Hands-On GPU Computing with Python

Converting CUDA code into cross-platform HIP code with hipify

As we begin understanding ROCm for both AMD and NVIDIA GPUs, what can be more practical than a hands-on approach to converting our first CUDA program in this book into an ROCm HIP version? Follow these steps to achieve that:

1. Make sure you have the Terminal open at the location where you have the gpu_multiply.cu file created for understanding CUDA.
2. Assuming you have hipify installed, as described previously in Chapter 4, Fundamentals of GPU Programming, let's use the following command to port the .cu program into a more familiar .cpp program extension:

$ hipify gpu_multiply.cu -o gpu_multiply_ported_to_hip.cpp

We have now HIPified CUDA! Note the replacement of cuda prefixes to ...