GPU Programming: CUDA
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F22%3A10250506" target="_blank" >RIV/61989100:27740/22:10250506 - isvavai.cz</a>
Výsledek na webu
<a href="https://events.it4i.cz/event/146/" target="_blank" >https://events.it4i.cz/event/146/</a>
DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
GPU Programming: CUDA
Popis výsledku v původním jazyce
The main goal of the course was to introduce how to program GPU accelerated applications using CUDA programming.We have described the main principles of heterogeneous or accelerated computing (with a short hardware description of the GPU-accelerated supercomputers) needed for a proper understanding of how to design CUDA code.The course was designed for beginners in GPU programming using CUDA. It explained how the parallelisation is done with basic examples, how data transfers are managed between CPU and GPU memory, what types of memory there are in GPU and how to use them, how the parallel threads are executed, and finally, it explained several key parallel computing patterns in CUDA.As the course used the Karolina supercomputer, it was also demonstrated how to write single and multi-GPU applications.
Název v anglickém jazyce
GPU Programming: CUDA
Popis výsledku anglicky
The main goal of the course was to introduce how to program GPU accelerated applications using CUDA programming.We have described the main principles of heterogeneous or accelerated computing (with a short hardware description of the GPU-accelerated supercomputers) needed for a proper understanding of how to design CUDA code.The course was designed for beginners in GPU programming using CUDA. It explained how the parallelisation is done with basic examples, how data transfers are managed between CPU and GPU memory, what types of memory there are in GPU and how to use them, how the parallel threads are executed, and finally, it explained several key parallel computing patterns in CUDA.As the course used the Karolina supercomputer, it was also demonstrated how to write single and multi-GPU applications.
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
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OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
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Návaznosti
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Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů