学习您需要的任何“Python for dummies”和“numpy for dummies”教程，以快速掌握 Python 的知识。
那么 PyCUDA 将变得完全不言而喻。我花了大约一个小时来消化 PyCUDA，因为我已经知道如何编写可工作的 CUDA 代码并大量使用 Python 和 numpy。
Starting with PyCUDA doesn't eliminate the need to understand how CUDA works and how to program the GPU. Realistically you probably need to do all of the following, and in this order:
Learn enough C to a least have a grasp of the syntax and a thorough understanding of pointers and memory concepts. The latter is really important because in CUDA you are always working with a non-uniform address space. There are dragons a plenty if you can't understand why pointers aren't portable and indirection of pointers in the wrong memory space can't work.
Work through something like CUDA by example to get the hang of the basic ideas behind CUDA programming and how the APIs work.
Do whatever "Python for dummies" and "numpy for dummies" tutorials you need to get up to speed with the Python end of things.
Then PyCUDA will become completely self evident. It took me about an hour to digest PyCUDA coming from a background of already knowing how to write working CUDA code and working a lot with Python and numpy.
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从 PyCUDA 开始并不能消除了解 CUDA 如何工作以及如何对 GPU 进行编程的需要。实际上，您可能需要按照以下顺序执行以下所有操作：
那么 PyCUDA 将变得完全不言而喻。我花了大约一个小时来消化 PyCUDA，因为我已经知道如何编写可工作的 CUDA 代码并大量使用 Python 和 numpy。
Starting with PyCUDA doesn't eliminate the need to understand how CUDA works and how to program the GPU. Realistically you probably need to do all of the following, and in this order:
Then PyCUDA will become completely self evident. It took me about an hour to digest PyCUDA coming from a background of already knowing how to write working CUDA code and working a lot with Python and numpy.