Abstract:

The GPU is not only a computer device but also a mature computer technology that enables modern computing applications. From games to fluid dynamics, from augmented reality to cryptocurrencies, all these computational technologies are facilitated by the GPU these days. The GPU has been democratized in a vast number of computers and smart phones, and yet, when talking about it, it seems to be an ambiguous term only understood by computer science consultants. In this article, the potential of the GPU is described in different areas of interest to attract attention to the GPU programming learning. Special attention to the education community is offered in this article. Teaching the GPU in all engineering programs should not be optional, but part of today's curricula or course content. Because of how fast this technology has grown and the vast programming tools available these days, introducing into the GPU programming learning could be as complicated that people get lost among principles and implementation. For such reason, in this article a guided route is provided for educators interested in structuring a course content for teaching GPU programming. Such methodology can be used in a formal course for college students as well as for any person in the field interested in learning GPU programming.

Keywords:

GPU programming, learning course, parallel processing.