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» Google's MapReduce programming model - Revisited
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HPCC
2009
Springer
13 years 11 months ago
Kahn Process Networks are a Flexible Alternative to MapReduce
Experience has shown that development using shared-memory concurrency, the prevalent parallel programming paradigm today, is hard and synchronization primitives nonintuitive becaus...
Zeljko Vrba, Pål Halvorsen, Carsten Griwodz,...
CLUSTER
2009
IEEE
14 years 2 months ago
Granules: A lightweight, streaming runtime for cloud computing with support, for Map-Reduce
— Cloud computing has gained significant traction in recent years. The Map-Reduce framework is currently the most dominant programming model in cloud computing settings. In this ...
Shrideep Pallickara, Jaliya Ekanayake, Geoffrey Fo...
HPDC
2010
IEEE
13 years 8 months ago
Multi-GPU volume rendering using MapReduce
In this paper we present a multi-GPU parallel volume rendering implemention built using the MapReduce programming model. We give implementation details of the library, including s...
Jeff A. Stuart, Cheng-Kai Chen, Kwan-Liu Ma, John ...
IPPS
2010
IEEE
13 years 5 months ago
BlobSeer: Bringing high throughput under heavy concurrency to Hadoop Map-Reduce applications
Hadoop is a software framework supporting the Map/Reduce programming model. It relies on the Hadoop Distributed File System (HDFS) as its primary storage system. The efficiency of ...
Bogdan Nicolae, Diana Moise, Gabriel Antoniu, Luc ...
SIGMOD
2011
ACM
210views Database» more  SIGMOD 2011»
12 years 10 months ago
A platform for scalable one-pass analytics using MapReduce
Today’s one-pass analytics applications tend to be data-intensive in nature and require the ability to process high volumes of data efficiently. MapReduce is a popular programm...
Boduo Li, Edward Mazur, Yanlei Diao, Andrew McGreg...