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 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/429/Correlation-Aware-Optimizations-for-Analytic-Databases">
  <title><![CDATA[Correlation Aware Optimizations for Analytic Databases]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/429/Correlation-Aware-Optimizations-for-Analytic-Databases</link>
  <description><![CDATA[Recent years have seen that the analysis of large data-sets is crucially important in a wide range of business, governmental, and scientific applications. For example, research projects in astronomy need to analyze petabytes of image data taken from telescopes. Providing a fast and scalable analytical data management system for such users has become increasingly important.
The major bottlenecks for analytics on such big data are disk- and network-I/O. Because the data is too large to fit in ...]]></description>
  <dc:date>2012-03-09</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/290/Map-Reduce-on-Heterogeneous-Multi-Core-clusters">
  <title><![CDATA[Map Reduce on Heterogeneous Multi-Core clusters]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/290/Map-Reduce-on-Heterogeneous-Multi-Core-clusters</link>
  <description><![CDATA[We have extended the Map Reduce programming paradigm to clusters with
multicore accelerators.  Map Reduce is a simple programming programming
model designed for parallel computations with large distributed datasets. 
Google has reinforced the practical effectiveness of this approach with
over 1000 commercial Map Reduce applications.  Typical Map Reduce
implementations, such as Apache Hadoop exploit parallel file systems for
use in homogeneous clusters.  Unfortunately, the multicore acce...]]></description>
  <dc:date>2009-04-08</dc:date>
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