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Design and Implementation of a Performance Visualization Tool for the High-Level Parallel Programming Framework SkePU

Authors: Frankell, Elin;

Design and Implementation of a Performance Visualization Tool for the High-Level Parallel Programming Framework SkePU

Abstract

The rise of parallel programming languages, as a result of processors' flattening clock frequencies, has lead to further use of high-level parallel pattern-based programming framework such as SkePU. SkePU provides a sequential high-level interface connected to different back-ends, or a hybrid of several, which reduces the time required to learn several new programming languages. Although this high-level interface introduces a new problem, an abstraction layer from the user to what code is being executed. To make SkePU programs easier to analyze this thesis implements a performance visualization tool for SkePU. The conducted literature study found that there currently exists very few performance visualization tools that cater specifically towards skeleton programming languages. This thesis evaluates usability of the implemented tool by conducting a survey and a user study with participants whom are very familiar with SkePU. The choice of evaluation method is in itself critically evaluated, as is the design choices made, and results are presented with an accompanying discussion as to how those results were derived. 

Country
Sweden
Keywords

Skeleton programming, Parallel programming languages, Datavetenskap (datalogi), Computer Sciences, SkePU, Performance Visualization Tool

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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!
0
Average
Average
Average
Green