Raspberry Pi
The GCHQ Bramble Cluster made up of 8 OctiPi clusters and 2 control nodes.
The GCHQ Bramble Cluster made up of 8 OctiPi clusters and 2 head nodes.

(Editor note: A couple of you have pointed out that there is an even larger RPi cluster, “The Beast,” with a jaw-dropping 120 Pis)

When you think about the Raspberry Pi board you probably don’t think about GCHQ — the agency that plays a similar role here in Britain as the NSA does in the US — although you do sometimes think about doughnuts.

However what you probably do think about is computers, big computers, large clusters of them, and that’s what they’ve taken along to this year’s Big Bang Fair — a event for young people celebrating science, technology and engineering being held in Birmingham in the UK — except what they’ve brought along is a cluster built out of Raspberry Pi boards.

Now there have been computing clusters — generally known as ‘Brambles’ — built out of Raspberry Pi’s before, the 64-node MPI-based cluster built by a team at the University of Southampton’s out of Raspberry Pi boards and Lego for instance.

The University of Southampton's Iridis-Pi compute cluster.
The University of Southampton’s Iridis-Pi compute cluster.

But the 66-node cluster, that’s 8 Octopi clusters with two head nodes for control, built by GCHQ is (probably?) the world’s biggest — if you know of one that’s bigger we’d love it if you’d let us know.

The two head nodes managing the cluster using a home grown system. While the team at GCHQ went through several iterations, they eventually settled on one based on node.js, Bootstrap and Angular.

If you want to build your own Bramble the team  at the University of Southampton has put together some instructions. Now all you need is a large box full of Raspberry Pi boards.

13 thoughts on “66 Raspberry Pi Boards Make the World’s Biggest Pi Cluster

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  1. ok, so wtf is the point? just to say you can do it and that its the biggest? why would you need so many raspberry pis? what would a cluster like this be used for?

    1. Like all non-shared memory parallel computers you can use it to do large parallelizable compute jobs using message-passing systems (such as MPI). Clusters like this are used extensively in academia (and industry). With the right sort of problem you can use these sorts of computers to make computational code highly parallel — and hence highly fast.

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Alasdair Allan is a scientist, author, hacker and tinkerer, who is spending a lot of his time thinking about the Internet of Things. In the past he has mesh networked the Moscone Center, caused a U.S. Senate hearing, and contributed to the detection of what was—at the time—the most distant object yet discovered.

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