2003Unpublished venueRequires access

A simple, fast parallel implementation of Quicksort and its performance evaluation on SUN Enterprise 10000

Philippas Tsigas, Yi Zhang

Open publisher page 84 citations

Abstract

We have implemented sample sort and a parallel version of Quicksort on a cache-coherent shared address space multiprocessor: the SUN ENTERPRISE 10000. Our computational experiments show that parallel Quicksort outperforms sample sort. Sample sort has been long thought to be the best, general parallel sorting algorithm, especially for larger data sets. On 32 processors of the ENTERPRISE 10000 the speedup of parallel Quicksort is more than six units higher than the speedup of sample sort, resulting in execution times that were more than 50% faster than sample sort. On one processor, parallel quicksort achieved 15% percent faster execution times than sample sorting. Moreover, because of its low memory requirements, parallel Quicksort could sort data sets at twice the size that sample sort could under the same system memory restrictions.

About this research paper

What this paper is about

We have implemented sample sort and a parallel version of Quicksort on a cache-coherent shared address space multiprocessor: the SUN ENTERPRISE 10000. Our computational experiments show that parallel Quicksort outperforms sample sort. Sample sort has been long thought to be the best, general parallel sorting algorithm, especially for larger data sets. On 32 processors of the ENTERPRISE 10000 the speedup of parallel Quicksort is more than six units higher than the speedup of sample sort, resulting in execution times that were more than 50% faster than sample sort. On one processor, parallel quicksort achieved 15% percent faster execution times than sample sorting. Moreover, because of its low memory requirements, parallel Quicksort could sort data sets at twice the size that sample sort could under the same system memory restrictions.

Why it matters

OpenAlex reports 84 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

We have implemented sample sort and a parallel version of Quicksort on a cache-coherent shared address space multiprocessor: the SUN ENTERPRISE 10000. Our computational experiments show that parallel Quicksort outperforms sample sort. Sample sort has been long thought to be the best, general parallel sorting algorithm, especially for larger data sets. On 32 processors of the ENTERPRISE 10000 the speedup of parallel Quicksort is more than six units higher than the speedup of sample sort, resulting in execution times that were more than 50% faster than sample sort. On one processor, parallel quicksort achieved 15% percent faster execution times than sample sorting. Moreover, because of its low memory requirements, parallel Quicksort could sort data sets at twice the size that sample sort could under the same system memory restrictions.

Key concepts: Quicksort, Computer science, Parallel computing, Speedup, sort, Sorting algorithm, Sorting, Sample (material)

Related papers

Back to paper searchBrowse research topicsOriginal source
A simple, fast parallel implementation of Quicksort and its performance evaluation on SUN Enterprise 10000 — Research Paper | ScholarLens