Efficient sorting is vital for overall performance of the underlying application. This paper presents Butterfly Network Sort (BNS) for sorting large data sets. A minimal version of the algorithm Min-Max Butterfly is also shown for searching minimum and maximum values in data. Both algorithms are implemented on GPUs using OpenCL exploiting data parallelism model. Results obtained on different GPU architectures show better performance of butterfly sorting in terms of sorting time and rate. The comparison of butterfly sorting with other algorithms:bitonic, odd-even and rank sort show significant speedup improvements against all on Nvidia Quadro-6000 GPU with relatively better sorting time and rate.
Parallel butterfly sorting algorithm on GPU / Jan, Bilal; Montrucchio, Bartolomeo; Ragusa, CARLO STEFANO; Khan, FIAZ GUL; Khan, OMAR USMAN. - STAMPA. - (2013), pp. 544-551. (Intervento presentato al convegno 11th IASTED International Conference on Parallel and Distributed Computing and Networks, PDCN 2013; Innsbruck; Austria; 11 February 2013 through 13 February 2013; Code 96246 tenutosi a Innsbruck; Austria nel 11 February 2013 through 13 February 2013) [10.2316/P.2013.795-026].
Parallel butterfly sorting algorithm on GPU
JAN, BILAL;MONTRUCCHIO, BARTOLOMEO;RAGUSA, CARLO STEFANO;KHAN, FIAZ GUL;KHAN, OMAR USMAN
2013
Abstract
Efficient sorting is vital for overall performance of the underlying application. This paper presents Butterfly Network Sort (BNS) for sorting large data sets. A minimal version of the algorithm Min-Max Butterfly is also shown for searching minimum and maximum values in data. Both algorithms are implemented on GPUs using OpenCL exploiting data parallelism model. Results obtained on different GPU architectures show better performance of butterfly sorting in terms of sorting time and rate. The comparison of butterfly sorting with other algorithms:bitonic, odd-even and rank sort show significant speedup improvements against all on Nvidia Quadro-6000 GPU with relatively better sorting time and rate.Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/2518565
Attenzione
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo