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» Massively Parallel Data Analysis with PACTs on Nephele
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PVLDB
2008
182views more  PVLDB 2008»
13 years 5 months ago
SCOPE: easy and efficient parallel processing of massive data sets
Companies providing cloud-scale services have an increasing need to store and analyze massive data sets such as search logs and click streams. For cost and performance reasons, pr...
Ronnie Chaiken, Bob Jenkins, Per-Åke Larson,...
BMCBI
2010
153views more  BMCBI 2010»
13 years 6 months ago
Pash 3.0: A versatile software package for read mapping and integrative analysis of genomic and epigenomic variation using massi
Background: Massively parallel sequencing readouts of epigenomic assays are enabling integrative genome-wide analyses of genomic and epigenomic variation. Pash 3.0 performs sequen...
Cristian Coarfa, Fuli Yu, Christopher A. Miller, Z...
IPPS
2007
IEEE
14 years 22 days ago
Pipelining Tradeoffs of Massively Parallel SuperCISC Hardware Functions
Parallel processing using multiple processors is a well-established technique to accelerate many different classes of applications. However, as the density of chips increases, ano...
Colin J. Ihrig, Justin Stander, Alex K. Jones
ICDE
2010
IEEE
227views Database» more  ICDE 2010»
14 years 1 months ago
Incorporating partitioning and parallel plans into the SCOPE optimizer
— Massive data analysis on large clusters presents new opportunities and challenges for query optimization. Data partitioning is crucial to performance in this environment. Howev...
Jingren Zhou, Per-Åke Larson, Ronnie Chaiken
ESANN
2008
13 years 7 months ago
Parallelizing single patch pass clustering
Clustering algorithms such as k-means, the self-organizing map (SOM), or Neural Gas (NG) constitute popular tools for automated information analysis. Since data sets are becoming l...
Nikolai Alex, Barbara Hammer