Fast Implementation Method of Protein Spots Detection Based on CUDA / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 83-88, 2016.
Article
in Chinese
| WPRIM
| ID: wpr-357847
ABSTRACT
In order to improve the efficiency of protein spots detection, a fast detection method based on CUDA was proposed. Firstly, the parallel algorithms of the three most time-consuming parts in the protein spots detection algorithm image preprocessing, coarse protein point detection and overlapping point segmentation were studied. Then, according to single instruction multiple threads executive model of CUDA to adopted data space strategy of separating two-dimensional (2D) images into blocks, various optimizing measures such as shared memory and 2D texture memory are adopted in this study. The results show that the operative efficiency of this method is obviously improved compared to CPU calculation. As the image size increased, this method makes more improvement in efficiency, such as for the image with the size of 2,048 x 2,048, the method of CPU needs 52,641 ms, but the GPU needs only 4,384 ms.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Algorithms
/
Image Processing, Computer-Assisted
/
Software
/
Proteomics
/
Methods
Type of study:
Diagnostic study
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2016
Type:
Article
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