Raspberry Pi Super Cluster


Raspberry Pi Super Cluster
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Overview
Table of Contents
Author
Support
Sample Chapters
  • Learn about parallel computing by building your own system using Raspberry Pi
  • Build a two-node parallel computing cluster
  • Integrate Raspberry Pi with Hadoop to build your own super cluster

Book Details

Language : English
Paperback : 126 pages [ 235mm x 191mm ]
Release Date : November 2013
ISBN : 1783286199
ISBN 13 : 9781783286195
Author(s) : Andrew K. Dennis
Topics and Technologies : All Books, Application Development, Open Source

Table of Contents

Preface
Chapter 1: Clusters, Parallel Computing, and Raspberry Pi – A Brief Background
Chapter 2: Setting Up your Raspberry Pi Software and Hardware for Parallel Computing
Chapter 3: Parallel Computing – MPI on the Raspberry Pi
Chapter 4: Hadoop – Distributed Applications on the Raspberry Pi
Chapter 5: MapReduce Applications with Hadoop and Java
Chapter 6: Calculate Pi with Hadoop and MPI
Chapter 7: Going Further
Appendix
Index
    • Chapter 2: Setting Up your Raspberry Pi Software and Hardware for Parallel Computing
      • Setting up our work environment
        • HDMI-capable monitor or VGA/DVI monitor and adapter
        • USB keyboard and mouse
        • Two micro-USB power units
        • A desk-mounted power strip with both USB and mains outlets (optional)
        • Three Ethernet/RJ45 network cables
        • A small network switch
        • An existing Internet connection
        • Two SD cards that are compatible with the Raspberry Pi
        • Housing units for the Raspberry Pi boards and Lego (optional)
        • USB hard drives (optional)
      • Future expansion and a scalable setup
      • Completing the initial setup
      • Using an SD card as our Raspberry Pi's storage device
        • SD card setup
        • Formatting our card
          • Mac OS X SD card formatting instructions
          • Windows 8 SD card formatting instructions
          • Linux instructions for SD card formatting
      • BerryBoot version 2
        • Downloading the BerryBoot version 2 ZIP file
          • Mac OS X
          • Windows 8
          • Linux
      • Starting up the Raspberry Pi
        • The installation process
        • Installation complete
        • Testing SSH and setting up keys
        • Connecting via SSH
          • Mac OS X and Linux users
          • Windows 8 users with PuTTY
        • Setting up your SSH RSA keys
          • The ssh-agent and ssh-add tools
          • SSH setup complete
      • Wrapping up
        • Editing text files on Raspbian
        • Installing Fortran
        • Terminal multiplexing with Screen
      • Summary
      • Chapter 3: Parallel Computing – MPI on the Raspberry Pi
        • MPI – Message Passing Interface
        • MPI implementations – MPICH and OpenMPI
        • Creating an environment and downloading MPICH
          • Building and installing MPICH
          • Configuring your Raspberry Pi to run with MPICH
          • Testing our MPICH installation
          • Building our second Raspberry Pi
            • Windows 8
            • Mac OS X
            • Linux
          • Powering up the second Raspberry Pi
          • RSA key setup for SSH
        • Writing an MPI-based application
          • MPI – point-to-point communication
        • Summary
              • Chapter 7: Going Further
                • Booting from an external USB HDD
                • Building a Lego enclosure
                • Experimenting with MPI and Fortran
                • Power for multiple devices
                  • USB wall plates
                  • Battery power
                  • Using a PC power supply
                  • Power over Ethernet
                • Summary
                • Appendix
                  • Fortran and C/C++
                  • MPI, Hadoop, and parallel computing
                  • Raspberry Pi cases and clusters

                  Andrew K. Dennis

                  Andrew K. Dennis is the Manager of Application Development at Prometheus Research. Prometheus Research is a leading provider of integrated data management for research and the home of HTSQL, an open source navigational query language for RDMS. Andrew has a Diploma in Computing and a BS in Software Engineering; he is currently studying a second BS in Creative Computing in his spare time. He has over 10 years of experience working in the software industry in the UK, Canada, and USA. This experience includes e-Learning, CMS and LMS development, SCORM consultancy, web development in a variety of languages, open source application development, and running a blog dedicated to maker culture and home automation. His interests include web development, e-Learning, 3D printing, Linux, the Raspberry Pi and Arduino, open source projects, parallel computing, home automation, amateur electronics, home networking, and software engineering. Many of these topics were covered in his previous book from Packt Publishing, Raspberry Pi Home Automation with Arduino.
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                  Code Downloads

                  Download the code and support files for this book.


                  Submit Errata

                  Please let us know if you have found any errors not listed on this list by completing our errata submission form. Our editors will check them and add them to this list. Thank you.


                  Errata

                  - 4 submitted: last submission 14 Mar 2014

                  Errata type: Code | Page number: 82

                   

                  jar -cvf /home/pi/hadoop/apps/wordcount.jar -C wordcount_classes/

                   

                  Should be:

                   

                  jar cvf /home/pi/hadoop/apps/wordcount.jar -C wordcount_classes/

                   

                  Type: Other | Page number: 79

                   

                   

                  http://hadoop.apache.org/docs/stable/file_system_shell.html

                  Should be :

                  http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-common/FileSystemShell.html

                  Errata type: Technical | Page no.: 69


                  We have one simple configuration task left on our Master Raspberry Pi before
                  we consider the Slave machine. Update the following masters conf file to
                  indicate this is the Master machine:

                  vim /home/pi/hadoop/hadoop-1.2.1/conf/masters

                  To this file add the IP address of this Raspberry Pi.

                  should be:


                  We have one simple configuration task left on our Master Raspberry Pi before
                  we consider the Slave machine. Update the following masters conf file to
                  indicate this is the Master machine:

                  vim /home/pi/hadoop/hadoop-1.2.1/conf/masters

                  To this file replace the IP address of this Raspberry Pi.

                  Errata type: Technical | Page no. 66

                   

                  cd ~/hadoop/hadoop-1.2.1/conf

                   

                  should be:

                   

                  cd ~/hadoop/hadoop-2.2.0/etc/hadoop

                  Sample chapters

                  You can view our sample chapters and prefaces of this title on PacktLib or download sample chapters in PDF format.

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                  What you will learn from this book

                  • Discover how to set up the hardware to build your parallel computing cluster
                  • Set up your Raspberry Pi computers and install an operating system
                  • Network your two Raspberry Pi’s together
                  • Gain an understanding of MPI through practical examples
                  • Learn how to work with MPICH to write parallel applications
                  • Install Hadoop and experiment with processing text files
                  • Get acquainted with MapReduce, the paradigm at the heart of Hadoop

                  In Detail

                  A cluster is a type of parallel/distributed processing system which consists of a collection of interconnected stand-alone computers cooperatively working together. Using Raspberry Pi computers, you can build a two-node parallel computing cluster which enhances performance and availability.

                  This practical, example-oriented guide will teach you how to set up the hardware and operating systems of multiple Raspberry Pi computers to create your own cluster. It will then navigate you through how to install the necessary software to write your own programs such as Hadoop and MPICH before moving on to cover topics such as MapReduce. Throughout this book, you will explore the technology with the help of practical examples and tutorials to help you learn quickly and efficiently.

                  Starting from a pile of hardware, with this book, you will be guided through exciting tutorials that will help you turn your hardware into your own super-computing cluster. You’ll start out by learning how to set up your Raspberry Pi cluster’s hardware. Following this, you will be taken through how to install the operating system, and you will also be given a taste of what parallel computing is about. With your Raspberry Pi cluster successfully set up, you will then install software such as MPI and Hadoop. Having reviewed some examples and written some programs that explore these two technologies, you will then wrap up with some fun ancillary projects. Finally, you will be provided with useful links to help take your projects to the next step.

                  Approach

                  This book follows a step-by-step, tutorial-based approach which will teach you how to develop your own super cluster using Raspberry Pi computers quickly and efficiently.

                  Who this book is for

                  Raspberry Pi Super Cluster is an introductory guide for those interested in experimenting with parallel computing at home. Aimed at Raspberry Pi enthusiasts, this book is a primer for getting your first cluster up and running.

                  Basic knowledge of C or Java would be helpful but no prior knowledge of parallel computing is necessary.

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