research-article

Biomedical image analysis on a cooperative cluster of GPUs and multicores

Authors:

Timothy D.R. Hartley,

Umit Catalyurek,

Francisco Igual,

Manuel UjaldonAuthors Info & Claims

ICS '08: Proceedings of the 22nd annual international conference on Supercomputing

Pages 15 - 25

https://doi.org/10.1145/1375527.1375533

Published: 07 June 2008 Publication History

Abstract

We are currently witnessing the emergence of two paradigms in parallel computing: streaming processing and multi-core CPUs. Represented by solid commercial products widely available in commodity PCs, GPUs and multi-core CPUs bring together an unprecedented combination of high performance at low cost. The scientific computing community needs to keep pace with application models and middleware which scale efficiently to hundreds of internal processing units. The purpose of the work we present here is twofold: first, a cooperative environment is designed so that both parallel models can coexist and complement one another. Second, beyond the parallelism of multiple internal cores, further parallelism is introduced when multiple CPU sockets, multiple GPUs, and multiple nodes are combined within a unique multi-processor platform which exceeds 10 TFLOPS when using 16 nodes. We illustrate our cooperative parallelization approach by implementing a large-scale, biomedical image analysis application which contains a number of assorted kernels including typical streaming operators, co-occurrence matrices, convolutions, and histograms. Experimental results are compared among different implementation strategies and almost linear speed-up is achieved when all coexisting methods in CPUs and GPUs are combined.

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Cited By

Jaiswal DKumar P(2021)A survey on parallel computing for traditional computer visionConcurrency and Computation: Practice and Experience10.1002/cpe.663834:4Online publication date: 28-Sep-2021
https://doi.org/10.1002/cpe.6638
Teodoro GKurc TAndrade GKong JFerreira RSaltz J(2017)Application performance analysis and efficient execution on systems with multi-core CPUs, GPUs and MICsInternational Journal of High Performance Computing Applications10.1177/109434201559451931:1(32-51)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1177/1094342015594519
Bordallo López MNieto ABoutellier JHannuksela JSilvén O(2017)Evaluation of real-time LBP computing in multiple architecturesJournal of Real-Time Image Processing10.1007/s11554-014-0410-513:2(375-396)Online publication date: 1-Jun-2017
https://dl.acm.org/doi/10.1007/s11554-014-0410-5
Show More Cited By

Index Terms

Biomedical image analysis on a cooperative cluster of GPUs and multicores
1. Computer systems organization
  1. Architectures
    1. Parallel architectures
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
  2. Computer graphics
    1. Graphics systems and interfaces
      1. Graphics processors

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Information & Contributors

Information

Published In

cover image ACM Conferences

ICS '08: Proceedings of the 22nd annual international conference on Supercomputing

June 2008

390 pages

ISBN:9781605581583

DOI:10.1145/1375527

General Chairs:
Theo Papatheodorou
University of Patras, Greece
,
Utpal Banerjee
Intel (retired), USA
,
Program Chairs:
Avi Mendelson
Intel, Israel
,
Kyle Gallivan
Florida State University, USA

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 June 2008

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ICS08: International Conference on Supercomputing

June 7 - 12, 2008

Island of Kos, Greece

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Overall Acceptance Rate 629 of 2,180 submissions, 29%

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Cited By

Jaiswal DKumar P(2021)A survey on parallel computing for traditional computer visionConcurrency and Computation: Practice and Experience10.1002/cpe.663834:4Online publication date: 28-Sep-2021
https://doi.org/10.1002/cpe.6638
Teodoro GKurc TAndrade GKong JFerreira RSaltz J(2017)Application performance analysis and efficient execution on systems with multi-core CPUs, GPUs and MICsInternational Journal of High Performance Computing Applications10.1177/109434201559451931:1(32-51)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1177/1094342015594519
Bordallo López MNieto ABoutellier JHannuksela JSilvén O(2017)Evaluation of real-time LBP computing in multiple architecturesJournal of Real-Time Image Processing10.1007/s11554-014-0410-513:2(375-396)Online publication date: 1-Jun-2017
https://dl.acm.org/doi/10.1007/s11554-014-0410-5
Kurc TQi XWang DWang FTeodoro GCooper LNalisnik MYang LSaltz JForan D(2015)Scalable analysis of Big pathology image data cohorts using efficient methods and high-performance computing strategiesBMC Bioinformatics10.1186/s12859-015-0831-616:1Online publication date: 1-Dec-2015
https://doi.org/10.1186/s12859-015-0831-6
Kim BJung HNadimi ECerny TKim SWang W(2015)A case study of data transfer efficiency optimization for GPU- and infiniband-based clustersProceedings of the 2015 Conference on research in adaptive and convergent systems10.1145/2811411.2811468(247-250)Online publication date: 9-Oct-2015
https://dl.acm.org/doi/10.1145/2811411.2811468
Mittal SVetter J(2015)A Survey of CPU-GPU Heterogeneous Computing TechniquesACM Computing Surveys10.1145/278839647:4(1-35)Online publication date: 21-Jul-2015
https://dl.acm.org/doi/10.1145/2788396
Tan GZhang CWang WZhang P(2015)SuperDragonACM Transactions on Reconfigurable Technology and Systems10.1145/27409668:4(1-22)Online publication date: 13-Sep-2015
https://dl.acm.org/doi/10.1145/2740966
Sarıyüce ASaule EKaya KÇatalyürek Ü(2015)Incremental closeness centrality in distributed memoryParallel Computing10.1016/j.parco.2015.01.00347:C(3-18)Online publication date: 1-Aug-2015
https://dl.acm.org/doi/10.1016/j.parco.2015.01.003
Galizia AD'Agostino DClematis A(2015)An MPI-CUDA library for image processing on HPC architecturesJournal of Computational and Applied Mathematics10.1016/j.cam.2014.05.004273:C(414-427)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1016/j.cam.2014.05.004
Antonelli MIgual FRamos FTraver V(2015)Speeding up the log-polar transform with inexpensive parallel hardwareJournal of Real-Time Image Processing10.1007/s11554-012-0281-610:3(533-550)Online publication date: 1-Sep-2015
https://dl.acm.org/doi/10.1007/s11554-012-0281-6
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