Book Image

Raspberry Pi Super Cluster

By : Andrew K. Dennis
Book Image

Raspberry Pi Super Cluster

By: Andrew K. Dennis

Overview of this book

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.
Table of Contents (15 chapters)
Raspberry Pi Super Cluster
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Pi with C language and MPI


We have seen that we can calculate П with Hadoop. We can now try a similar application in C. The program we will now write will generate results similar to what we saw with the example program included with MPICH and will also use a MapReduce-style approach.

Create a new file at the following location to store your code in:

~/mpich3/code/monte_carlo_pi.c

Open this file and add the following code:

#include "mpi.h"
#include <stdio.h>
#include <stdlib.h>
#include <time.h>

double insidecircle(int throws);

#define GAMES 20
#define THROWS 100

The previous block of code includes the necessary header files and defines a function and two constants. The function insidercircle() will be responsible for calculating П.

The first constant is the number of GAMES, that is, attempts at calculating П. The second defines the number of THROWS in each game. Now add the following code to the end of the file:

int main (int argc, char *argv[]) {

double jobaverage, calcpi...