Naono Keita Teranishi John Cavazos Reiji Suda It is well known that carefully tuned programs run much faster than ones consisting of simply written code, and sometimes the difference of speed is more 100X. To make things more complex, well-tuned code for some machines performs badly on others. "Automatic Performance Tuning" is a technology paradigm that enables software to tune itself to its environments so that it performs well on any computer, even on computers unknown to the programmer. This book summarizes the research efforts to date and state of the art of automatic performance tuning. Software developers and researchers in the area of scientific and technical computing, optimized compilers, high performance systems software, and low-power computing will find this book to be an invaluable reference to this powerful new paradigm. Presents the first English collaboration on the powerful, new software paradigm of Automatic Performance Tuning; Offers a comprehensive survey of fundamental concepts and state-of-the-art results from the field; Enables programmers to create software that will tune itself to its environments so that it performs well on any computer | ||
| 700 | 1 | |a Naono, Ken. |4 pbd | |
| 700 | 1 | |a Teranishi, Keita. |4 pbd | |
| 700 | 1 | |a Cavazos, John. |4 pbd | |
| 700 | 1 | |a Suda, Reiji. |4 pbd | |
| 776 | 0 | |t Software Automatic Tuning |b Texte imprimé |z 9781441969347 | |
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