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130
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CLOUD
2010
ACM
15 years 7 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...
130
Voted
ICS
2010
Tsinghua U.
15 years 5 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
128
Voted
IPPS
2010
IEEE
15 years 16 days ago
Acceleration of spiking neural networks in emerging multi-core and GPU architectures
Recently, there has been strong interest in large-scale simulations of biological spiking neural networks (SNN) to model the human brain mechanisms and capture its inference capabi...
Mohammad A. Bhuiyan, Vivek K. Pallipuram, Melissa ...
164
Voted
CCGRID
2010
IEEE
15 years 1 days 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...
133
Voted
HPCA
2003
IEEE
16 years 3 months ago
Slipstream Execution Mode for CMP-Based Multiprocessors
Scalability of applications on distributed sharedmemory (DSM) multiprocessors is limited by communication overheads. At some point, using more processors to increase parallelism y...
Khaled Z. Ibrahim, Gregory T. Byrd, Eric Rotenberg