Image Quality Improvement on OpenGL-Based Animations by Using CUDA Architecture

Taner UÇKAN, Deniz DAL
2.130 605

Abstract


2D or 3D rendering technology is used for graphically modelling many physical phenomena occurring in real life by means of the computers. On the other hand, the ever-increasing intensity of the graphics applications require that the image quality of the so-called modellings is enhanced and they are performed more quickly. In this direction, a new software and hardware-based architecture called CUDA has been introduced by Nvidia at the end of 2006. Thanks to this architecture, larger number of graphics processors has started contributing towards the parallel solutions of the general-purpose problems. In this study, this new parallel computing architecture is taken into consideration and an animation application consisting of humanoid robots with different behavioral characteristics is developed using the OpenGL library in C++. This animation is initially implemented on a single serial CPU and then parallelized using the CUDA architecture. Eventually, the serial and the parallel versions of the same animation are compared against each other on the basis of the number of image frames per second. The results reveal that the parallel application is by far the best yielding high quality images.

Keywords


3D Modelling; OpenGL; C++; Nvidia; CUDA; GPGPU; Animation

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DOI: http://dx.doi.org/10.17482/uujfe.97021

References


https://open.gl/textures (Erişim Tarihi: 08.05.2015). OpenGL Doku Haritalama.

Ahn, H. S., (2014). OpenGL Pixel Buffer Object (PBO). http://www.songho.ca/opengl/gl_pbo.html (Erişim Tarihi: 05.03.2015)

Akçay, M., Şen, B., Orak, İ. Ö., Çelik, A., (2011). Paralel Hesaplama ve CUDA. 6. Uluslararası İleri Teknolojiler Sempozyumu (İATS’11), Elazığ.

Archirapatkave, V., Sumilo, V., See, S.C.W., Achalakul, T., (2011). GPGPU Acceleration Algorithm for Medical Image Reconstruction. Ninth IEEE International Symposium on Parallel and Distributed Processing with Applications, Singapore.

Balfour, J., (2011). Introduction to CUDA. http://mc.stanford.edu/cgi-bin/images/f/f7/Darve_cme343_cuda_1.pdf (Erişim Tarihi: 20.03.2015)

Centelles, A. P., Sunyer, N., Ripolles, O., Chover, M., Sbert, M., (2011). Rain Simulation in Dynamic Scenes. International Journal of Creative Interfaces and Computer Graphics, 2 (2), 23-36

Çolak, M. A., (2010). Grafik Kartı Üzerinde Paralel Hızlandırılmış Işın İzleme. Yüksek Lisans Tezi, İstanbul Teknik Üniversitesi Fen Bilimleri Enstitüsü, İstanbul.

Huaming, L., Baosheng, K., (2014). Real-time Physically Cloth Simulation with CUDA. Computer Modelling & New Technologies, 18 (12B), 28-32.

Kılıç, O. M., (1995). An Open Graphics Library (OpenGL) based Toolbox for Biomedical Image Display and Processing. Yüksek Lisans Tezi, Boğaziçi Üniversitesi Biyomedikal Mühendisliği Enstitüsü, İstanbul.

Li, W., Huang, X., Zheng, N., (1997). Parallel Implementing OpenGL on PVM. Parallel Computing, 23 (1997) 1839-1850.

Lin, C.Y., Lee, W.S., Tang, C.Y., (2012). Parallel Shellsort Algorithm for Many-Core GPUs with CUDA. International Journal of Grid and High Performance Computing, 4 (2), 1-16.

Ma, L., Zhao D.X., Yang Z.Z., (2013). A Software Tool for Visualization of Molecular Face (VMF) by Improving Marching Cubes Algorithm. Computational and Theoretical Chemistry, 1028 (2014), 34–45.

Manavski, S.A., (2007). CUDA Compatible GPU as an Efficient Hardware Accelerator for AES Cryptography, IEEE ICSPC 2007, 24-27.

Nuli, U. A., Kulkarni P. J., (2012). SPH Based Fluid Animation Using CUDA Enabled Gpu. International Journal of Computer Graphics & Animation (IJCGA), 2(4), 45-51.

Nvidia, (2007). Nvidia CUDA (Compute Unified Device Architecture). http://moss.csc.ncsu.edu/~mueller/cluster/nvidia/0.8/NVIDIA_CUDA_Programming_Guide_0.8.2.pdf (Erişim Tarihi: 25.05.2015).

Nvidia, (2014). CUDA C Programming Guide. http://docs.nvidia.com/cuda/cuda-c-programming-guide/#axzz3LyTDrCdH (Erişim Tarihi: 25.04.2015).

Okidsu, Y., Ino, F., Hagihara, K., (2010). High-Performance Cone Beam Reconstruction using CUDA Compatible GPUs. Parallel Computing, 36 (2010) 129–141.

Şaşıoğlu, S., (2010). OpenGL ile 3 Boyutlu Arazi Modellerinin Üretimi ve Çoklu Çözünürlükte Sadeleştirilmesi. Yüksek Lisans Tezi, Gazi Üniversitesi Fen bilimleri Enstitüsü, Ankara.

Tokatlı, A., (2010). Modelling of Geological Measurements with OpenGL. Yüksek Lisans Tezi, Eskişehir Osmangazi Üniversitesi Fen Bilimleri Enstitüsü, Eskişehir.

Wang, G., Huang, L., (2011). 3D Geological Modelling for Mineral Resource Assessment of the Tongshan Cu Deposit. Elsevier, 3(4), 483-491.

Yıldız, E., (2011). Nvidia CUDA ile Yüksek Performanslı Görüntü İşleme. Yüksek Lisans Tezi, İstanbul Üniversitesi Fen Bilimleri Enstitüsü, İstanbul.




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