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» Co-Scheduling of Computation and Data on Computer Clusters
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148
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BMCBI
2010
139views more  BMCBI 2010»
15 years 3 months ago
A highly efficient multi-core algorithm for clustering extremely large datasets
Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
Johann M. Kraus, Hans A. Kestler
159
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CLUSTER
2004
IEEE
15 years 7 months ago
A distributed data management middleware for data-driven application systems
A key challenge in supporting data-driven scientific applications is the storage and management of input and output data in a distributed environment. In this paper, we describe a...
Stephen Langella, Shannon Hastings, Scott Oster, T...
122
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DATAMINE
1999
113views more  DATAMINE 1999»
15 years 3 months ago
A Fast Parallel Clustering Algorithm for Large Spatial Databases
The clustering algorithm DBSCAN relies on a density-based notion of clusters and is designed to discover clusters of arbitrary shape as well as to distinguish noise. In this paper,...
Xiaowei Xu, Jochen Jäger, Hans-Peter Kriegel
150
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ICCV
2009
IEEE
15 years 1 months ago
Learning with dynamic group sparsity
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas
CLUSTER
2006
IEEE
15 years 7 months ago
Efficient Data-Movement for Lightweight I/O
Efficient data movement is an important part of any highperformance I/O system, but it is especially critical for the current and next-generation of massively parallel processing ...
Ron Oldfield, Patrick Widener, Arthur B. Maccabe, ...