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)

Fast Fourier transforms with cuFFT

Now let's look at how we can do some basic fast Fourier transforms (FFT) with cuFFT. First, let's briefly review what exactly a Fourier transform is. If you have taken an advanced Calculus or Analysis class, you might have seen the Fourier transform defined as an integral formula, like so:

What this does is take f as a time domain function over x. This gives us a corresponding frequency domain function over "ξ". This turns out to be an incredibly useful tool that touches virtually all branches of science and engineering.

Let's remember that the integral can be thought of as a sum; likewise, there is a corresponding discrete, finite version of the Fourier Transform called the discrete Fourier transform (DFT). This operates on vectors of a finite length and allows them to be analyzed or modified in the frequency...