2010
DOI: 10.1002/cpe.1646
|View full text |Cite
|
Sign up to set email alerts
|

Image processing applications performance study on Cell BE and Blue Gene/L

Abstract: SUMMARYTwo image processing applications, edge detection and image resizing, are studied in this paper on two HPC platforms namely the Cell BE and the Blue Gene/L machines. In this paper we focus on the performance scalability of the studied applications. Our results show that the scale of the problem to be solved highly affects the fitness of the platform. If the data set size is to fit into the Cell core, the fast on-chip inter-core communication of a multi-core system pays back for its high technology desig… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2013
2013
2022
2022

Publication Types

Select...
4
1

Relationship

1
4

Authors

Journals

citations
Cited by 5 publications
(2 citation statements)
references
References 19 publications
0
2
0
Order By: Relevance
“…We have developed a parallel HMM algorithm in Ref. 38; but the study in this paper is thē rst to our knowledge that compares the multicores to the clusters on one of the bioinformatics applications that used to predict PPIs.…”
Section: Related Workmentioning
confidence: 99%
“…We have developed a parallel HMM algorithm in Ref. 38; but the study in this paper is thē rst to our knowledge that compares the multicores to the clusters on one of the bioinformatics applications that used to predict PPIs.…”
Section: Related Workmentioning
confidence: 99%
“…In recent years, CG interconnected systems have been used to improve speed and performance of algorithms in applications like multimedia processing, image processing, and parallel computing [5]- [12]. Hardware implementations like matrix computations on FPGA [13], contour extraction on partitionable SIMD/MIMD System -PASM [14], and edge detection and image resizing on Cell BE and Blue Gene\L HPC (High Performance Computing) platforms [15] have been developed to improve the performance in the corresponding fields. To improve the speed of contour tracing (hence image processing) on existing parallel processing hardware, we developed distributed data processing based algorithms for implementation on CG interconnected parallel processors.…”
Section: Introductionmentioning
confidence: 99%