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» Clustering performance data efficiently at massive scales
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ECCV
2010
Springer
15 years 7 months ago
Texture Regimes for Entropy-Based Multiscale Image Analysis
We present an approach to multiscale image analysis. It hinges on an operative definition of texture that involves a "small region", where some (unknown) statistic is agg...
Sylvain Boltz, Frank Nielsen, Stefano Soatto
NSDI
2010
15 years 7 months ago
Cheap and Large CAMs for High Performance Data-Intensive Networked Systems
We show how to build cheap and large CAMs, or CLAMs, using a combination of DRAM and flash memory. These are targeted at emerging data-intensive networked systems that require mas...
Ashok Anand, Chitra Muthukrishnan, Steven Kappes, ...
EXPDB
2006
ACM
15 years 12 months ago
Performance Study of Rollout for Multi Dimensional Clustered Tables in DB2
In data warehousing applications, the ability to efficiently delete large chunks of data from a table is very important. This feature is also known as Rollout. Rollout is generall...
Bishwaranjan Bhattacharjee
EUROPAR
2007
Springer
16 years 5 days ago
Experiences Understanding Performance in a Commercial Scale-Out Environment
Abstract. Clusters of loosely connected machines are becoming an important model for commercial computing. The cost/performance ratio makes these scale-out solutions an attractive ...
Robert W. Wisniewski, Reza Azimi, Mathieu Desnoyer...
ICDE
2010
IEEE
227views Database» more  ICDE 2010»
16 years 26 days 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