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11 - Computer Science and Informatics

University of Edinburgh

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Output 64 of 401 in the submission

Article title

Autotuning Skeleton-Driven Optimizations for Transactional Worklist Applications

Type

D - Journal article

DOI

10.1109/TPDS.2012.140

Title of journal

IEEE Transactions on Parallel and Distributed Systems

Article number

Volume number

Issue number

First page of article

2205

ISSN of journal

1045-9219

Year of publication

2012

URL

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6197183

Number of additional authors

Additional information

<08>Originality: The first paper to apply a skeletal approach to software transactional memory (STM) systems.

Significance: STM systems offer a complex performing tuning space. Navigating this space manually negates much of the conceptual simplification offered by the TM programming model. We demonstrate that pattern specific constraints, carried implicitly by our worklist skeleton interface, allow the space to be traversed automatically in a machine and application sensitive way. This opens up a rich seam of research into the exploitation of other application patterns within TM.

Rigour: Real experiments with real benchmarks on real systems. Thorough investigation of underlying architectural performance factors.

Interdisciplinary

Cross-referral requested

Research group

C - Institute for Computing Systems Architecture

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract