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PVLDB
2008
182views more  PVLDB 2008»
15 years 6 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,...
CG
2008
Springer
15 years 6 months ago
Masked photo blending: Mapping dense photographic data set on high-resolution sampled 3D models
The technological advance of sensors is producing an exponential size growth of the data coming from 3D scanning and digital photography. The production of digital 3D models consi...
Marco Callieri, Paolo Cignoni, Massimiliano Corsin...
CGA
1999
15 years 6 months ago
Visualizing Large Telecommunication Data Sets
displays to abstract network data and let users interactwithit.Wehaveimplementedafull-scaleSwift3D prototype, which generated the examples we present here. Swift-3D We developed Sw...
Eleftherios Koutsofios, Stephen C. North, Daniel A...
DAC
2011
ACM
14 years 6 months ago
Supervised design space exploration by compositional approximation of Pareto sets
Technology scaling allows the integration of billions of transistors on the same die but CAD tools struggle in keeping up with the increasing design complexity. Design productivit...
Hung-Yi Liu, Ilias Diakonikolas, Michele Petracca,...
BMCBI
2004
196views more  BMCBI 2004»
15 years 6 months ago
MUSCLE: a multiple sequence alignment method with reduced time and space complexity
Background: In a previous paper, we introduced MUSCLE, a new program for creating multiple alignments of protein sequences, giving a brief summary of the algorithm and showing MUS...
Robert C. Edgar