This paper presents a general methodology for the efficient parallelization of existing data cube construction algorithms. We describe two different partitioning strategies, one f...
Frank K. H. A. Dehne, Todd Eavis, Susanne E. Hambr...
The pre-computation of data cubes is critical to improving the response time of On-Line Analytical Processing (OLAP) systems and can be instrumental in accelerating data mining tas...
Ying Chen, Frank K. H. A. Dehne, Todd Eavis, Andre...
In this demo we present the cgmOLAP server, the first fully functional parallel OLAP system able to build data cubes at a rate of more than 1 Terabyte per hour. cgmOLAP incorporat...
Ying Chen, Andrew Rau-Chaplin, Frank K. H. A. Dehn...
Given the large communication overheads characteristic of modern parallel machines, optimizations that eliminate, hide or parallelize communication may improve the performance of ...