Computing dominances inEn (short communication)
Information Processing Letters
Scalable parallel geometric algorithms for coarse grained multicomputers
SCG '93 Proceedings of the ninth annual symposium on Computational geometry
On Finding the Maxima of a Set of Vectors
Journal of the ACM (JACM)
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
OpenMP: An Industry-Standard API for Shared-Memory Programming
IEEE Computational Science & Engineering
Proceedings of the 17th International Conference on Data Engineering
Integrating the UB-Tree into a Database System Kernel
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Progressive skyline computation in database systems
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Maximal vector computation in large data sets
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Software and the Concurrency Revolution
Queue - Multiprocessors
Map-reduce-merge: simplified relational data processing on large clusters
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Parallel Computation of Skyline Queries
HPCS '07 Proceedings of the 21st International Symposium on High Performance Computing Systems and Applications
Efficient Skyline and Top-k Retrieval in Subspaces
IEEE Transactions on Knowledge and Data Engineering
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Evaluating MapReduce for Multi-core and Multiprocessor Systems
HPCA '07 Proceedings of the 2007 IEEE 13th International Symposium on High Performance Computer Architecture
Approaching the skyline in Z order
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Optimization of frequent itemset mining on multiple-core processor
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Angle-based space partitioning for efficient parallel skyline computation
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Efficient sort-based skyline evaluation
ACM Transactions on Database Systems (TODS)
Parallelizing query optimization
Proceedings of the VLDB Endowment
Parallel Skyline Computation on Multicore Architectures
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Dependency-aware reordering for parallelizing query optimization in multi-core CPUs
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Scalable skyline computation using object-based space partitioning
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Sort vs. Hash revisited: fast join implementation on modern multi-core CPUs
Proceedings of the VLDB Endowment
Thread cooperation in multicore architectures for frequency counting over multiple data streams
Proceedings of the VLDB Endowment
Mining tree-structured data on multicore systems
Proceedings of the VLDB Endowment
Parallelizing skyline queries for scalable distribution
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Highly scalable multiprocessing algorithms for preference-based database retrieval
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
Breaking skyline computation down to the metal: the skyline breaker algorithm
Proceedings of the 17th International Database Engineering & Applications Symposium
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With the advent of multicore processors, it has become imperative to write parallel programs if one wishes to exploit the next generation of processors. This paper deals with skyline computation as a case study of parallelizing database operations on multicore architectures. First we parallelize three sequential skyline algorithms, BBS, SFS, and SSkyline, to see if the design principles of sequential skyline computation also extend to parallel skyline computation. Then we develop a new parallel skyline algorithm PSkyline based on the divide-and-conquer strategy. Experimental results show that all the algorithms successfully utilize multiple cores to achieve a reasonable speedup. In particular, PSkyline achieves a speedup approximately proportional to the number of cores when it needs a parallel computation the most.