Lecture 1 in a five part series introducing
mapreduce and cluster computing. See
http://code.google.com/edu/content/submission
s/mapreduce-minilecture/listing.html for
slides and other resources. Tags :mapreducegfshadoopclustercomputingdistributedparallel
Lecture 2: The MapReduce programming model.
See
http://code.google.com/edu/content/submission
s/mapreduce-minilecture/listing.html for
slides and other resources. Tags :mapreducegfshadoopclustercomputingdistributedparallel
Lecture 3: The Google File System. See
http://code.google.com/edu/content/submission
s/mapreduce-minilecture/listing.html for
slides and other resources. Tags :mapreducegfshadoopclustercomputingdistributedparallel
Lecture 4: Clustering Algorithms with
MapReduce. See
http://code.google.com/edu/content/submission
s/mapreduce-minilecture/listing.htmlfor
slides and other resources. Tags :mapreducegfshadoopclustercomputingdistributedparallel
In October 2007, Google announced that it was
partnering with IBM to provide largescale
cluster computing resources to undergraduate
computer science students along with a
creative commons licensed curriculum. Using
the cluster and curriculum as a starting
point, students have been able to develop
some compelling projects. Tags :ibmgoogleacademicclustercomputinginitiativeUWmapreducegfshadoop
A demo of an image processing application
running in a cloud test bed. More information
at:
http://www.hpl.hp.com/open_innovation/cloud_c
ollaboration/ Tags :hadooptycooncartoon
This video showcases a parallel video
processing application running on a cloud
computing platform. More information at:
http://www.hpl.hp.com/open_innovation/cloud_c
ollaboration/ Tags :hadooptycooncartoon