Firing Up 750 Raspberry Pis

January 24, 2018 by Al Williams 37 Comments

Creating Raspberry Pi clusters is a popular hacker activity. Bitscope has been commercializing these clusters for a bit now and last year they created a cluster of 750 Pis for Los Alamos National Labs. You might wonder what an institution know for supercomputers wants with a cluster of Raspberry Pis. Turns out it is tough to justify taking a real high-speed cluster down just to test software. Now developers can run small test programs with a large number of CPU cores without requiring time on the big iron.

On the face of it, this doesn’t sound too hard, but hooking up 750 of anything is going to have its challenges. You have to provide power and carry away heat. They all have to communicate, and you aren’t going to want to house the thing in a few hundred square feet which makes heat and power even more difficult.

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Imagine A Cluster Of ESP32s

January 14, 2018 by Jenny List 24 Comments

When the ESP32 microcontroller first appeared on the market it’s a fair certainty that somewhere in a long-forgotten corner of the Internet a person said: “Imagine a Beowulf cluster of those things!”.

Someone had to do it, and it seems that the someone in question was [Kodera2t], who has made a mini-cluster of 4 ESP32 modules on a custom PCB. They might not be the boxed computers that would come to mind from a traditional cluster, but an ESP32 module is a little standalone computer with processing power that wouldn’t have looked too bad on your desktop only in the last decade. The WiFi on an ESP32 would impose an unacceptable overhead for communication between processors, and ESP32s are not blessed with wired Ethernet, so instead the board has a parallel bus formed by linking together a group of GPIO lines. There is also a shared SPI SRAM chip with a bus switchable between the four units by one of the ESp32s acting as the controller.

You might ask what the point is of such an exercise, and indeed as it is made clear, there is no point beyond interest and edification. It’s unclear what software will run upon this mini-cluster as it has so far only just reached the point of a first hardware implementation, but since ESP32 clusters aren’t exactly mainstream it will have to be something written especially for the platform.

This cluster may be somewhat unusual, but in the past we’ve brought you more conventional Beowulf clusters such as this one using the ever-popular Raspberry Pi.

Terrible Cluster Of PIs

October 11, 2017 by Al Williams 36 Comments

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

July 17, 2017 by Al Williams 50 Comments

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

April 9, 2017 by Dan Maloney 8 Comments

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

March 16, 2017 by Will Sweatman 16 Comments

[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

December 19, 2016 by Al Williams 26 Comments

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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