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» Optimizing for parallelism and data locality
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CCGRID
2010
IEEE
15 years 3 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...
CLOUD
2010
ACM
15 years 11 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...
170
Voted
ICS
2010
Tsinghua U.
15 years 8 months ago
InterferenceRemoval: removing interference of disk access for MPI programs through data replication
As the number of I/O-intensive MPI programs becomes increasingly large, many efforts have been made to improve I/O performance, on both software and architecture sides. On the sof...
Xuechen Zhang, Song Jiang
150
Voted
JCC
2007
121views more  JCC 2007»
15 years 6 months ago
Speeding up parallel GROMACS on high-latency networks
: We investigate the parallel scaling of the GROMACS molecular dynamics code on Ethernet Beowulf clusters and what prerequisites are necessary for decent scaling even on such clust...
Carsten Kutzner, David van der Spoel, Martin Fechn...
154
Voted
ICDCS
2007
IEEE
16 years 13 days ago
Stabilizing Peer-to-Peer Spatial Filters
In this paper, we propose and prove correct a distributed stabilizing implementation of an overlay, called DR-tree, optimized for efficient selective dissemination of information...
Silvia Bianchi, Ajoy Kumar Datta, Pascal Felber, M...