Parallel Computing for Data Science: With Examples in R, C++ and CUDA: 28 (Chapman & Hall/CRC The R Series)

Book Details:

• Author: Norman Matloff

• Publisher: CRC Press

• Edition: 1

• Binding: Paperback

• Format: Import

• Release Date: 18-12-2020

• ISBN: 9780367738198

• Language: English

• Pages: 328

• Cover: Paperback

• Dimensions: 9.0 x 6.1 x 0.9 inches

About The Book:

Parallel Computing for Data Science: With Examples in R, C++, and CUDA is one of the pioneering works in parallel computing that focuses exclusively on parallel data structures, algorithms, software tools, and applications in data science. This comprehensive guide presents an in-depth look at the essential concepts of parallel programming, with a particular emphasis on data science applications.

The book provides numerous examples drawn from various data science fields, including classic "n observations, p variables" matrix formats, time series, network graph models, and other data structures commonly encountered in real-world applications. These examples highlight the challenges and solutions in parallel programming, giving readers a hands-on approach to parallel computing.

Focusing on computational efficiency, the book explores how to perform computations on three types of platforms: multicore systems, clusters, and graphics processing units (GPUs). It also addresses software packages that can span multiple hardware platforms and be used with different programming languages. Although examples in R, C++, and CUDA are provided, the foundational knowledge in this book is designed to be easily transferable to other languages, such as Python and Julia.

This book is a valuable resource for data scientists, researchers, and students looking to expand their understanding of parallel computing techniques and their application to data science.