Algorithms for Memory Hierarchies : Advanced Lectures
Algorithms that have to process large data sets have to take into account that the cost of memory access depends on where the data is stored. Traditional algorithm design is based on the von Neumann model where accesses to memory have uniform cost. Actual machines increasingly deviate from this mode...
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| Autres auteurs: | , , |
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| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Collection: | Lecture notes in computer science
2625 |
| Sujets: | |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
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Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Algorithms for memory hierarchies, advanced lectures, Ulrich Meyer, Peter Sanders, Jop Sibeyn (eds.), Berlin, Springer, 2003, 1 vol. (XVII-428 p.), Lecture notes in computer science, 3-540-00883-7 • Algorithms for Memory Hierarchies, Texte imprimé, 9783662190630 |
| Résumé: | Algorithms that have to process large data sets have to take into account that the cost of memory access depends on where the data is stored. Traditional algorithm design is based on the von Neumann model where accesses to memory have uniform cost. Actual machines increasingly deviate from this model: while waiting for memory access, nowadays, microprocessors can in principle execute 1000 additions of registers; for hard disk access this factor can reach six orders of magnitude. The 16 coherent chapters in this monograph-like tutorial book introduce and survey algorithmic techniques used to achieve high performance on memory hierarchies; emphasis is placed on methods interesting from a theoretical as well as important from a practical point of view. |
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| Description: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| ISBN: | 9783540365747 (PDF) |
| ISSN: | 1611-3349 |
| Accès: | Accès en ligne pour les établissements français bénéficiaires des licences nationales Accès soumis à abonnement pour tout autre établissement Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |