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CLOUD
2010
ACM
15 years 2 months ago
Comet: batched stream processing for data intensive distributed computing
Batched stream processing is a new distributed data processing paradigm that models recurring batch computations on incrementally bulk-appended data streams. The model is inspired...
Bingsheng He, Mao Yang, Zhenyu Guo, Rishan Chen, B...
CCGRID
2009
IEEE
15 years 4 months ago
Performance Issues in Parallelizing Data-Intensive Applications on a Multi-core Cluster
The deluge of available data for analysis demands the need to scale the performance of data mining implementations. With the current architectural trends, one of the major challen...
Vignesh T. Ravi, Gagan Agrawal
CCGRID
2010
IEEE
14 years 7 months ago
Dynamic Load-Balanced Multicast for Data-Intensive Applications on Clouds
Data-intensive parallel applications on clouds need to deploy large data sets from the cloud's storage facility to all compute nodes as fast as possible. Many multicast algori...
Tatsuhiro Chiba, Mathijs den Burger, Thilo Kielman...
MSS
2003
IEEE
90views Hardware» more  MSS 2003»
15 years 3 months ago
NSM: A Distributed Storage Architecture for Data-Intensive Applications
: Several solutions have been developed to provide dataintensive applications with the highest possible data rates. Such solutions tried to utilize the available network resources ...
Zeyad Ali, Qutaibah M. Malluhi
CLUSTER
2008
IEEE
15 years 4 months ago
Supporting storage resources in Urgent Computing Environments
Abstract—The Special PRiority and Urgent Computing Environment (SPRUCE) provides on-demand access to highperformance computing resources for time-critical applications. While SPR...
Jason Cope, Henry M. Tufo