Continuing with our hands-on experience, we now focus on our most important chapter, about using Python-only code, which essentially simplifies the GPU computing approach. We will revisit Anaconda and after a short reintroduction including Miniconda, we will begin our exploration by looking into it with a GPU computing perspective. In particular, CuPy and Numba will be covered to highlight the significance of Python-only syntax for GPU computing. We will carry out the same by seamlessly restructuring our earlier examples in a much simpler manner through CuPy and Numba.
Python programming enthusiasts will be encouraged to invoke NVIDIA GPUs within their program code with CuPy and CUDA-enabled Numba, while also not excluding AMD GPU users from experimenting with ROCm-enabled Numba. We start with gaining an understanding of how a CuPy...
