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» Parallel Relative Debugging with Dynamic Data Structures
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NIPS
1998
15 years 3 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
HPDC
2002
IEEE
15 years 7 months ago
A Comparison of TCP Automatic Tuning Techniques for Distributed Computing
Rather than painful, manual, static, per-connection optimization of TCP buffer sizes simply to achieve acceptable performance for distributed applications [8, 10], many researcher...
Eric Weigle, Wu-chun Feng
EUROPAR
1995
Springer
15 years 5 months ago
Bounds on Memory Bandwidth in Streamed Computations
The growing disparity between processor and memory speeds has caused memory bandwidth to become the performance bottleneck for many applications. In particular, this performance ga...
Sally A. McKee, William A. Wulf, Trevor C. Landon
CLUSTER
2003
IEEE
15 years 7 months ago
A Performance Monitor Based on Virtual Global Time for Clusters of PCs
Debugging the performance of parallel and distributed systems remains a difficult task despite the widespread use of middleware packages for automatic distribution, communication...
Michela Taufer, Thomas Stricker
CGF
2010
98views more  CGF 2010»
15 years 2 months ago
Fast Generation of Pointerless Octree Duals
Geometry processing applications frequently rely on octree structures, since they provide simple and efficient hierarchies for discrete data. However, octrees do not guarantee dire...
Thomas Lewiner, Vinícius Mello, Adelailson ...