Book Image

Hands-On GPU Programming with Python and CUDA

By : Dr. Brian Tuomanen
Book Image

Hands-On GPU Programming with Python and CUDA

By: Dr. Brian Tuomanen

Overview of this book

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 Python code, and set up an appropriate GPU programming environment. You’ll then see how to “query” the GPU’s features and copy arrays of data to and from the GPU’s own memory. As you make your way through the book, you’ll launch code directly onto the GPU and write full blown GPU kernels and device functions in CUDA C. You’ll get to grips with profiling GPU code effectively and fully test and debug your code using Nsight IDE. Next, you’ll explore some of the more well-known NVIDIA libraries, such as cuFFT and cuBLAS. With a solid background in place, you will now apply your new-found knowledge to develop your very own GPU-based deep neural network from scratch. You’ll then explore advanced topics, such as warp shuffling, dynamic parallelism, and PTX assembly. In the final chapter, you’ll see some topics and applications related to GPU programming that you may wish to pursue, including AI, graphics, and blockchain. By the end of this book, you will be able to apply GPU programming to problems related to data science and high-performance computing.
Table of Contents (15 chapters)

Launching compiled code with Ctypes

We will now give a brief overview of the Ctypes module from the Python Standard Library. Ctypes is used for calling functions from the Linux .so (shared object) or Windows. DLL (Dynamically Linked Library) pre-compiled binaries. This will allow us to break out of the world of pure Python and interface with libraries and code that have been written in compiled languages, notably C and C++—it just so happens that Nvidia only provides such pre-compiled binaries for interfacing with our CUDA device, so if we want to sidestep PyCUDA, we will have to use Ctypes.

Let's start with a very basic example: we will show you how to call printf directly from Ctypes. Open up an instance of IPython and type import ctypes. We are now going to look at how to call the standard printf function from Ctypes. First, we will have to import the appropriate...