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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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https://doi.org/10.5281/zenodo...
Dataset . 2021
License: CC BY
Data sources: Sygma
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PyCOMPSs Performance Models

Research datakeyboard_double_arrow_right Dataset 31 Dec 2021Publisher:ZenodoFunded by:EC | AI-SPRINT
Authors: Filippini, Federica; Sedghani, Hamta; Ardagna, Danilo; Lezzi, Daniele;

doi: 10.5281/zenodo.5760964 , 10.5281/zenodo.5760963

PyCOMPSs Performance Models

Abstract

The repository includes the source code and the datasets used to build performance models for PyCOMPSs applications. The results are included in the AI-SPRINT project deliverable "D2.1 - First release and evaluation of the AI-SPRINT design tools".

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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