Exploiting throughput for pipeline execution in streaming image processing applications

被引：0
|
作者：
Guirado, F. [1 ]
Ripoll, A.
Roig, C.
Hernandez, A.
Luque, E.
机构：
[1] Univ Lleida, Lleida, Spain
[2] Univ Autonoma Barcelona, Comp Vis Ctr, E-08193 Barcelona, Spain
来源：
EURO-PAR 2006 PARALLEL PROCESSING | 2006年 / 4128卷
关键词：
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
There is a large range of image processing applications that act on an input sequence of image frames that are continuously received. Throughput is a key performance measure to be optimized when executing them. In this paper we propose a new task replication methodology for optimizing throughput for an image processing application in the field of medicine. The results show that by applying the proposed methodology we are able to achieve the desired throughput in all cases, in such a way that the input frames can be processed at any given rate.
引用
收藏
页码：1095 / 1105
页数：11
相关论文
共 50 条
  • [41] The Dark Energy Survey Image Processing Pipeline
    Morganson, E.
    Gruendl, R. A.
    Menanteau, F.
    Kind, M. Carrasco
    Chen, Y. -C.
    Daues, G.
    Drlica-Wagner, A.
    Friedel, D. N.
    Gower, M.
    Johnson, M. W. G.
    Johnson, M. D.
    Kessler, R.
    Paz-Chinchon, F.
    Petravick, D.
    Pond, C.
    Yanny, B.
    Allam, S.
    Armstrong, R.
    Barkhouse, W.
    Bechtol, K.
    Benoit-Levy, A.
    Bernstein, G. M.
    Bertin, E.
    Buckley-Geer, E.
    Covarrubias, R.
    Desai, S.
    Diehl, H. T.
    Goldstein, D. A.
    Gruen, D.
    Li, T. S.
    Lin, H.
    Marriner, J.
    Mohr, J. J.
    Neilsen, E.
    Ngeow, C. -C.
    Paech, K.
    Rykoff, E. S.
    Sako, M.
    Sevilla-Noarbe, I.
    Sheldon, E.
    Sobreira, F.
    Tucker, D. L.
    Wester, W.
    PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC, 2018, 130 (989)
  • [42] Optoelectronic pipeline architecture for morphological image processing
    Michael, N
    Arrathoon, R
    APPLIED OPTICS, 1997, 36 (08): : 1718 - 1725
  • [43] A modular Advanced pipeline Image Processing Accelerator
    Messner, RA
    Bloomfield, J
    1996 IEEE AEROSPACE APPLICATIONS CONFERENCE, PROCEEDINGS, VOL 4, 1996, : 407 - 422
  • [44] A MODULAR HYPERSPECTRAL IMAGE PROCESSING PIPELINE FOR CUBESATS
    Bakken, Sivert
    Danielsen, Aksel
    Dosvik, Kristine
    Garrett, Joeseph
    Orlandic, Milica
    Langer, Dennis
    Johansen, Tor Arne
    2022 12TH WORKSHOP ON HYPERSPECTRAL IMAGING AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS), 2022,
  • [45] Image Processing Pipeline for Automated Larva Counting
    Clarke, Hayden
    Horine, Brent
    Thomas-Hall, Peter L.
    2018 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC): DISCOVERING NEW HORIZONS IN INSTRUMENTATION AND MEASUREMENT, 2018, : 1917 - 1921
  • [46] ReconfigISP: Reconfigurable Camera Image Processing Pipeline
    Yu, Ke
    Li, Zexian
    Peng, Yue
    Loy, Chen Change
    Gu, Jinwei
    2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021), 2021, : 4228 - 4237
  • [47] A Crystal/Clear Pipeline for Applied Image Processing
    Watkins, Christopher J.
    Rosa, Nicholas
    Carroll, Thomas
    Ratcliffe, David
    Ristic, Marko
    Russell, Christopher
    Li, Rongxin
    Fazio, Vincent
    Newman, Janet
    SUPERCOMPUTING FRONTIERS, SCFA 2019, 2019, 11416 : 19 - 37
  • [48] Recycled materials execution through digital image processing
    Surendranath, Arigela
    Ramana, P., V
    MATERIALS TODAY-PROCEEDINGS, 2021, 46 : 8795 - 8801
  • [49] Reconfigurable architectures for parallel execution of image processing tasks
    Gorgon, M.
    OPTO-ELECTRONICS REVIEW, 2007, 15 (04) : 196 - 201
  • [50] PyAnaDroid: A fully-customizable execution pipeline for benchmarking Android Applications
    Rua, Rui
    Saraiva, Joao
    2023 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION, ICSME, 2023, : 586 - 591
12345