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http://dx.doi.org/10.18419/opus-9490
Autor(en): | Tkachev, Gleb |
Titel: | Investigation and prediction of distributed volume rendering performance |
Erscheinungsdatum: | 2017 |
Dokumentart: | Abschlussarbeit (Master) |
Seiten: | 65 |
URI: | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-95077 http://elib.uni-stuttgart.de/handle/11682/9507 http://dx.doi.org/10.18419/opus-9490 |
Zusammenfassung: | In this work, I describe the process of developing a cluster scalability model that is capable of predicting performance of a parallel rendering application running on a cluster while only having data that can be obtained from one of its nodes. I begin by studying scaling behavior of a single cluster, employing linear regression and neural networks to construct a cluster-specific scalability model, which im-plicitly captures its hardware characteristics. I use this model as a foundation for further work, developing a hardware-agnostic cluster scalability model. Instead of using explicit hardware characteristics as input, the hardware-agnostic model takes in a distribution of node computation time, which encapsulates local computational load of a rendering application, enabling the model to focus on pre-dicting communication overhead of a cluster. This allows simulation of different hardware by varying the node computation time, gathering enough data to train a neural network that predicts the overall performance of the rendering application on a cluster with arbitrary node hardware. |
Enthalten in den Sammlungen: | 05 Fakultät Informatik, Elektrotechnik und Informationstechnik |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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Investigation and prediction of distributed volume rendering performance.pdf | 1,72 MB | Adobe PDF | Öffnen/Anzeigen |
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