In the last section, we saw many advantages of using the Python programming language. It is also mentioned that Python is much slower than C or C++. So, it will be beneficial if it can leverage the parallel processing capability of a GPU. Python provides a PyCUDA wrapper that can utilize the parallel computing capability of a GPU by using the Nvidia CUDA API. Python also has a PyOpenCL module that can be used for parallel computation on any GPU.
Then, one question you might ask is why you have to use PyCUDA, which is specific to Nvidia GPUs. There are many advantages of using PyCUDA over other similar modules; the following are the reasons:
- It provides an easy interface with CUDA API for Python developers and has good documentation, which make it easy to learn.
- The full power of CUDA API provided by Nvidia can be used within Python code using...
