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Output details

11 - Computer Science and Informatics

Lancaster University

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Output title

Towards a holistic approach to auto-parallelization: integrating profile-driven parallelism detection and machine-learning based mapping

Type

E - Conference contribution

DOI

10.1145/1542476.1542496

Name of conference/published proceedings

Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2009)

Volume number

Issue number

First page of article

177

ISSN of proceedings

Year of publication

2009

URL

http://doi.acm.org/10.1145/1542476.1542496

Number of additional authors

Additional information

<08> Combines novel dynamic analysis and machine learning based parallelism mapping to develop a completely portable approach to auto-parallelisation, an important problem that has been outstanding for over 30 years. Published in PLDI as one of 41 papers accepted from 194 (21.1%) and won HiPEAC award in recognition of publication in a world-class conference. The significance of this work is reflected in wide citation, and it also included in a recently published book and taught in over 10 universities worldwide. Similar ideas have been adopted by industrial companies such as Vectorfabrics since this work had been published.

Interdisciplinary

Cross-referral requested

Research group

None

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract