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» Breakpoints and Time in Distributed Computations
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SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
13 years 3 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
ICPADS
1998
IEEE
15 years 4 months ago
The XBW Model for Dependable Real-Time Systems
This paper presents a new conceptual model, the XBWModel. Distributed computing is becoming a cost effective way to implement safety critical control systems. To support the devel...
Vilgot Claesson, Stefan Poledna, Jan Söderber...
PRDC
2002
IEEE
15 years 5 months ago
Reliability Analysis of Grid Computing Systems
Grid computing system is different from conventional distributed computing systems by its focus on large-scale resource sharing, where processors and communication have significan...
Y. S. Dai, Min Xie, Kim-Leng Poh
IPPS
2007
IEEE
15 years 7 months ago
Expected Time for Obtaining Dependable Data in Real-Time Environment
In real-time environment, data usually has a lifespan associated with it. The semantics and the importance of the data depend on the time when data is utilized. Hence, the process...
Yue Yu, Shangping Ren
89
Voted
IPPS
2000
IEEE
15 years 5 months ago
Using Time Skewing to Eliminate Idle Time due to Memory Bandwidth and Network Limitations
Time skewing is a compile-time optimization that can provide arbitrarily high cache hit rates for a class of iterative calculations, given a sufficient number of time steps and s...
David Wonnacott