How to structure a CUDA programming learning path
In a publication dated November 9, 2025, an author recommends studying C/C++ and linear algebra before CUDA and suggests books and a course for getting started with GPU programming.
Source: Um caminho sugerido para aprender programação CUDA (amazon.com). Text prepared with AI from this source.
What happened and what to do
In a publication dated November 9, 2025, the author recommends building a foundation in C/C++ and linear algebra before studying CUDA. For beginners, the suggested resources are the books *Programming Massively Parallel Processors* and *Professional CUDA C Programming*, along with a CUDA course.
A company assessing GPU processing can turn this sequence into a technical learning path tied to real use cases: identify candidate workloads, define exercises and evaluation criteria, and test a CUDA prototype. A diagnosis can help determine whether GPU optimization serves business needs before expanding the investment.
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Wendelmaques can assess workloads and GPU opportunities, scope a technical proof of concept or CUDA pipeline, and propose its operation and evolution based on the company’s needs.
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