Deep Belief Nets in C++ and CUDA C: Volume 3: Convolutional Nets
Deep Belief Nets in C++ and CUDA C: Volume 3: Convolutional Nets
Автор: Timothy Masters
Дата выхода: 2018
Издательство: Apress Media, LLC.
Количество страниц: 184
Размер файла: 1,3 МБ
Тип файла: PDF
This book is a continuation of Volumes 1 and 2 of this series. Numerous references are made to material in the prior volumes, especially in regard to coding threaded operation and CUDA implementations. For this reason, it is strongly suggested that you be at least somewhat familiar with the material in Volumes 1 and 2. Volume 1 is especially important, as it is there that much of the philosophy behind multithreading and CUDA hardware accommodation appears.
All techniques presented in this book are given modest mathematical justification, including the equations relevant to algorithms. However, it is not necessary for you to understand the mathematics behind these algorithms. Therefore, no mathematical background beyond basic algebra is necessary.
The two main purposes of this book are to present important convolutional net algorithms in thorough detail and to guide programmers in the correct and efficient programming of these algorithms. For implementations that do not use CUDA processing, the language used here is what is sometimes called enhanced C, which is basically C that additionally employs some of the most useful aspects of C++ without getting into the full C++ paradigm. Strict C (except for CUDA extensions) is used for the CUDA algorithms. Thus, you should ideally be familiar with C and C++, although my hope is that the algorithms are presented sufficiently clearly that they can be easily implemented in any language.