What is this book about? Hands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning how to apply Amdahl’s Law, use a code profiler to identify bottlenecks in your ...

CUDA is a parallel computing platform and programming model developed by NVIDIA for general computing on its own GPUs (graphics processing ... you’ll have to try your hand at low-level CUDA ...

Replace TORCH with the PyTorch version and CUDA with the CUDA version which you are using ... It provides an easy-to-use mini-batch loader, multi GPU-support, benchmark datasets, and data transforms ...

At the conclusion of the workshop, you’ll have an understanding of the fundamental tools and techniques for GPU-accelerated Python applications with ... ndarrays and ufuncs No previous knowledge of ...

Supported programming languages for CUDA include C, C++, Fortran, Python, and Julia ... processing unit found inside your Nvidia graphics card that handles parallel computing tasks; with more ...

Existing solutions for this problem include using general-purpose computing on graphics processing units (GPGPU) frameworks like CUDA ... Python framework designed to simplify the process of writing ...