Buy Parallel Computing for Data Science: With Examples in R, C++ and CUDA

1st Edition PDF ebook by author Norman Matloff published by Chapman and Hall/CRC in 2016 and save up to 80% compared to the print version of this textbook. With PDF version of this textbook, not only save you money, you can also highlight, add text, underline add post-it notes, bookmarks to pages, instantly search for the major terms or chapter titles, etc.

You can search our site for other versions of the Parallel Computing for Data Science: With Examples in R, C++ and CUDA

1st Edition PDF ebook. You can also search for others PDF ebooks from publisher Chapman and Hall/CRC, as well as from your favorite authors. We have thousands of online textbooks and course materials (mostly in PDF) that you can download immediately after purchase.

Note: e-textBooks do not come with access codes, CDs/DVDs, workbooks, and other supplemental items.

eBook Details:

Full title: Parallel Computing for Data Science: With Examples in R, C++ and CUDA

1st Edition

Edition: 1st

Copyright year: 2016

Publisher: Chapman and Hall/CRC

Author: Norman Matloff

ISBN: 9781466587014, 9781466587038

Format: PDF

Description of Parallel Computing for Data Science: With Examples in R, C++ and CUDA

1st Edition:

Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel computing books to concentrate exclusively on parallel data structures, algorithms, software tools, and applications in data science. It includes examples not only from the classic “n observations, p variables” matrix format but also from time series, network graph models, and numerous other structures common in data science. The examples illustrate the range of issues encountered in parallel programming. With the main focus on computation, the book shows how to compute on three types of platforms: multicore systems, clusters, and graphics processing units (GPUs). It also discusses software packages that span more than one type of hardware and can be used from more than one type of programming language. Readers will find that the foundation established in this book will generalize well to other languages, such as Python and Julia.

## Reviews

There are no reviews yet.