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Parallel Protein Structure Alignment: A Comparative Study of Two Parallel Programming Paradigms

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Nada M. A. Mohammed, Hala M. Ebeid, Mostafa G. M. Mostafa, Mahmoud E. A. Gadallah

Nada M A Mohammed, Hala M Ebeid, Mostafa G M Mostafa and Mahmoud E A Gadallah. Parallel Protein Structure Alignment: A Comparative Study of Two Parallel Programming Paradigms. International Journal of Computer Applications 150(7):43-48, September 2016. BibTeX

	author = {Nada M. A. Mohammed and Hala M. Ebeid and Mostafa G. M. Mostafa and Mahmoud E. A. Gadallah},
	title = {Parallel Protein Structure Alignment: A Comparative Study of Two Parallel Programming Paradigms},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2016},
	volume = {150},
	number = {7},
	month = {Sep},
	year = {2016},
	issn = {0975-8887},
	pages = {43-48},
	numpages = {6},
	url = {},
	doi = {10.5120/ijca2016911563},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Protein 3D structure alignment process has become the key focus of interest in structural bioinformatics. Yet, obtaining perfect alignment in a short execution time was not successful to this point. To overcome this problem, researchers tend to use parallel programming techniques to enhance the performance of the alignment process. In this article, we compare between two parallel programming paradigms for implementing a parallel version of the well-known pairwise alignment algorithm MatAlign. This parallel algorithm is implemented by using two common APIs for C++ parallel programming, which are OpenMP for multi-core CPUs and CUDA for multi-core GPUs. The results show that beside the significant improvement of the parallel implementation over the sequential one, it also shows that the multi-core GPU parallel programming model improves speedup over multi-core CPU programming model.


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MatAlign, TM-Score, GPGPU, CUDA, OpenMP