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IEEEPACT
2002
IEEE
14 years 16 days ago
Cost Effective Memory Dependence Prediction using Speculation Levels and Color Sets
Memory dependence prediction allows out-of-order issue processors to achieve high degrees of instruction level parallelism by issuing load instructions at the earliest time withou...
Soner Önder
SDM
2012
SIAM
297views Data Mining» more  SDM 2012»
11 years 10 months ago
A Flexible Open-Source Toolbox for Scalable Complex Graph Analysis
The Knowledge Discovery Toolbox (KDT) enables domain experts to perform complex analyses of huge datasets on supercomputers using a high-level language without grappling with the ...
Adam Lugowski, David M. Alber, Aydin Buluç,...
IPPS
1998
IEEE
13 years 12 months ago
ScalParC: A New Scalable and Efficient Parallel Classification Algorithm for Mining Large Datasets
In this paper, we present ScalParC (Scalable Parallel Classifier), a new parallel formulation of a decision tree based classification process. Like other state-of-the-art decision...
Mahesh V. Joshi, George Karypis, Vipin Kumar
ICPP
2009
IEEE
13 years 5 months ago
Employing Transactional Memory and Helper Threads to Speedup Dijkstra's Algorithm
In this paper we work on the parallelization of the inherently serial Dijkstra's algorithm on modern multicore platforms. Dijkstra's algorithm is a greedy algorithm that ...
Konstantinos Nikas, Nikos Anastopoulos, Georgios I...
SIGMOD
1997
ACM
134views Database» more  SIGMOD 1997»
13 years 11 months ago
Scalable Parallel Data Mining for Association Rules
One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items. The most time consu...
Eui-Hong Han, George Karypis, Vipin Kumar