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.
General
Imprint: |
Crc Press
|
Country of origin: |
United States |
Series: |
Chapman & Hall/CRC The R Series |
Release date: |
June 2015 |
First published: |
2015 |
Authors: |
Norman Matloff
|
Dimensions: |
234 x 156 x 23mm (L x W x T) |
Format: |
Hardcover - Cloth over boards
|
Pages: |
328 |
ISBN-13: |
978-1-4665-8701-4 |
Categories: |
Books >
Computing & IT >
Computer hardware & operating systems >
General
|
LSN: |
1-4665-8701-6 |
Barcode: |
9781466587014 |
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