Building a Compute Cluster with the BeagleBone Black


Building a Compute Cluster with the BeagleBone Black

As a developer, I’ve always been interested in learning about and developing for new technologies. Distributed and parallel computing are two topics I’m especially interested in, leading to my interest in creating a home cluster. Home clusters are of course nothing new and can easily be done using old desktops running Linux. Constantly running desktops (and laptops) consume space, use up a decent amount of power, cost money to set up and can emit a fair amount of heat. Thankfully, there has been a recent explosion of enthusiast interest in cheap arm based computers, the most popular of which is the Raspberry Pi. With a small size, extremely low power consumption and great Linux support, arm based boards are great for developer home projects. While the Raspberry Pi is a great little package and enjoys good community support, I decided to go with an alternative, the BeagleBone Black.

Launched in 2008, the original BeagleBoard was developed by Texas Instruments as an open source computer. It featured a 720 MHz Cortex A8 arm chip and 256MB of memory. The BeagleBoard-xm and BeagleBone were released in subsequent years leading to the BeagleBone Black as the most recent release. Though its $45 price tag is a little higher than a Raspberry Pi, it has a faster 1GHz Cortex 8 chip, 512 MB of RAM and extra USB connections. In addition to 2GB of onboard memory that comes with a pre-installed Linux distribution, there is a micro SD card slot allowing you to load additional versions of Linux and boot to them instead. Thanks to existing support for multiple Linux distributions such as Debian and Ubuntu, BeagleBone Black looked to me like a great inexpensive starting point for creating my very own home server cluster.

Setting up the Cluster

For my personal cluster I decided to start small and try it out with just three machines. The list of equipment that I bought is as follows:

1x 8 port gigabit switch
3x beaglebone blacks
3x ethernet cables
3x 5V 2 amp power supplys
3x 4 GB microSD cards

To keep it simple, I decided to build a command line cluster that I would control through my laptop or desktop. The BeagleBone Black supports HDMI output so you can use them as standalone computers but I figured that would not be necessary for my needs. The simplest way to get the BeagleBone Black running is to use the supplied USB cable to hook it up to an existing computer and SSH to the pre-installed OS. For my project though I chose to use the SD card slot and start with a fresh install. To accomplish this, I had to first load a version of Linux on to each of the thre SD cards. I used my existing Ubuntu Linux machine with a USB SD card reader to accomplish this task.

Initial searches for BeagleBone compatible distributions reveals there are a few places to download them. I decided to go with Ubuntu and found a nice pre-created image from At the time I searched and downloaded, the most recent image was from August but there are now more recent builds. Once you have un-tared the file, you will see a lot of files and directories inside the newly created folder. Included is a nice utility for loading the OS on to an SD card called If you aren’t sure what device Linux is reading your SD card as, you can use the following to show you your devices:

sudo ./ --probe-mmc

On my machine the SD card was listed as /dev/sdb with its main partition showing as /dev/sdb1. If you see the partition listed as I did, you need to unmount it before you can install the image on it. Once the card was ready, I ran the following:

sudo ./ --mmc /dev/sdb --uboot bone

This command took care of the full install of the OS on to the SD card. Once it was finished I repeated I for the other two SD cards. The default user name for the installed distribution is ubuntu with password temppwd. I inserted the SD cards in to the BeagleBones and them connected them to the ethernet switch.

The last step was to power them up and boot them using the micro SD cards. Doing this required holding down the user boot button while connecting the 5V power connector. The button is located on a little raised section near the usb port and tells the device to read from the SD card. Once you see the lights flashing repeatedly you can release the button. Since each instance will have the same default hostname when initially booting, it is advisable to power them on one at a time and follow the steps below to set the IP and hostname before powering up the next one.

Configuring the BeagleBones

Once the hardware is set up and a machine is connected to the network, Putty or any other SSH client can be used to connect to the machines. The default hostname to connect to using the above image is ubuntu-armhf. My first task was to change the hostname. I chose to name mine beaglebone1, beaglebone2 and beaglebone3. First I used the hostname command:

sudo hostname beaglebone1

Next I edited /etc/hostname and placed the new hostname in the file. The next step was to hard code the IP address for so I could probably map it in the hosts file. I did this by editing /etc/network/interfaces to tell it to use static IPs. In my case I have a local network with a router at I decided to start the IP addresses at so the file on the first node looked like this:

    iface eth0 inet static

It is usually a good idea to pick something outside the range of IPs that your router might assign if you are going to have a lot of devices. Usually you can configure this range on your router. With this done, the final step to perform was to edit /etc/hosts and list the name and IP address of each node that would be in the cluster. My file ended up looking like this on each of them:     localhost  beaglebone1  beaglebone2  beaglebone3

Creating a Compute Cluster With MPI

After setting up all 3 BeagleBones, I was ready to tackle my first compute project. I figured a good starting point for this was to set up MPI. MPI is a standardized system for passing messages between machines on a network. It is powerful in that it distributes programs across nodes so each instance has access to the local memory of its machine and is supported by several languages such as C, Python and Java. There are many versions of MPI available so I chose MPICH which I was already familiar with. Installation was simple, consisting of the following three steps:

sudo apt-get update
sudo apt-get install gcc
sudo apt-get install libcr-dev mpich2 mpich2-doc

MPI works by using SSH to communicate between nodes and using a shared folder to share data. The first step to allowing this was to install NFS. I picked beaglebone1 to act as the master node in the MPI cluster and installed NFS server on it:

sudo apt-get install nfs-client

With this done, I installed the client version on the other two nodes:

sudo apt-get install nfs-server

Next I created a user and folder on each node that would be used by MPI. I decided to call mine hpcuser and started with its folder:

sudo mkdir /hpcuser

Once it was created on all the nodes, I synced up the folders by issuing this on the master node:

echo "/hpcuser *(rw,sync)" | sudo tee -a /etc/exports

Then I mounted the master’s node on each slave so they can see any files that are added to the master node:

sudo mount beaglebone1:/hpcuser /hpcuser

To make sure this is mounted on reboots I edited /etc/fstab and added the following:

beaglebone1:/hpcuser    /hpcuser    nfs

Finally I created the hpcuser and assigned it the shared folder:

sudo useradd -d /hpcuser hpcuser

With network sharing set up across the machines, I installed SSH on all of them so that MPI could communicate with each:

sudo apt-get install openssh-server

The next step was to generate a key to use for the SSH communication. First I switched to the hpcuser and then used ssh-keygen to create the key.

su - hpcuser
ssh­keygen ­-t rsa

When performing this step, for simplicity you can keep the passphrase blank. When asked for a location, you can keep the default. If you want to use a passphrase, you will need to take extra steps to prevent SSH from prompting you to enter the phrase. You can use ssh-agent to store the key and prevent this. Once the key is generated, you simply store it in our authorized keys collection:

cd .ssh
cat >> authorized_keys

I then verified that the connections worked using ssh:

ssh hpcuser@beaglebone2

Testing MPI

Once the machines were able to successfully connect to each other, I wrote a simple program on the master node to try out. While logged in as hpcuser, I created a simple program in its root directory /hpcuser called mpi1.c. MPI needs the program to exist in the shared folder so it can run on each machine. The program below simply displays the index number of the current process, the total number of processes running and the name of the host of the current process. Finally, the main node receives a sum of all the process indexes from the other nodes and displays it:

#include <mpi.h>
#include <stdio.h>
int main(int argc, char* argv[])
    int rank, size, total;
    char hostname[1024];
    gethostname(hostname, 1023);
    MPI_Init(&argc, &argv);
    MPI_Comm_rank (MPI_COMM_WORLD, &rank);
    MPI_Comm_size (MPI_COMM_WORLD, &size);
    MPI_Reduce(&rank, &total, 1, MPI_INT, MPI_SUM, 0, MPI_COMM_WORLD);
    printf("Testing MPI index %d of %d on hostname %sn", rank, size, hostname);
    if (rank==0)
        printf("Process sum is %dn", total);
    return 0;

Next I created a file called machines.txt in the same directory and placed the names of the nodes in the cluster inside, one per line. This file tells MPI where it should run:


With both files created, I finally compiled the program using mpicc and ran the test:

mpicc mpi1.c -o mpiprogram
mpiexec -n 8 -f machines.txt ./mpiprogram

This resulted in the following output demonstrating it ran on all 3 nodes:

Testing MPI index 4 of 8 on hostname beaglebone2
Testing MPI index 7 of 8 on hostname beaglebone2
Testing MPI index 5 of 8 on hostname beaglebone3
Testing MPI index 6 of 8 on hostname beaglebone1
Testing MPI index 1 of 8 on hostname beaglebone2
Testing MPI index 3 of 8 on hostname beaglebone1
Testing MPI index 2 of 8 on hostname beaglebone3
Testing MPI index 0 of 8 on hostname beaglebone1
Process sum is 28

Additional Projects

While MPI is a fairly straightforward starting point, a lot of people are more familiar with Hadoop. To test out Hadoop compatibility, I downloaded version 1.2 of Hadoop (hadoop-1.2.1.tar.gz) from the Hadoop downloads at After following the basic set up steps I was able to get it running simple jobs on all nodes. Hadoop, however, shows a major limitation of the BeagleBone which is the speed of SD cards. As a result, using HDFS for jobs is especially slow so you may have mixed luck running anything this is disk IO heavy.

Another great use of the BeagleBones are as web servers and code repositories. It is very easy to install Git and Apache or Node.js the same as you would on other Ubuntu servers. Additionally you can install Jenkins or Hudson to create your own personal build server. Finally, you can utilize all the hookups of the BeagleBone and install xbmc to turn a BeagleBone in to a full media server.

The Future

In addition to single core boards such as the BeagleBones or Raspberry Pi, there are dual core boards starting to appear such as Pandaboard and Cubieboard with likely more on the way. The latter is priced only a little higher than the BeagleBone, supports connecting a 2.5 inch SATA hard disk and features a dual core chip in its latest version. Similar steps to those performed here can be used to set them up, giving hobbyists like me some really good options for home server building. I encourage anyone with the time to try them out and see what you can create.