PORTO @ 
Archivio Istituzionale della Ricerca
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishThis paper presents a comparative analysis of the three widely used parallel sorting algorithms: Odd-Even sort, Rank sort and Bitonic sort in terms of sorting rate, sorting time and speed-up on CPU and different GPU architectures. Alongside we have implemented novel parallel algorithm: min-max butterfly network, for finding minimum and maximum in large data sets. All algorithms have been implemented exploiting data parallelism model, for achieving high performance, as available on multi-core GPUs using the OpenCL specification. Our results depicts minimum speed-up19x of bitonic sort against odd-even sorting technique for small queue sizes on CPU and maximum of 2300x speed-up for very large queue sizes on Nvidia Quadro 6000 GPU architecture. Our implementation of full-butterfly network sorting results in relatively better performance than all of the three sorting techniques: bitonic, odd-even and rank sort. For min-max butterfly network, our findings report high speed-up of Nvidia quadro 6000 GPU for high data set size reaching 2^24 with much lower sorting time.
Fast parallel sorting algorithms on GPUs / B. Jan; B. Montrucchio; C. S. Ragusa; F. G. Khan; O. U. Khan. - In: INTERNATIONAL JOURNAL OF DISTRIBUTED AND PARALLEL SYSTEMS. - ISSN 2229-3957. - ELETTRONICO. - 3(2012), pp. 107-118.
| Titolo: | Fast parallel sorting algorithms on GPUs | |
| Autori: | ||
| Data di pubblicazione: | 2012 | |
| Rivista: | ||
| Digital Object Identifier (DOI): | http://dx.doi.org/10.5121/ijdps.2012.3609 | |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
File in questo prodotto:
http://hdl.handle.net/11583/2505485
Copyright © 2021