Transformer: A New Paradigm for Building Data-Parallel Programming Models
- 19 August 2010
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Micro
- Vol. 30 (4), 55-64
- https://doi.org/10.1109/mm.2010.75
Abstract
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.Keywords
This publication has 9 references indexed in Scilit:
- PregelPublished by Association for Computing Machinery (ACM) ,2009
- The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale MachinesSynthesis Lectures on Computer Architecture, 2009
- Pig latinPublished by Association for Computing Machinery (ACM) ,2008
- All-pairs: An abstraction for data-intensive cloud computing2008 IEEE International Symposium on Parallel and Distributed Processing, 2008
- Technical perspectiveCommunications of the ACM, 2008
- DryadPublished by Association for Computing Machinery (ACM) ,2007
- Interpreting the Data: Parallel Analysis with SawzallScientific Programming, 2005
- Advances in dataflow programming languagesACM Computing Surveys, 2004
- ActorsPublished by MIT Press ,1986