FAIR Sharing of Data in Autotuning Research (Vision Paper)
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F24%3A00139198" target="_blank" >RIV/00216224:14610/24:00139198 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1145/3629527.3651429" target="_blank" >http://dx.doi.org/10.1145/3629527.3651429</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3629527.3651429" target="_blank" >10.1145/3629527.3651429</a>
Alternative languages
Result language
angličtina
Original language name
FAIR Sharing of Data in Autotuning Research (Vision Paper)
Original language description
Autotuning is an automated process that selects the best computer program implementation from a set of candidates to improve performance, such as execution time, when run under new circumstances, such as new hardware. The process of autotuning generates a large amount of performance data with multiple potential use cases, including reproducing results, comparing included methods, and understanding the impact of individual tuning parameters. We propose the adoption of FAIR Principles, which stands for Findable, Accessible, Interoperable, and Reusable, to organize the guidelines for data sharing in autotuning research. The guidelines aim to lessen the burden of sharing data and provide a comprehensive checklist of recommendations for shared data. We illustrate three examples that could greatly benefit from shared autotuning data to advance the research without time- and resource-demanding data collection.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
<a href="/en/project/LM2018140" target="_blank" >LM2018140: e-Infrastructure CZ</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
COMPANION OF THE 15TH ACM/SPEC INTERNATIONAL CONFERENCE ON PERFORMANCE ENGINEERING, ICPE COMPANION 2024
ISBN
9798400704451
ISSN
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e-ISSN
—
Number of pages
7
Pages from-to
21-27
Publisher name
ASSOC COMPUTING MACHINERY
Place of publication
NEW YORK
Event location
London, ENGLAND
Event date
May 7, 2024
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
001227617500004