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...

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Bibliographic Details
Published in:IEEE MICRO Vol. 30; no. 4; pp. 55 - 64
Main Authors: Wang, Peng, Meng, Dan, Han, Jizhong, Zhan, Jianfeng, Tu, Bibo, Shi, Xiaofeng, Wan, Le
Format: Journal Article
Language:English
Published: Los Alamitos IEEE 01.07.2010
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
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 Access:Get full text
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Summary: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.
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ISSN:0272-1732
1937-4143
DOI:10.1109/MM.2010.75