Design of Efficient TLB-based Data Classification Mechanisms in CMPs

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Private/Shared Data Classification

ISBN: 6202017325
ISBN 13: 9786202017329
Autor: Esteve, Albert
Verlag: LAP LAMBERT Academic Publishing
Umfang: 148 S.
Erscheinungsdatum: 16.08.2017
Auflage: 1/2017
Format: 0.9 x 22 x 15
Gewicht: 238 g
Produktform: Kartoniert
Einband: Kartoniert
Artikelnummer: 2768377 Kategorie:

Beschreibung

Most of the data referenced by sequential and parallel applications running in current chip multiprocessors are referenced by a single thread, i.e., private. Recent proposals leverage this observation to improve many aspects of chip multiprocessors, such as reducing coherence overhead or the access latency to distributed caches. The effectiveness of those proposals depends to a large extent on the amount of detected private data. However, the mechanisms proposed so far either do not consider either thread migration or the private use of data within different application phases, or do entail high overhead. As a result, a considerable amount of private data is not detected. In order to increase the detection of private data, this book proposes a TLB-based mechanism that is able to account for both thread migration and private application phases with low overhead. Classification status in the proposed TLB-based classification mechanisms is determined by the presence of the page translation stored in other cores TLBs. The classification schemes are analyzed in multilevel TLB hierarchies, for systems with both private and distributed shared last-level TLBs.

Autorenporträt

Received the M.S. degree and PhD in computer science from the Universitat Politècnica de València, Spain, in 2012 and 2017, respectively. Currently, working as a research technician at the Parallel Architecture Group (GAP) of the Universitat Politècnica de València. Research interests include cache coherence protocols, and CMP architectures.

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