Book Review: GPU-Accelerated Computing with Python 3 and CUDA

Book Review: GPU-Accelerated Computing with Python 3 and CUDA Amazon Packt Niels Cautaerts on Medium Hossein Ghorbanfekr on GitHub I was offered to read GPU-Accelerated Computing with Python 3 and CUDA by Niels Cautaerts and Hossein Ghorbanfekr in exchange for an honest review. As a Google Developer Expert in AI/PyTorch, I work with PyTorch a lot, so a deep book on GPU computing in Python was in my area of interest. The book teaches Python developers and scientists to write GPU-accelerated code without dropping into C or C++, and it does this by moving up an abstraction ladder: you start by writing raw CUDA kernels with Numba-CUDA, then switch to high-level libraries like CuPy, RAPIDS, and JAX, and finally build four full applications end-to-end. I often use GPUs, but I use PyTorch/JAX without thinking about the kernels, the memory hierarchy, and the profiler. This book is about the layer underneath that, and I liked how consistently it pushes you to measure what is actually happening…