University Team Builds Lego and Raspberry Pi Cluster

hypnosec writes about a neat little hack using Lego, Raspberry Pis, and Scratch to construct a "supercomputer." From the article: "A team of computational engineers over at the University of Southampton led by Professor Simon Cox have built a supercomputer using Raspberry Pi and Lego. The supercomputer is comprised of 64 processors, 1TB of storage (16GB SD cards in each of the Raspberry Pis) and can be powered on using just a single 13-amp mains socket. MPI is used for communications between the nodes through the ethernet port. The team managed to build the core of the supercomputer for under £2500. Named 'Iridis-Pi' after University of Southampton's supercomputer Iridis, the supercomputer runs software that was built using Python and Scratch. Professor Cox used the free plug-in 'Python Tools for Visual Studio' to develop code for the Raspberry Pi." Lots of pictures of the thing, and a howto on making your own.

Comments

Re:Want

[the_humeister]

Unfortunately, the term "supercomputer" isn't really being used properly. They built a cluster of computers, sure. But "supercomputer"??? Hardly. The Raspberry Pi uses a processor based on ARM v6. Lemme give a single-threaded rendering comparison (Povray 3.6 running the benchmark scene (here's what the benchmark image output looks like) with my old HTC Aria, which uses a Qualcomm MSM 7227 processor and has similar processor specs as the Raspberry Pi (ARM v6 + VFP2 floating point hardware):

HTC Aria (MSM 7227 @ 0.6 GHz) *
    Debian 6.0(armel), gcc 4.4, -mfloat-abi=softfp -mthumb
    Parse Time: 0 hours 1 minutes 3 seconds (63 seconds)
    Photon Time: 0 hours 53 minutes 49 seconds (3229 seconds)
    Render Time: 57 hours 31 minutes 41 seconds (207101 seconds)
    Total Time: 58 hours 26 minutes 33 seconds (210393 seconds)

For comparison, here's a faster ARM processor from my Samsung Galaxy S II:

Exynos 4210 @ 1.2 GHz (ARM Cortex A9),
    Debian 7.0(armhf), gcc 4.6, -mcpu=cortex-a9 -mhard-float -mthumb -mfpu=vfpv3 -ffast-math -funsafe-math-optimizations
    Parse Time: 0 hours 0 minutes 4 seconds (4 seconds)
    Photon Time: 0 hours 1 minutes 33 seconds (93 seconds)
    Render Time: 1 hours 26 minutes 34 seconds (5194 seconds)
    Total Time: 1 hours 28 minutes 11 seconds (5291 seconds)

And here's from an Intel Core i5 2400s @ 2.5 GHz:

Core i5 2400s @ 2.5 GHz, Ubuntu 12.04, gcc 4.6, -march=corei7-avx
Total Scene Processing Times
    Parse Time: 0 hours 0 minutes 1 seconds (1 seconds)
    Photon Time: 0 hours 0 minutes 14 seconds (14 seconds)
    Render Time: 0 hours 10 minutes 12 seconds (612 seconds)
    Total Time: 0 hours 10 minutes 27 seconds (627 seconds)

The ARM v6 processor took more than 2 days to render something that takes 10 minutes on a Core i5. So, "supercomputer" this cluster is not.

* You may say, "Hey, this test is running using soft-float! If you used hard float, it'd be faster!" Well, you would be right that it would render faster under hard float, but this processor still wouldn't finish rendering in less than a day, let alone come anywhere close to Core i5 or Cortex A9.

Re:Want

[CastrTroy]

Actually, Just ran a test, because I was a little amazed that the ARM 6 was so much slower than the A9. Here are my numbers. Parse Time: 0 hours 0 minutes 14 seconds (14 seconds) Photon Time: 0 hours 5 minutes 43 seconds (343 seconds) Render Time: 5 hours 58 minutes 53 seconds (21533 seconds) Total Time: 6 hours 4 minutes 50 seconds (21890 seconds) While the Raspberry Pi wasn't faster than the A9 (didn't expect it to be) it was way faster then ARM6 you tested on. Most likely due to the fact that it uses hard float.