8602

Fast Parallel Sorting Algorithms on GPUs

Bilal Jan, Bartolomeo Montrucchio, Carlo Ragusa, Fiaz Gul Khan, Omar Khan
Dipartimento di Automatica e Informatica, Politecnico di Torino, Torino, I-10129 Italy
International Journal of Distributed and Parallel systems (IJDPS), Volume 3, Number 6, 2012
@article{jan2012fast,

   title={FAST PARALLEL SORTING ALGORITHMS ON GPUS},

   author={Jan, B. and Montrucchio, B. and Ragusa, C. and Khan, F.G. and Khan, O.},

   year={2012}

}

Download Download (PDF)   View View   Source Source   

2638

views

This paper presents a comparative analysis of the three widely used parallel sorting algorithms: OddEven 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 oddeven 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 224 with much lower sorting time.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

TwitterAPIExchange Object
(
    [oauth_access_token:TwitterAPIExchange:private] => 301967669-yDz6MrfyJFFsH1DVvrw5Xb9phx2d0DSOFuLehBGh
    [oauth_access_token_secret:TwitterAPIExchange:private] => o29ji3VLVmB6jASMqY8G7QZDCrdFmoTvCDNNUlb7s
    [consumer_key:TwitterAPIExchange:private] => TdQb63pho0ak9VevwMWpEgXAE
    [consumer_secret:TwitterAPIExchange:private] => Uq4rWz7nUnH1y6ab6uQ9xMk0KLcDrmckneEMdlq6G5E0jlQCFx
    [postfields:TwitterAPIExchange:private] => 
    [getfield:TwitterAPIExchange:private] => ?cursor=-1&screen_name=hgpu&skip_status=true&include_user_entities=false
    [oauth:protected] => Array
        (
            [oauth_consumer_key] => TdQb63pho0ak9VevwMWpEgXAE
            [oauth_nonce] => 1474756589
            [oauth_signature_method] => HMAC-SHA1
            [oauth_token] => 301967669-yDz6MrfyJFFsH1DVvrw5Xb9phx2d0DSOFuLehBGh
            [oauth_timestamp] => 1474756589
            [oauth_version] => 1.0
            [cursor] => -1
            [screen_name] => hgpu
            [skip_status] => true
            [include_user_entities] => false
            [oauth_signature] => ia8sHwLW+BiXN55nSNclyW1MFxI=
        )

    [url] => https://api.twitter.com/1.1/users/show.json
)
Follow us on Facebook
Follow us on Twitter

HGPU group

1995 peoples are following HGPU @twitter

HGPU group © 2010-2016 hgpu.org

All rights belong to the respective authors

Contact us: