Easy Carrier Board For The Compute Module 4 Shows You Can Do It, Too

The Raspberry Pi Compute Module 4 has got many excited, with a raft of new features bringing exciting possibilities. However, for those used to the standard Raspberry Pi line, switching over to the Compute Module form factor can be daunting. To show just how easy it is to get started, [timonsku] set about producing a quick and dirty carrier board for the module at home.

The Twitter thread goes into further detail on the design of the board. The carrier features HDMI, USB-A and USB-C ports, as well as a microSD slot. It’s all put together on a single-sided copper PCB that [timonsku] routed at home. The board was built as an exercise to show that high-speed signals and many-pin connectors can be dealt with by the home gamer, with [timonsku] sharing tips on how to get the job done with cheap, accessible tools.

The board may look rough around the edges, but that’s the point. [timonsku] doesn’t recommend producing PCBs at home when multi-layer designs can be had cheaply from overseas. Instead, it serves to show how little is really required to design a carrier board that works. Even four-layer boards can be had for under $10 apiece now, so there’s never been a better time to up your game and get designing.

For those eager to learn more about the CM4, we’ve got a full breakdown to get you up to speed!

Adventures In Overclocking: Which Raspberry Pi 4 Flavor Is Fastest?

There are three different versions of the Raspberry Pi 4 out on the market right now: the “normal” Pi 4 Model B, the Compute Module 4, and the just-released Raspberry Pi 400 computer-in-a-keyboard. They’re all riffing on the same tune, but there are enough differences among them that you might be richer for the choice.

The Pi 4B is easiest to integrate into projects, the CM4 is easiest to break out all the system’s features if you’re designing your own PCB, and the Pi 400 is seemingly aimed at the consumer market, but it has a dark secret: it’s an overclocking monster capable of running full-out at 2.15 GHz indefinitely in its stock configuration.

In retrospect, there were hints dropped everywhere. The system-on-a-chip that runs the show on the Model B is a Broadcom 2711ZPKFSB06B0T, while the SOC on the CM4 and Pi 400 is a 2711ZPKFSB06C0T. If you squint just right, you can make out the revision change from “B” to “C”. And in the CM4 datasheet, there’s a throwaway sentence about it running more efficiently than the Model B. And when I looked inside the Pi 400, there was this giant aluminum heat spreader attached to the SOC, presumably to keep it from overheating within the tight keyboard case. But there was one more clue: the Pi 400 comes clocked by default at 1.8 GHz, instead of 1.5 GHz for the other two, which are sold without a heat-sink.

Can the CM4 keep up with the Pi 400 with a little added aluminum? Will the newer siblings leave the Pi 4 Model B in the dust? Time to play a little overclocking!

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Trying (And Failing) To Use GPUs With The Compute Module 4

The Raspberry Pi platform grows more capable and powerful with each iteration. With that said, they’re still not the go-to for high powered computing, and their external interfaces are limited for reasons of cost and scope. Despite this, people like [Jeff Geerling] strive to push the platform to its limits on a regular basis. Unfortunately, [Jeff’s] recent experiments with GPUs hit a hard stop that he’s as yet unable to overcome.

With the release of the new Compute Module 4, the Raspberry Pi ecosystem now has a device that has a PCI-Express 2.0 1x interface as stock. This lead to many questioning whether or not GPUs could be used with the hardware. [Jeff] was determined to find out, buying a pair of older ATI and NVIDIA GPUs to play with.

Immediate results were underwhelming, with no output whatsoever after plugging the modules in. Of course, [Jeff] didn’t expect things to be plug and play, so dug into the kernel messages to find out where the problems lay. The first problem was the Pi’s limited Base Address Space; GPUs need a significant chunk of memory allocated in the BAR to work. With the CM4’s BAR expanded from 64MB to 1GB, the cards appeared to be properly recognised and ARM drivers were able to be installed.

Alas, the story ends for now without success. Both NVIDIA and ATI drivers failed to properly initialise the cards. The latter driver throws an error due to the Raspberry Pi failing to account for the I/O BAR space, a legacy x86 feature, however others suggest the problem may lay elsewhere. While [Jeff] may not have pulled off the feat yet, he got close, and we suspect with a little more work the community will find a solution. Given ARM drivers exist for these GPUs, we’re sure it’s just a matter of time.

For more of a breakdown on the Compute Module 4, check out our comprehensive article. Video after the break.

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Ethernet Goes To The Ether

Since the ether is an old term for the fictitious space where radio waves propagate, we always thought it was strange that the term ethernet refers to wired communication. Sure, there are wireless devices, but that’s not really ethernet. [Jacek] had the same thought, but decided to do something about it.

What he did is use two different techniques to alter the electromagnetic emission from an ethernet adapter on a Raspberry Pi. The different conditions send Morse code that you can receive at 125 MHz with a suitable receiver.

Practical? Hardly, unless you are looking to exfiltrate data from an air-gapped machine, perhaps. But it does have a certain cool factor. The first method switches the adapter between 10 Mbps and 100 Mbps. The second technique uses a stream of data to accomplish the modulation. The switching method had a range of around 100 meters while the data-based method topped out at about 30 meters. The code is on GitHub if you want to replicate the experiment.

There is plenty of precedent for this sort of thing. In 1976 Dr. Dobb’s Journal published an article about playing music on an Altair 8800 by running code while an AM radio was nearby. We’ve seen VGA adapters forced to transmit data, too.

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“Hey, You Left The Peanut Out Of My Peanut M&Ms!”

Candy-sorting robots are in plentiful supplies on these pages, and with good reason — they’re a great test of the complete suite of hacker tools, from electronics to machine vision to mechatronics. So we see lots of sorters for Skittles, jelly beans, and occasionally even Reese’s Pieces, but it always seems that the M&M sorters are the most popular.

This M&M sorter has a twist, though — it finds the elusive and coveted peanutless candies lurking in most bags of Peanut M&Ms. To be honest, we’d never run into this manufacturing defect before; being chiefly devoted to the plain old original M&Ms, perhaps our sample size has just been too small. Regardless, [Harrison McIntyre] knows they’re there and wants them all to himself, hence his impressive build.

To detect the squib confections, he built a tiny 3D-scanner from a line laser, a turntable, and a Raspberry Pi camera. After scanning the surface to yields its volume, a servo sweeps the candy onto a scale, allowing the density to be calculated. Peanut-free candies will be somewhat denser than their leguminous counterparts, allowing another servo to move the candy to the proper exit chute. The video below shows you all the details, and more than you ever wanted to know about the population statistics of Peanut M&Ms.

We think this is pretty slick, and a nice departure from the sorters that primarily rely on color to sort candies. Of course, we still love those too — take your pick of quick and easy, compact and sleek, or a model of industrial design.

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A Super UPS For The Pi

One of the problems with using a Raspberry Pi or most other systems in a production environment is dealing with sudden shutdowns due to power loss. Modern operating systems often keep data in memory that should be on disk, and a sudden power cycle can create problems. One answer is an uninterruptible power supply, but maintaining batteries is no fun. [Scott] wanted to do better, so he built a UPS using supercapacitors.

A supercapacitor UPS is nearly ideal. The caps charge quickly and don’t wear out as a battery does. The capacitors also don’t care if they stay in storage for a long time. The only real downside is they don’t have the capacity that batteries can have, but for a small computer like a Pi Zero it is pretty easy to gang up enough capacitors to do the job.

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Raspberry Raven Pi Security Camera Does Double Duty

The worst thing about holiday decorations is that while you could leave them up all year, your neighbors probably won’t like you very much for it. Christmas lights on your house are one thing, but as far as Halloween decorations go, [MisterM]’s raven security camera is one of the few exceptions to this rule.

Nevermore will [MisterM] wonder who goes there. As soon as this raven lays its beady red LED eyes on whatever is lurking in the garden, it comes to life with a bit of head swiveling and some random sounds. The bird either goes CAW! or quotes Christopher Lee’s reading of Edgar Allen Poe’s “The Raven”.

Inside this bird’s chest cavity is a Raspberry Pi 2 and standard camera, a servo to swivel the head, and an audio amplifier and speaker. This bird is running MotionEye on top of the Raspi OS so it can run a script whenever it senses motion.

We like that [MisterM] was able to find right-sized bits of plastic to mount the servo in the neck and the horn to the head. It just goes to show that not everything needs a 3D printer, a CNC, or woodworking. Check out the scary demo after the break.

Want to scare the whole neighborhood? Check out the science behind good-looking house projections.

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