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» Optimizing for parallelism and data locality
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88
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ICDM
2006
IEEE
89views Data Mining» more  ICDM 2006»
15 years 6 months ago
On the Lower Bound of Local Optimums in K-Means Algorithm
The k-means algorithm is a popular clustering method used in many different fields of computer science, such as data mining, machine learning and information retrieval. However, ...
Zhenjie Zhang, Bing Tian Dai, Anthony K. H. Tung
108
Voted
ICPP
1998
IEEE
15 years 4 months ago
Concurrent SSA Form in the Presence of Mutual Exclusion
Most current compiler analysis techniques are unable to cope with the semantics introduced by explicit parallel and synchronization constructs in parallel programs. In this paper ...
Diego Novillo, Ronald C. Unrau, Jonathan Schaeffer
130
Voted
ICS
2007
Tsinghua U.
15 years 6 months ago
Performance driven data cache prefetching in a dynamic software optimization system
Software or hardware data cache prefetching is an efficient way to hide cache miss latency. However effectiveness of the issued prefetches have to be monitored in order to maximi...
Jean Christophe Beyler, Philippe Clauss
110
Voted
HPCA
2008
IEEE
16 years 1 months ago
Performance and power optimization through data compression in Network-on-Chip architectures
The trend towards integrating multiple cores on the same die has accentuated the need for larger on-chip caches. Such large caches are constructed as a multitude of smaller cache ...
Reetuparna Das, Asit K. Mishra, Chrysostomos Nicop...
ICDE
2005
IEEE
110views Database» more  ICDE 2005»
15 years 6 months ago
Locality Aware Networked Join Evaluation
We pose the question: how do we efficiently evaluate a join operator, distributed over a heterogeneous network? Our objective here is to optimize the delay of output tuples. We di...
Yanif Ahmad, Ugur Çetintemel, John Jannotti...