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ISP: An Optimal Out-of-Core Image-Set Processing Streaming Architecture for Parallel Heterogeneous Systems
June 2012 (vol. 18 no. 6)
pp. 838-851
ASCII Text
x 
 
L. K. Ha, C. T. Silva, J. L. D. Comba, J. Kruger, S. Joshi, "ISP: An Optimal Out-of-Core Image-Set Processing Streaming Architecture for Parallel Heterogeneous Systems," IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 6, pp. 838-851, June, 2012.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2012.32,
author = {L. K. Ha and C. T. Silva and J. L. D. Comba and J. Kruger and S. Joshi},
title = {ISP: An Optimal Out-of-Core Image-Set Processing Streaming Architecture for Parallel Heterogeneous Systems},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {18},
number = {6},
issn = {1077-2626},
year = {2012},
pages = {838-851},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2012.32},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - ISP: An Optimal Out-of-Core Image-Set Processing Streaming Architecture for Parallel Heterogeneous Systems
IS - 6
SN - 1077-2626
SP838
EP851
EPD - 838-851
A1 - L. K. Ha,
A1 - C. T. Silva,
A1 - J. L. D. Comba,
A1 - J. Kruger,
A1 - S. Joshi,
PY - 2012
KW - statistical analysis
KW - graphics processing units
KW - image processing
KW - parallel processing
KW - pipeline processing
KW - out-of-core approach pipeline processing
KW - ISP framework
KW - optimal out-of-core image-set processing streaming architecture
KW - parallel heterogeneous systems
KW - image population analysis
KW - statistical methods
KW - supercomputing power
KW - CPU-GPU systems
KW - streaming algorithms
KW - data structures
KW - memory usage
KW - computational efficiency
KW - asynchronous execution mechanism
KW - Streaming media
KW - Graphics processing unit
KW - MIMO
KW - Hardware
KW - Computational modeling
KW - Data models
KW - Parallel processing
KW - multiimage processing framework.
KW - GPUs
KW - out-of-core processing
KW - atlas construction
KW - diffeomorphism
VL - 18
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
L. K. Ha, Sci. Imaging & Comput. Inst., Univ. of Utah, Salt Lake City, UT, USA
C. T. Silva, Six Metrotech Center, Polytech. Inst. of NYU, Brooklyn, NY, USA
J. L. D. Comba, Inst. de Inf., Fed. Univ. of Rio Grande do Sul, Porto Alegre, Brazil
J. Kruger, Univ. of Saarland, Saarbrucken, Germany
S. Joshi, Sci. Imaging & Comput. Inst., Univ. of Utah, Salt Lake City, UT, USA
Image population analysis is the class of statistical methods that plays a central role in understanding the development, evolution, and disease of a population. However, these techniques often require excessive computational power and memory that are compounded with a large number of volumetric inputs. Restricted access to supercomputing power limits its influence in general research and practical applications. In this paper we introduce ISP, an Image-Set Processing streaming framework that harnesses the processing power of commodity heterogeneous CPU/GPU systems and attempts to solve this computational problem. In ISP, we introduce specially designed streaming algorithms and data structures that provide an optimal solution for out-of-core multiimage processing problems both in terms of memory usage and computational efficiency. ISP makes use of the asynchronous execution mechanism supported by parallel heterogeneous systems to efficiently hide the inherent latency of the processing pipeline of out-of-core approaches. Consequently, with computationally intensive problems, the ISP out-of-core solution can achieve the same performance as the in-core solution. We demonstrate the efficiency of the ISP framework on synthetic and real datasets.

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Index Terms:
statistical analysis,graphics processing units,image processing,parallel processing,pipeline processing,out-of-core approach pipeline processing,ISP framework,optimal out-of-core image-set processing streaming architecture,parallel heterogeneous systems,image population analysis,statistical methods,supercomputing power,CPU-GPU systems,streaming algorithms,data structures,memory usage,computational efficiency,asynchronous execution mechanism,Streaming media,Graphics processing unit,MIMO,Hardware,Computational modeling,Data models,Parallel processing,multiimage processing framework.,GPUs,out-of-core processing,atlas construction,diffeomorphism
Citation:
L. K. Ha, C. T. Silva, J. L. D. Comba, J. Kruger, S. Joshi, "ISP: An Optimal Out-of-Core Image-Set Processing Streaming Architecture for Parallel Heterogeneous Systems," IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 6, pp. 838-851, June 2012, doi:10.1109/TVCG.2012.32
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