While I have tried my best to be as simple as possible in explaining the concepts in this book, knowledge of the basics of programming paradigms will be a big help to you.

This book uses the Ubuntu 18.04 LTS Linux operating system for the hands-on examples. Running the code on an Ubuntu system would, thus, be an ideal choice.

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

1. Log in or register at www.packt.com.
2. Select the SUPPORT tab.
3. Click on Code Downloads & Errata.
4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

• WinRAR/7-Zip for Windows
• Zipeg/iZip/UnRarX for Mac
• 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Hands-On-GPU-Computing-with-Python. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://www.packtpub.com/sites/default/files/downloads/9781789341072_ColorImages.pdf.

Visit the following link to check out videos of the code being run: http://bit.ly/2Jb0liA

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "All the elements of the p and q arrays are set to 24 and 12 respectively"

A block of code is set as follows:

  // Run function on 500 Million elements on the CPU
  begin = clock();
  multiply(N, p, q);
  end = clock();
  cpu_time_used = ((double) (end - begin)) / CLOCKS_PER_SEC;

Any command-line input or output is written as follows:

$ g++ cpu_multiply.cpp -o cpu_multiply
$ ./cpu_multiply

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Choose New Project from the PyCharm main menu."