Have you ever read about parallel computing clusters and supercomputing, and wondered how to do it at home?
Do you have a number of Raspberry Pis and don't know what to do with them?
Then this is the book for you!
The field of parallel computing is certainly an exciting one. With the introduction of the Raspberry Pi, building a cluster at home is even easier. Hobbyists can now construct a small parallel computing cluster at low cost and using minimal physical space.
This book will walk you through building a parallel computing cluster using two Raspberry Pis and commodity off-the-shelf hardware.
Having set up your cluster, you will explore parallel computing paradigms such as MPI and MapReduce through exciting software projects.
Using MPICH and the C programming language, step-by-step guides will walk you through writing your own MPI-based applications. You will then test these in parallel on your two Raspberry Pis.
Following this, MapReduce will be examined through Apache Hadoop, which you will install and set up. You will then learn to interact with Hadoop by writing programs in Java.
Finally Raspberry Pi Super Cluster provides you with some fun jump-off points where you can explore the topics discussed in the book in further detail.
Having completed the various chapters' projects, you will have gained a basic knowledge of parallel computing and how it can be implemented on Raspberry Pi.
Chapter 1, Clusters, Parallel Computing, and Raspberry Pi – A Brief Background, provides an introduction to the topic of parallel computing and its history. You will also learn a little about the Raspberry Pi and why it is a good fit for experimenting with parallel computing.
Chapter 2, Setting Up your Raspberry Pi Software and Hardware for Parallel Computing, builds upon the first chapter by providing a guide to setting up a two node Raspberry Pi cluster and its associated hardware.
Chapter 3, Parallel Computing – MPI on the Raspberry Pi, introduces the topics of MPI (Message Passing Interface), and MPICH. These are explored through examples in the C programming language.
Chapter 4, Hadoop – Distributed Applications on the Raspberry Pi, explores Apache Hadoop and Java through practical examples. From installing Java through to Hadoop configuration, you will get a taste of the two technologies.
Chapter 5, MapReduce Applications with Hadoop and Java, explores the paradigm of MapReduce: the core technology at the heart of Hadoop.
Chapter 6, Calculate Pi with Hadoop and MPI, expands upon previous chapters with experiments on calculating Pi using Hadoop and MPICH. Here you will work with a Java example and write another C application implementing MPI.
Chapter 7, Going Further, finishes off the book with some projects ranging from building a Lego Raspberry Pi case to writing a Fortran application. You will also learn about some alternative approaches to powering your Raspberry Pi.
Appendix, provides you with a list of resources for further reading and exploration. Links to topics covered in this book are provided for the reader to follow up.
The following list includes the recommended and optional hardware to complete the projects in this book:
Two Raspberry Pi Model B's
An HDMI monitor and cable
USB keyboard
USB mouse
Two Micro-USB power units compatible with the Raspberry Pi
Three network cables
A small network switch
Two Raspberry Pi compatible SD cards
Internet connection
A desk mounted power strip with both USB and mains outlet (optional)
Raspberry Pi cases/project enclosures (optional)
USB hard drive (optional for a project in Chapter 7, Going Further)
Lego (optional)
Have you ever wanted to build your own super computer? Wonder what parallel computing is all about and want to experiment with it? Have a bunch of Raspberry Pis and not sure what to do with them? Then this book is for you.
Aimed at the super computing novice and Raspberry Pi enthusiast alike, this is the perfect introductory text for those wishing to get their hands dirty building their own system.
While some programming experience is required, no prior knowledge of the technologies associated with parallel computing is assumed.
In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles, and an explanation of their meaning.
Code words in text are shown as follows: "Navigate into mpich3 and create the following two directories."
A block of code is set as follows:
/* Hello RPI implemented using MPI */ #include <stdio.h> #include <mpi.h>
Any command-line input or output is written as follows:
ssh [email protected] 'sudo echo "raspberrypi2" | sudo tee /etc/hostname; sudo shutdown -r now'
New terms and important words are shown in bold. Words that you see on the screen, in menus or dialog boxes for example, appear in the text like this: "Select your SD card drive from the Device dropdown on the right-hand side".
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