Terrible Cluster of PIs

When we first saw [Ajlitt’s] Hackaday.io project Terrible Cluster we thought, perhaps, he meant terrible in the sense of the third definition:

3. exciting terror, awe, or great fear; dreadful; awful. (Dictionary.com)

After looking at the subtitle, though, we realized he just meant terrible. The subtitle, by the way, is: 5 Raspberry PI Zeros. One custom USB hub. Endless disappointment.

There are four Raspberry Pi Zero boards that actually compute and one Raspberry Pi Zero W serves as a head node and network router. The total cost is about $100 and half of that is in SD cards. There’s a custom USB backplane and even a 3D-printed case.

At first, using five tiny computers in a cluster might not seem like a big deal. Benchmarking shows the cluster (with a little coaxing) could reach 1.281 GFLOPS, with an average draw of 4.962W. That isn’t going to win any world records. However, the educational possibilities of building a $100 cluster that fits in the palm of your hand is interesting. Besides, it is simply a cute build.

We’ve seen much larger Pi clusters, of course. You might be better off with some desktop CPUs, but — honestly — not much better.

Using the GPU from JavaScript

Everyone knows that writing programs that exploit the GPU (Graphics Processing Unit) in your computer’s video card requires special arcane tools, right? Well, thanks to [Matthew Saw], [Fazil Sapuan], and [Cheah Eugene], perhaps not. At a hackathon, they turned out a Javascript library that allows you to create “kernel” functions to execute on the GPU of the target system. There’s a demo available with a benchmark which on our machine sped up a 512×512 calculation by well over five times. You can download the library from the same page. There’s also a GitHub page.

The documentation is a bit sparse but readable. You simply define the function you want to execute and the dimensions of the problem. You can specify one, two, or three dimensions, as suits your problem space. When you execute the associated function it will try to run the kernels on your GPU in parallel. If it can’t, it will still get the right answer, just slowly.

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Industrial Indicator Makes the Move from PLC to FPGA

Industrial controls are fun to use in a build because they’re just so — well, industrial. They’re chunky and built to take a beating, both from the operating environment and the users. They’re often power guzzlers, though, so knowing how to convert an industrial indicator for microcontroller use might be a handy skill to have.

Having decided that an Allen-Bradley cluster indicator worked with the aesthetic of his project, a Halloween prop of some sort, [Glen] set about dissecting the controls. Industrial indicators usually make that a simple task so that they can be configured for different voltages in the field, and it turned out that the easiest approach to replacing the power-hungry incandescent bulbs with LEDs was to build a tiny PCB to fit inside the four-color lens.

The uniquely shaped board ended up being too small for even series resistors for the LEDs, so a separate driver board was also fabbed. The driver board is set up to allow a single 5-volt supply and logic levels of 3.3-volt or 5-volt, making the indicator compatible with just about anything. The finished product lends a suitably sinister look to the prop.

If you’re not familiar with the programmable logic controllers such an indicator would be used with in the field, then maybe you should try running Pong on a PLC for a little background.

Super Computing with Mini ITX Cluster

[Colin Alston] was able to snag a handful of Mini ITX motherboards for cheap and built a mini super computer he calls TinyJaguar. Named partly after the AMD Sempron 2650 APU, the TinyJaguar boasts four, yes that’s four MSI AM1I Mini-ITX motherboards, each with 4GB of DDR memory.

A Raspberry Pi with custom software manages the cluster, and along with some TTL and relays, controls the power to the four nodes. The mini super computer resides in a custom acrylic case held together by an array of 3D printed parts and fasteners.There’s even a rack-like faceplate near the bottom to host the RPi, an Ethernet switch, an array of status LEDs, and the two buttons.

With 16 total cores of computing power (including GPU), the TinyJaguar is quite capable of doing some pretty cool stuff such as running Jupyter notebook with IPyParallel. [Colin] ran into some issues getting the GPU to behave with PyOpenCL. It took a bit of pain and time, but in the end he was able to get the GPUs up, and wrote a small message passing program to show two of the cores were up and working together.

Be sure to check out [Colin’s] super computer project page, specifically the ten project logs that walk through everything that went into this build. He also posted his code if you want to take a look under the hood.

80-PIC32 Cluster Does Fractals

One way to get around limitations in computing resources is to throw more computers at the problem. That’s why even cheap consumer-grade computers and phones have multiple cores in them. In supercomputing, it is common to have lots of processors with sophisticated sharing mechanisms.

[Henk Verbeek] decided to take 80 inexpensive PIC32 chips and build his own cluster programmed in — of all things — BASIC. The devices talk to each other via I2C. His example application plots fractals on another PIC32-based computer that has a VGA output. You can see a video of the device in action, below.

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Hackaday Links: September 25, 2016

So you like watching stupid stuff? Here you go, a scene from Bones that tops the infamous ‘IP backtrace with Visual Basic’ or ‘four-handed keyboard’ scenes from other TV shows. Someone hacked the bones by embedding malware in a calcium fractal pattern. Also, when she uses the fire extinguisher, she doesn’t spray the base of the fire.

Raspberry Pi! You have no idea how good the term Raspberry Pi is for SEO. Even better is Raspberry Pi clusters, preferably made with Raspberry Pi Zeros. Here’s a Raspberry Pi hat for four Raspberry Pi Zeros, turning five Raspberry Pis into a complete cluster computer. To be honest and fair, if you’re looking to experiment with clusters, this probably isn’t a bad idea. The ‘cluster backplane’ is just a $2 USB hub chip, and a few MOSFETs for turning the individual Pis on and off. The Zeros are five bucks a pop, making the entire cluster cost less than two of the big-boy sized Pi 3s.

Do you think you might have too much faith in humanity? Don’t worry, this video has you covered.

Hacking on some Lattice chips? Here’s a trip to CES for you. Lattice is holding a ‘hackathon’ for anyone who is building something with their chips. The top prize is $5k, and a trip to next year’s CES in Vegas, while the top three projects just get the trip to Vegas. If you already have a project on your bench with a Lattice chip, it sounds like a great way to wait an hour for a cab at McCarran.

UPSat. What’s an upsat? Not much, how about you? The first completely open source hardware and software satellite will soon be delivered to the ISS. Built by engineers from the University of Patras and the Libre Space Foundation, the UPSat was recently delivered to Orbital ATK where it will be delivered to the ISS by a Cygnus spacecraft. From there, it will be thrown out the airlock via the NanoRacks deployment pod.

The Voyager Golden Record is a message in a bottle thrown into the cosmic ocean and a time capsule from Earth that may never be opened. Now it’s a Kickstarter. Yes, this record is effectively Now That’s What I Call Humanity volume 1, but there are some interesting technical considerations to the Voyager Golden Record. To the best of my knowledge, no one has ever tried to extract the audio and pictures from this phonographic time capsule. The pictures included in the Golden Record are especially weird, with the ‘how to decode this’ message showing something like NTSC, without a color burst, displayed on a monitor that is effectively rotated 90 degrees counterclockwise from a normal CRT TV. Want to know how to get on Hackaday? Get this Golden Record and show an image on an oscilloscope. I’d love to see it, if only because it hasn’t been done before by someone independent from the original project.

Raspberry Pi Hive Mind

Setting up a cluster of computers used to be a high-end trick used in big data centers and labs. After all, buying a bunch of, say, VAX computers runs into money pretty quickly (not even counting the operating expense). Today, though, most of us have a slew of Raspberry Pi computers.

Because the Pi runs Linux (or, at least, can run Linux), there are a wealth of tools out there for doing just about anything. The trick is figuring out how to install it. Clustering several Linux boxes isn’t necessarily difficult, but it does take a lot of work unless you use a special tool. One of those tools is Docker, particularly Docker Swarm Mode. [Alex Ellis] has a good video (see below) showing the details of a 28 CPU cluster.

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