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» Implementing Parallel Google Map-Reduce in Eden
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OSDI
2004
ACM
14 years 5 months ago
MapReduce: Simplified Data Processing on Large Clusters
MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to ge...
Jeffrey Dean, Sanjay Ghemawat
ICPP
2009
IEEE
14 years 7 days ago
Speeding Up Distributed MapReduce Applications Using Hardware Accelerators
—In an attempt to increase the performance/cost ratio, large compute clusters are becoming heterogeneous at multiple levels: from asymmetric processors, to different system archi...
Yolanda Becerra, Vicenç Beltran, David Carr...
IEEEPACT
2008
IEEE
13 years 12 months ago
Mars: a MapReduce framework on graphics processors
We design and implement Mars, a MapReduce framework, on graphics processors (GPUs). MapReduce is a distributed programming framework originally proposed by Google for the ease of ...
Bingsheng He, Wenbin Fang, Qiong Luo, Naga K. Govi...
KDD
2009
ACM
146views Data Mining» more  KDD 2009»
14 years 10 days ago
Mining in a mobile environment
Distributed PRocessing in Mobile Environments (DPRiME) is a framework for processing large data sets across an ad-hoc network. Developed to address the shortcomings of Google’s ...
Sean McRoskey, James Notwell, Nitesh V. Chawla, Ch...
SIGMOD
2010
ACM
207views Database» more  SIGMOD 2010»
13 years 10 months ago
Automatic contention detection and amelioration for data-intensive operations
To take full advantage of the parallelism offered by a multicore machine, one must write parallel code. Writing parallel code is difficult. Even when one writes correct code, the...
John Cieslewicz, Kenneth A. Ross, Kyoho Satsumi, Y...