FPGAs have gone from being a niche product for people with big budgets to something that every electronics experimenter ought to have in their toolbox. I am always surprised at how many people I meet who tell me they are interested in using FPGAs but they haven’t started. If you’ve been looking for an easy way to get started with FPGAs, Hackaday’s FPGA boot camp is for you. There’s even a Hackaday.io chat in the group specifically for FPGA talk for questions and general discussion!
While it is true FPGAs aren’t for everything, when you need them you really need them. Using FPGAs you can build logic circuits — not software simulations, but real circuits — and reap major performance benefits compared to a CPU. For digital signal processing, neural networks, or computer vision applications, being able to do everything essentially in parallel is a great benefit. Sometimes you just need the raw speed of a few logic gates compared to a CPU plodding methodically through code. We expect to see a lot more FPGA activity now that Arduino is in the game.
These boot camps gather together some of the material you seen spread over many articles here before, plus new material to flesh it out. It’s designed for you to work through more like a training class than just some text to read. There’s plenty of screenshots and even animations to help you see what you are supposed to be doing. You’ll be able to work with simulations to see how the circuits we talk about work, make changes, and see the results. We’ll focus on Verilog — at least for now — as it is close to C and easier for people who know C to pick up. Still not convinced? Let’s run though the gist of the boot camp series.
Continue reading “Learn FPGA Fast with Hackaday’s FPGA Boot Camp”
No one loves hacked keyboards more than Hackaday. We spend most of our workday pressing different combinations of the same 104 buttons. Investing time in that tool is time well spent. [Max] feels the same and wants some personality in his input device.
In the first of three videos, he steps us through the design and materials, starting with a layer to hold the keys. FR4 is the layer of fiberglass substrate used for most circuit boards. Protoboards with no copper are just bare FR4 with holes. Homemade CNC machines can glide through FR4, achieving clean lines, and the material comes in different mask colors so customizing an already custom piece is simple. We see a couple of useful online tools for making a homemade keyboard throughout the videos. The first is a keypad layout tool which allows you to start with popular configurations and tweak them to suit your weirdest desires. Missing finger? Forget one key column. Extra digit? Add a new key column. Huge hands? More spaces between the keys. [Max] copied the Iris keyboard design but named his Arke, after the fraternal sister to Iris which is fitting since his wrist rests are removable. Continue reading “A Custom Keyboard At Maximum Effort”
Sometimes, less is more. Sometimes, more is more. There is a type of person who believes that if enough photos of the same subject are taken, one of them will shine above the rest as a gleaming example of what is possible with a phone camera and a steady hand. Other people know how to frame a picture before hitting the shutter button. In some cases, the best method may be snapping a handful of photos to get one good one, not by chance, but by design.
[The Thought Emporium]’s video, also below the break, is about getting crisp pictures from a DSLR camera and a microscope using focus stacking, sometimes called image stacking. The premise is to take a series of photos that each have a different part of the subject in focus. In a microscope, this range will be microscopic but in a park, that could be several meters. When the images are combined, he uses Adobe products, the areas in focus are saved while the out-of-focus areas are discarded and the result is a single photo with an impossible depth of focus. We can’t help but remember those light-field cameras which didn’t rely on moving lenses to focus but took many photos, each at a different focal range.
[The Thought Emporium] has shown us his photography passion before, as well as his affinity for taking the cells out of plants and unusual cuts from the butcher and even taking a noble stab at beating lactose intolerance.
Continue reading “Impossibly Huge Depth of Focus in Microscope Photographs”
If you’ve made it through the last two posts on quantum computing (QC), then you’ve seen the Quirk simulator, a little of IBM’s web-based offering, and how entanglement and superposition can do strange and possibly wonderful things. However, the superdense encoding I showed you didn’t really feel like a real computer algorithm. This time we will look at Grover’s algorithm which is often incorrectly billed as an “unstructured database search.” In reality, it is an algorithm for making a state — that is a set of qubits — match some desired state without simply setting the state.
By analogy, consider a web service where you guess a number. Most discussions of Grover’s algorithm will tell you that the service will only tell you if the number is correct or not. If the number was from 1 to 16, using traditional computing, you’d have to query the values one at a time to see which is correct. You might get lucky and hit the first time. Or it might take 16 times. With qubits you can get the same result in only four attempts. In fact, if you try more times, you might get the wrong answer. Of course, what you really get is an answer that is probably correct, because that how QC works.
Continue reading “Quantum Searching in Your Browser”
Quantum computing (QC) is a big topic, and last time I was only able to walk you through the construction of a few logic gates, but you have to start somewhere. If you haven’t read that part, you probably should, because you’ll need to understand the simulator I’m using and some basic concepts.
I like to get right into practice, but with this topic, there’s no avoiding some theory. But don’t despair. We’ll have a little science fiction story you can try by the end of this installment, where we manage to pack two bits of information into a single physical qubit. Last time I mentioned that qubits have 1 and 0 states and I hinted that they were really |1> and |0> states. Why create new names for the two normal binary states? Turns out there is more to the story.
What’s the Vector, Victor?
In Dirac notation, |1> is a vector. So is |hackaday> and |123>. You can get into a lot of math with these, but I’m going to try to avoid most of that. This is also called ket notation (the last part of the word bracket) so you’ll hear people say “one ket” or “hackaday ket.” Either way, the vector can represent one or more qubits and there are several ways to represent them.
Continue reading “Quantum Communications in Your Browser”
I’ll be brutally honest. When I set out to write this post, I was going to talk about IBM’s Q Experience — the website where you can run real code on some older IBM quantum computing hardware. I am going to get to that — I promise — but that’s going to have to wait for another time. It turns out that quantum computing is mindbending and — to make matters worse — there are a lot of oversimplifications floating around that make it even harder to understand than it ought to be. Because the IBM system matches up with real hardware, it is has a lot more limitations than a simulator — think of programming a microcontroller with on debugging versus using a software emulator. You can zoom into any level of detail with the emulator but with the bare micro you can toggle a line, use a scope, and hope things don’t go too far wrong.
So before we get to the real quantum hardware, I am going to show you a simulator written by [Craig Gidney]. He wrote it and promptly got a job with Google, who took over the project. Sort of. Even if you don’t like working in a browser, [Craig’s] simulator is easy enough, you don’t need an account, and a bookmark will save your work.
It isn’t the only available simulator, but as [Craig] immodestly (but correctly) points out, his simulator is much better than IBM’s. Starting with the simulator avoids tripping on the hardware limitations. For example, IBM’s devices are not fully connected, like a CPU where only some registers can get to other registers. In addition, real devices have to deal with noise and the quantum states not lasting very long. If your algorithm is too slow, your program will collapse and invalidate your results. These aren’t issues on a simulator. You can find a list of other simulators, but I’m focusing on Quirk.
What Quantum Computing Is
As I mentioned, there is a lot of misinformation about quantum computing (QC) floating around. I think part of it revolves around the word computing. If you are old enough to remember analog computers, QC is much more like that. You build “circuits” to create results. There’s also a lot of difficult math — mostly linear algebra — that I’m going to try to avoid as much as possible. However, if you can dig into the math, it is worth your time to do so. However, just like you can design a resonant circuit without solving differential equations about inductors, I think you can do QC without some of the bigger math by just using results. We’ll see how well that holds up in practice.
Continue reading “Quantum Weirdness in Your Browser”
Hackaday likes the idea of fine-tuning existing hardware rather than buying new stuff. [fishpepper] wrote up a tutorial on rewinding brushless motors, using the Racerstar BR1103B as the example. The BR1103B comes in 8000 Kv and 10000 Kv sizes, but [fishpepper] wanted to rewind the stock motor and make 6500 Kv and 4500 Kv varieties — or as close to it as he could get.
Kv is the ratio of the motor’s RPM to the voltage that’s required to get it there. This naturally depends on the magnet coils that it uses. The tutorial goes into theory with the difference between Wye-terminated and Star-terminated winding schemes, and how to compute the number of winds to achieve what voltage — for his project he ended up going with 12 turns, yielding 6700 Kv and 17 turns for 4700 Kv. His tutorial assumes the same gauge wire as the Racerstar.
Just as important as the theory, however, the tutorial also covers the physical process of opening up the motor and unwinding the copper wire, cleaning the glue off the stator, and then rewinding to get the required stats.
[fishpepper]’s handle has graced Hackaday before: he created what he calls the world’s lightest brushless FPV quadcopter. In addition to motors and drones, he also rocks a mean fidget spinner.