[1] Bjarne Stroustrup. The C++ Programming Language, 4th Edition. Addison-Wesley Professional, 4th edition, 5 2013.
[2] Graham Sellers, Richard S. Wright, and Nicholas Haemel. OpenGL SuperBible: Comprehensive Tutorial and Reference (6th Edition). Addison-Wesley Professional, 6th edition, 7 2013.
[3] John Cheng, Max Grossman, and Ty McKercher. Professional CUDA C Programming. Wrox, 1st edition, 9 2014.
[4] Soyata, Tolga. GPU parallel program development using CUDA. CRC Press, 2018.
Parallel Algorithms II
| Language of instruction | angličtina, čeština |
|---|---|
| Code | 460-4118 |
| Abbreviation | PA II |
| Course title | Parallel Algorithms II |
| Coordinating department | Department of Computer Science |
| Course coordinator | doc. Ing. Petr Gajdoš, Ph.D. |
Summary
The subject follows an existing one called Parallel Algorithms I. Acquired knowledge makes a presumption for understanding of new topics. Selected lecture notes give a ground for practical exercises. nVidia CUDA architecture will be presented in more detail will related tools for parallel programming on GPU. Assumption of parallel programming technics in combination with solving of practical tasks makes the most important premises to pass the final exam.
Literature
Advised literature
[1] Bjarne Stroustrup. The C++ Programming Language, 4th Edition. Addison-Wesley Professional, 4th edition, 5 2013.
[2] John Cheng, Max Grossman, and Ty McKercher. Professional CUDA C Programming. Wrox, 1st edition, 9 2014.
[3] Tuomanen, Brian. Hands-On GPU Programming with Python and CUDA: Explore high-performance parallel computing with CUDA. Packt Publishing Ltd, 2018.
[4] Volodymyr Kindratenko, editor. Numerical Computations with GPUs. Springer, 2014 edition, 7 2014.
[5] Vaidya, Bhaumik. Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA: Effective techniques for processing complex image data in real time using GPUs. Packt Publishing Ltd, 2018.
[6] Jung W. Suh and Youngmin Kim. Accelerating MATLAB with GPU Computing: A Primer with Examples. Morgan Kaufmann, 1st edition, 12 2013.
[2] John Cheng, Max Grossman, and Ty McKercher. Professional CUDA C Programming. Wrox, 1st edition, 9 2014.
[3] Tuomanen, Brian. Hands-On GPU Programming with Python and CUDA: Explore high-performance parallel computing with CUDA. Packt Publishing Ltd, 2018.
[4] Volodymyr Kindratenko, editor. Numerical Computations with GPUs. Springer, 2014 edition, 7 2014.
[5] Vaidya, Bhaumik. Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA: Effective techniques for processing complex image data in real time using GPUs. Packt Publishing Ltd, 2018.
[6] Jung W. Suh and Youngmin Kim. Accelerating MATLAB with GPU Computing: A Primer with Examples. Morgan Kaufmann, 1st edition, 12 2013.