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Active learning processes to study memory hierarchy on Multicore systems
Author(s) -
John Corredor,
Juan Carlos Moure,
Dolores Rexachs,
Daniel Franco,
Emilio Luque
Publication year - 2010
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2010.04.101
Subject(s) - computer science , multi core processor , memory hierarchy , hierarchy , artificial intelligence , theoretical computer science , machine learning , computer architecture , human–computer interaction , parallel computing , cache , economics , market economy
A current challenge for computer users is to fully exploit performance of new Multicore systems. We propose a methodology for students in computational science to analyze the effect of memory hierarchy on application performance. The analysis is proposed in a experimental environment consisting of different systems with different configurations of memory hierarchy. New Multicore systems put tremendous pressure on memory hierarchy systems. The pressure is because, unfortunately, the effectiveness of the computing power offered by Multicore is affected by the data communications inter-chip and off-chip to the memory hierarchy, leading to significant problems in performance for many parallel applications. In the scope of computer science, it is important that students understand these problems. This methodology was successfully applied to students, where they acquired a significant improvement in their parallel application metrics assessment as was demonstrated in our evaluation

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