Efficient grouping-based mapping and scheduling on heterogeneous cluster architectures
Heterogeneous clusters of computers usually provide high computing power for large-scale applications at the expense of large cost. And there are two challenges currently faced by researchers. One is how to map large applications, modeled by Directed Acyclic Graphs (DAG), to heterogeneous architectu...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Sun, Qunyan [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2014 |
|---|
| Umfang: |
17 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Brain-derived microvesicles confer sickness behaviours by switching on the acute phase response in the liver - Couch, Yvonne ELSEVIER, 2014, an international journal, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:40 ; year:2014 ; number:5 ; pages:1604-1620 ; extent:17 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.compeleceng.2014.03.009 |
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Efficient grouping-based mapping and scheduling on heterogeneous cluster architectures |
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Heterogeneous clusters of computers usually provide high computing power for large-scale applications at the expense of large cost. And there are two challenges currently faced by researchers. One is how to map large applications, modeled by Directed Acyclic Graphs (DAG), to heterogeneous architectures with minimal cost. The other is how to schedule tasks on each cluster to further decrease the total cost. |
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Heterogeneous clusters of computers usually provide high computing power for large-scale applications at the expense of large cost. And there are two challenges currently faced by researchers. One is how to map large applications, modeled by Directed Acyclic Graphs (DAG), to heterogeneous architectures with minimal cost. The other is how to schedule tasks on each cluster to further decrease the total cost. |
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Heterogeneous clusters of computers usually provide high computing power for large-scale applications at the expense of large cost. And there are two challenges currently faced by researchers. One is how to map large applications, modeled by Directed Acyclic Graphs (DAG), to heterogeneous architectures with minimal cost. The other is how to schedule tasks on each cluster to further decrease the total cost. |
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