A few years back NVIDIA created a dedicated cryptocurrency mining GPU, the CMP 170HX. This was a heavily restricted version of its flagship A100 datacenter accelerator, using the same GA100 chip. It was intended for accelerating Ethash, the Etherium proof-of-work algorithm, and nothing else. [niconiconi] bought one to use for accelerating PCB electromagnetic simulations and put a lot of effort into repairing the card, converting it to water-cooling, and figuring out how best to use this nobbled GPU.

Typically, the GA100 silicon sits in the center of the mighty A100 GPU card and would be found in a server rack, cooled by forced air. This was not an option at home, so an off-the-shelf water-cooling block was wedged in. During this process, [niconconi] found that the board wouldn’t power on, so they went on a deep dive into the power supply tree with the help of a leaked A100 schematic. The repair and modifications can be found in the appendix, right down to the end of the article. It is a long read to get there.

NVIDIA has a history of deliberately restricting silicon in consumers’ hands to justify the hefty price tags of its offerings to big businesses, and this board is no different. The plan was to restrict the peak performance of the board to only applications with the same compute requirements as Ethash, specifically memory-intensive algorithms. The FP64 performance was severely limited, but instructions were not removed. This meant the code would run really badly, considering what the GPU is capable of.

The memory was limited to 8 GB, despite some A100 cards hosting a whopping 80 GB. The strategy was to use fuses to limit the crucial instructions, particularly the FP32 FMA and MAD instructions, which are used for multiply-add operations and are crucial for general computing applications. Finally, the PCIe bus was nobbled to run only as a Gen 1 interface with a single lane. They reduced the lane count by removing the coupling capacitors on the PCB, which meant they could just be added later, but it’s still only a slow interface.

[niconconi] went into great detail benchmarking the instruction types, keeping their EM simulation application in mind. After a few tweaks to make it work, they determined it was a good purchase. This article is worth reading for all those hardcore GPU nerds!

If you need a primer on GPU mining, we’ve got you covered. Once you’ve understood proof-of-work crypto, perhaps take a look at Chia?

Thanks to [gnif] for the tip!

For racing games, flight simulators, and a few other simulation-style games, a simple controller just won’t do. You want something that looks and feels closer to the real thing. The major downsides to these more elaborate input methods is that they take up a large amount of space, requiring extra time for setup, and can be quite expensive as well. To solve both of these problems [Rahel zahir Ali] created a miniature steering wheel controller for some of his favorite games.

While there are some commercial offerings of small steering wheels integrated into an otherwise standard video game controller and a few 3D printed homebrew options, nothing really felt like a true substitute. The main design goal with this controller was to maintain the 900-degree rotation of a standard car steering wheel in a smaller size. It uses a 600P/R rotary encoder attached to a knob inside of a printed case, with two spring-loaded levers to act as a throttle and brake, as well as a standard joystick to adjust camera angle and four additional buttons. Everything is wired together with an Arduino Leonardo that sends the inputs along to the computer.

Now he’s ready to play some of his favorite games and includes some gameplay footage using this controller in the video linked below. If you’re racing vehicles other than cars and trucks, though, you might want a different type of controller for your games instead.

You’ve probably heard that a 3D printer is capable of producing its own replacement parts. Sometimes, that even includes upgraded or improved versions of the parts it was originally built with. But sometimes, it’s hard to figure out what improved really means. Think about air ducts that cool the part after printing. In theory, it should be easy to design a new duct. But how does it perform? Empirical testing can be difficult, but [Mike] shows how you can simulate the airflow so you can test design changes and validate assumptions before you print the actual part.

Of course, this wouldn’t only apply to printer ducts. You might also get some tips if you want to model airflow for PC cooling, hot air soldering, or other air-related projects. The free version of the software has some limitations, but it was surprisingly capable.

We also enjoyed how [Mike] used fluid to visualize the actual patterns and compared it to the simulation. The trick is using a compound from a kid’s science project kit, and it seems to work very well. Of course, you could just grab your smartphone. This might be worth thinking about if you are building a laser cutter air assist, too.