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...
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 ...
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...
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 ...
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...