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EUROPAR
2009
Springer
13 years 9 months ago
Distributed Data Partitioning for Heterogeneous Processors Based on Partial Estimation of Their Functional Performance Models
The paper presents a new data partitioning algorithm for parallel computing on heterogeneous processors. Like traditional functional partitioning algorithms, the algorithm assumes ...
Alexey L. Lastovetsky, Ravi Reddy
ICDE
2010
IEEE
227views Database» more  ICDE 2010»
13 years 11 months ago
Incorporating partitioning and parallel plans into the SCOPE optimizer
— Massive data analysis on large clusters presents new opportunities and challenges for query optimization. Data partitioning is crucial to performance in this environment. Howev...
Jingren Zhou, Per-Åke Larson, Ronnie Chaiken
JDWM
2006
178views more  JDWM 2006»
13 years 4 months ago
Improved Data Partitioning for Building Large ROLAP Data Cubes in Parallel
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 ta...
Ying Chen, Frank K. H. A. Dehne, Todd Eavis, Andre...
ICDT
2001
ACM
147views Database» more  ICDT 2001»
13 years 9 months ago
Parallelizing the Data Cube
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...
SPAA
2012
ACM
11 years 7 months ago
A scalable framework for heterogeneous GPU-based clusters
GPU-based heterogeneous clusters continue to draw attention from vendors and HPC users due to their high energy efficiency and much improved single-node computational performance...
Fengguang Song, Jack Dongarra