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Big CPU, Big Data

To study parallel programming with this book, you’ll need the following prerequisite knowledge: Java programming; C programming (for GPU programs); computer organization concepts (CPU, memory, cache, and so on); operating system concepts (threads, thread synchronization). This link for educational purpose only. Please remove file from your computer after familiarization.

To study parallel programming with this book, you’ll need the following prerequisite knowledge: Java programming; C programming (for GPU programs); computer organization concepts (CPU, memory, cache, and so on); operating system concepts (threads, thread synchronization).

My pedagogical style is to teach by example. Accordingly, this book consists of a series of complete parallel program examples that illustrate various aspects of parallel programming. The example programs’ source code is listed on the right-hand pages, and explanatory narrative is on the left-hand pages. The example source code is also included in the PJ2 download. To write programs well, you must first learn to read programs; so please avoid the temptation to gloss over the source code listings, and carefully study both the source code and the explanations.

Also study the PJ2 Javadoc documentation for the various classes used in the example programs. The Javadoc includes comprehensive descriptions of each class and method. Space does not permit describing all the classes in detail in this book; read the Javadoc for further information.

The book consists of these parts:

  • Part I covers introductory concepts.
  • Part II covers parallel programming for multicore computers.
  • Part III covers parallel programming for compute clusters.
  • Part IV covers parallel programming on GPUs.
  • Part V covers big data parallel programming using map-reduce.

Book year:

Book pages: 424

Book language: en

File size: 12.00 MB

File type: pdf

Published: 26 May 2022 - 14:00