- 07, Mar 2019
- #1
This book teaches you how to write parallel programs for multicore machines, compute clusters, GPU accelerators, and big data map-reduce jobs, in the Java language, with the free, easy-to-use, object-oriented Parallel Java 2 Library.
The book also covers how to measure the performance of parallel programs and how to design the programs to run as fast as possible.
The goal of this book is to teach you how to write parallel programs that take full advantage of the vast processing power of modern multicore computers, compute clusters, and graphics processing unit (GPU) accelerators.
To study parallel programming with this book, you'll need the following prerequisite knowledge: Java programming; C programming (for GPU pro grams); computer organization concepts (CPU, memory, cache, and so on); operating system concepts (threads, thread synchronization).
BIG CPU, BIG DATA: Solving the World's Toughest Problems with Parallel Computing
The book also covers how to measure the performance of parallel programs and how to design the programs to run as fast as possible.
The goal of this book is to teach you how to write parallel programs that take full advantage of the vast processing power of modern multicore computers, compute clusters, and graphics processing unit (GPU) accelerators.
To study parallel programming with this book, you'll need the following prerequisite knowledge: Java programming; C programming (for GPU pro grams); computer organization concepts (CPU, memory, cache, and so on); operating system concepts (threads, thread synchronization).
BIG CPU, BIG DATA: Solving the World's Toughest Problems with Parallel Computing
