Author: Al Williams

4576 Articles

The FPGA Chronicles: Open Source It

October 5, 2026 by 4 Comments

Last time, we looked at getting started with the GOWIN tools and a Tang Nano 20K FPGA. The software from GOWIN isn’t bad, but it isn’t open source, and there are a few oddities about it. In addition, simulation is through a third-party simulation package that has undergone some changes since an acquisition. There are tons of free simulation programs that are extremely good, and there is an open-source toolchain for the FPGA.

You could go grab everything you need piece by piece. But you don’t have to. There are several efforts to produce a toolchain from all the different pieces. We’re going to look at APIO.

APIO

APIO isn’t so much an FPGA toolchain project as it is an aggregator of toolchain projects. It reminded us of PlatformIO, and notes that it was inspired by it. It updates the tools you need, includes its own libraries, and gives you a common workflow across the FPGAs it supports.

You can download it for the command line, but you can also install it as a Visual Studio Code extension, which is what I did. You have to create a simple file that describes your project, and that’s about it.

Install Problems

Since APIO has its own libraries, it is possible that you will find some conflicts with your system libraries. In my case, the libreadline.so.8 file (in ~/.apio/bin/_internal) was causing problems that prevented anything from working. I simply renamed it out of the way, or you can just delete it. That took care of the problem.

Keep in mind that APIO just orchestrates a bunch of other tools like Yosys and GTKWave. Even if you have your own versions, APIO expects to use its private copies. For example, GTKWave on my system is a different version than the APIO copy, and if I try to read wave files without using APIO, I get error messages. You can, however, open a shell from the Tools/Misc menu of the APIO panel in Visual Studio Code.

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Tearing Down A Heavy Oscilloscope

October 4, 2026 by 12 Comments

When [Thomas] showed his 1960s-era Tektronix 545A oscilloscope in a recent video, it made us both nostalgic and happy. Nostalgic because we miss the days when our oscilloscopes were “mainframes” that could take plug-in modules. Happy because we noticed the two handles on top to manage hauling the almost 70 pounds of tubes, transformers, and glass around if you didn’t have the requisite cart.

Not only did old scopes have plugins so you could reconfigure them, but there were also handy plugins and racks that could power them so you could build different test setups easily. This scope was an early version of that idea, but it only accepted a vertical section plugin. The mainframe part of the scope has 75 tubes, and the plugin, a type D, has six tubes, too. The power consumption was about 500 watts!

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Motion Control Via Belt

October 4, 2026 by 1 Comment

[Tolko] wanted to encourage kids to have some physical activity, but noted that they only wanted to play games. That led to BlobJump, a Raspberry Pi-based game sort of like the famous dinosaur runner game. The difference? Your body — or more precisely, a belt worn on your body — is the controller. Your jumping and ducking make your on-screen avatar do the same thing. Watch the video below to see the game in action.

Each belt contains an ESP32-C3, an MPU-6050, and enough rechargeable battery to make it all work. Everything is wireless, of course. We didn’t see any video of the actual kids, so we don’t know how active they were or whether they figured out they could just have a seat and move the belts in their hands. Even so, it looks like a fun game.

We couldn’t help but think that, beyond encouraging activity, this might be a great project to get a kid excited about building hardware and software. You could certainly do worse in that department.

This isn’t a totally new idea, but we liked the execution. If you are truly lazy, you can skip playing the game completely.

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AI On Your Gaming PC

October 4, 2026 by 14 Comments

If you want to experiment with LLMs, you typically have a choice of sending your requests to someone else’s computer or fielding a very large GPU and CPU setup to run models locally. However, a recent crop of projects aims to bring bigger models to much more modest hardware.

One example is Strata, a project from [Niko1221], which lets you run a 125-billion-parameter LLM on hardware you might already have for gaming. It won’t run on your old Pentium laptop, but it doesn’t require a supercomputer-like farm of graphics cards, either.

Strata can use several Qwen3.8 model variants, including different quantizations of the original model as well as coding and other specialized versions. Qwen3.8-Flash-Next is a mixture-of-experts model containing 24,576 small experts, of which only ten are needed for each token. The clever part is that Strata effectively treats VRAM as a cache for the much larger model. Frequently used experts stay on the GPU, while the complete collection normally remains in system RAM. The model also includes a roughly 29 GB lookup table that stays on the SSD and is accessed as needed.

The software also uses the model’s multi-token prediction machinery for speculative decoding, allowing several candidate tokens to be checked in a single pass. According to the project, an RTX 5070 with 12 GB of VRAM can produce roughly 50 to 90 tokens per second, depending on quantization. Tokens, of course, aren’t usually entire words, but it is still a respectable clip, once everything gets set up.

We did have some trouble setting everything up due to some incompatibility with the NVIDIA C compiler, our gcc version, and some headers, but your problems will surely be different. The setup.sh file asks you a few questions on the first run. After that, it just handles your selected startup options, which can take a few minutes while everything loads.

Once running, Strata lets you interact through a web browser. It also exposes OpenAI- and Anthropic-compatible APIs on localhost, so existing chat front ends, coding assistants, and other tools can use the local model without much special handling. Of course, you can’t expect its answers to compete with the big models out there for every task. When asking about Hackaday, for example, it got a lot of it right but also got confused about who founded the site and our authors (unless we forgot that [Tom Nardelli] once wrote some posts). Turning up the “thinking level” and turning down the temperature didn’t help much, although it did move its confusion to different facts. It did better when asked to identify some problem code or outline how to port a particular C compiler to a new target.

You’ll still want at least 32 GB of system RAM, 12 GB of VRAM, and around 80 GB of storage, so “modest” is relative. Still, it’s a neat demonstration of how mixture-of-experts models and some clever memory management can stretch ordinary PC hardware surprisingly far.

These economical LLMs can even run on older hardware, just slower.

That’s No Moon… That’s An Exoplanet!

October 3, 2026 by 6 Comments

It wasn’t that long ago that a science teacher would have told students that there was no evidence of planets around other star systems. Even more recently, they might have said that while we’ve seen evidence of extra-solar planets, we would never be able to see them directly. But that’s all changed. [Jason Wang] has several videos that use images taken over years to visualize the orbit of several large exoplanets.

Of course, some extrapolation is involved. According to [Jason]:

We unfortunately do not have the luxury of watching these planets every night and record them. However, these planets move slowly, with orbital periods at least decades long, and predictably following Kepler’s laws. We can use a technique called motion interpolation to reconstruct what the image should look like using images taken before and after the date we are interested in. Motion interpolation is a technique commonly found in video editing and in modern TVs.

You have to be a patient photographer, apparently. One video has 30 images taken over 17 years, for example. Another has 10 images from the Keck Observatory taken over 12 years.

The work has fed scientific papers like this one or this one. While it might be more fun to see these star systems from the bridge of your favorite starship, this is probably as close as you are going to get.

We find both the prospect of exoplanets and the technology used to find them exciting

Power It With Sodium (But Please Don’t)

October 1, 2026 by 18 Comments

[Applied Science] has a new demo of an old 1970s patent for a portable generator that is both interesting and terrifying. The generator uses sodium and water, which, if you remember your old chemistry classes, will combust spontaneously. Turns out, though, it won’t if you draw power from it fast enough. Don’t draw enough power? BOOM, apparently. Check it out in the video below.

Of course, lithium-ion batteries might catch fire, too, but this looks a lot more likely. The patent made some wild claims about how much you could draw from the device, but the video shows that practical results are somewhat less.

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A Mechanical Radio, Sort Of

October 1, 2026 by 41 Comments

[The Mike Stuff] has an interesting proposition. He asserts that ancient people like the Greeks could have built a form of radio that was purely mechanical. We aren’t sure we agree, but even if it were possible, we are sure it would have sounded awful. You can see the details in the video below.

The idea is that you can compress air with a waterwheel, blow it through a rotating disk with slots in it, and a valve to amplitude modulate the airflow through the disk. Horns like an old gramophone speaker would amplify the signal at both ends. The demodulation is straightforward and doesn’t even require power, like compressed air.

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