Paralleizing AwSpPCA for robust facial recognition using CUDA
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014.
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BRAC University
2014
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| On-line přístup: | http://hdl.handle.net/10361/3226 |
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10361-32262022-01-26T10:23:16Z Paralleizing AwSpPCA for robust facial recognition using CUDA Zawad, Syed Amer Alom, Md. Zahangir Ali, Ashfaque Department of Computer Science and Engineering, BRAC University Computer science and engineering This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014. Cataloged from PDF version of thesis report. This paper was conducted to analyze the performance benefits of parallelizing the Adaptive Weighted Sub-patterned Principle Component Analysis (Aw SP PCA) algorithm, given that the algorithm is implemented so as to retain the accuracy from its serialized version. The serialized execution of this algorithm is analyzed first and then compared against its parallel implementation, both compiled and run on the same computer. Throughout this paper, the methodology is to undergo a step by step procedure which can clearly outline and describe the problems faced when trying to parallelize this algorithm. It will also describe where, how and why parallelizing procedures were used. The results of the research have shown that while not all parts of the algorithm can be implemented in parallel in the first place, some of the sections that can be parallelized does not necessarily yield a considerable amount of benefits. Also, it was seen that not all sections scale well with problem size, meaning that some portions of the algorithm can be left in its serialized state without much loss in time. The sections which can be parallelized were discussed in detail. Some changes were also made to certain variables to ensure the best accuracy possible. Finally, through analysis and experimentation, a speedup of 2.76 was achieved, with a recognition accuracy of 92.6%. Syed Amer Zawad Ashfaque Ali B. Computer Science and Engineering 2014-05-14T07:15:36Z 2014-05-14T07:15:36Z 2014-04 Thesis ID 13301094 ID 10101009 http://hdl.handle.net/10361/3226 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 46 pages application/pdf BRAC University |
| institution |
Brac University |
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Institutional Repository |
| language |
English |
| topic |
Computer science and engineering |
| spellingShingle |
Computer science and engineering Zawad, Syed Amer Paralleizing AwSpPCA for robust facial recognition using CUDA |
| description |
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014. |
| author2 |
Alom, Md. Zahangir |
| author_facet |
Alom, Md. Zahangir Zawad, Syed Amer |
| format |
Thesis |
| author |
Zawad, Syed Amer |
| author_sort |
Zawad, Syed Amer |
| title |
Paralleizing AwSpPCA for robust facial recognition using CUDA |
| title_short |
Paralleizing AwSpPCA for robust facial recognition using CUDA |
| title_full |
Paralleizing AwSpPCA for robust facial recognition using CUDA |
| title_fullStr |
Paralleizing AwSpPCA for robust facial recognition using CUDA |
| title_full_unstemmed |
Paralleizing AwSpPCA for robust facial recognition using CUDA |
| title_sort |
paralleizing awsppca for robust facial recognition using cuda |
| publisher |
BRAC University |
| publishDate |
2014 |
| url |
http://hdl.handle.net/10361/3226 |
| work_keys_str_mv |
AT zawadsyedamer paralleizingawsppcaforrobustfacialrecognitionusingcuda |
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1814309825135247360 |