Transformer: A New Paradigm for Building Data-Parallel Programming Models

Cloud computing drives the design and development of diverse programming models for massive data processing. the transformer programming framework aims to facilitate the building of diverse data-parallel programming models. transformer has two layers: a common runtime system and a model-specific sys...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE MICRO Jg. 30; H. 4; S. 55 - 64
Hauptverfasser: Wang, Peng, Meng, Dan, Han, Jizhong, Zhan, Jianfeng, Tu, Bibo, Shi, Xiaofeng, Wan, Le
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Los Alamitos IEEE 01.07.2010
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
actor model
All-Pairs
Cloud computing
Clouds
Computation
Computational modeling
data flow
data intensive computing
Data models
Data processing
Design engineering
Libraries
Load modeling
MapReduce
Mathematical models
Parallel processing
Programming
Programming languages
programming model
Receivers
Runtime
Transformers
ISSN:0272-1732, 1937-4143
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Cloud computing drives the design and development of diverse programming models for massive data processing. the transformer programming framework aims to facilitate the building of diverse data-parallel programming models. transformer has two layers: a common runtime system and a model-specific system. using transformer, the authors show how to implement three programming models: dryad-like data flow, MapReduce, and All-Pairs.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-2
content type line 23
ISSN:0272-1732
1937-4143
DOI:10.1109/MM.2010.75