The design and analysis of parallel algorithms
The design and analysis of parallel algorithms
IEEE Transactions on Software Engineering
Parallel sorting by regular sampling
Journal of Parallel and Distributed Computing
Proceedings of the eighth annual ACM symposium on Parallel algorithms and architectures
High-performance sorting on networks of workstations
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Optimal sampling strategies for quicksort
Random Structures & Algorithms
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
Searching for the sorting record: experiences in tuning NOW-Sort
SPDT '98 Proceedings of the SIGMETRICS symposium on Parallel and distributed tools
Evolving data into mining solutions for insights
Communications of the ACM - Evolving data mining into solutions for insights
Partitioned parallel radix sort
Journal of Parallel and Distributed Computing
Parallel Merge Sort with Load Balancing
International Journal of Parallel Programming
Sorting in Parallel Database Systems
HPC '00 Proceedings of the The Fourth International Conference on High-Performance Computing in the Asia-Pacific Region-Volume 2 - Volume 2
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Many parallel sorting algorithms of external disk data have been reported such as NOW-sort, SPsort, hill sort and so on. They all reduce the execution time compared with some known sequential sort; however, they differ in terms of the speed, throughput or cost-effectiveness. Mostly, they deal with uniformly distributed data in their value range. If we divide and redistribute data to processors by fixed and equal division of the key range, all processors will have about equal numbers of keys to sort and store. But if irregularly distributed data are given, the performance will suffer severely as the partitioning would no longer produce balanced loads among processors. Few research results have been reported for parallel external sort of data with arbitrary distribution. In this paper, we develop two distribution-insensitive scalable parallel external sorting algorithms that use sampling technique and histogram counts to achieve even distribution of keys, which eventually contribute to achieve good performance. Experimental results on a cluster of 16 Linux workstations show up to threefold enhancement of the performance compared with NOW-sort for sorting 16 GB integer keys.