The Raspberry Pi has a port for a camera connector, allowing it to capture 1080p video and stream it to a network without having to deal with the craziness of webcams and the improbability of capturing 1080p video over USB. The Raspberry Pi compute module is a little more advanced; it breaks out two camera connectors, theoretically giving the Raspberry Pi stereo vision and depth mapping. [David Barker] put a compute module and two cameras together making this build a reality.
The use of stereo vision for computer vision and robotics research has been around much longer than other methods of depth mapping like a repurposed Kinect, but so far the hardware to do this has been a little hard to come by. You need two cameras, obviously, but the software techniques are well understood in the relevant literature.
[David] connected two cameras to a Pi compute module and implemented three different versions of the software techniques: one in Python and NumPy, running on an 3GHz x86 box, a version in C, running on x86 and the Pi’s ARM core, and another in assembler for the VideoCore on the Pi. Assembly is the way to go here – on the x86 platform, Python could do the parallax computations in 63 seconds, and C could manage it in 56 milliseconds. On the Pi, C took 1 second, and the VideoCore took 90 milliseconds. This translates to a frame rate of about 12FPS on the Pi, more than enough for some very, very interesting robotics work.
There are some better pictures of what this setup can do over on the Raspi blog. We couldn’t find a link to the software that made this possible, so if anyone has a link, drop it in the comments.
Nearly a year ago, an extremely interesting project hit Kickstarter: an open source GPU, written for an FPGA. For reasons that are obvious in retrospect, the GPL-GPU Kickstarter was not funded, but that doesn’t mean these developers don’t believe in what they’re doing. The first version of this open source graphics processor has now been released, giving anyone with an interest a look at what a late-90s era GPU looks like on the inside, If you’re cool enough, there’s also enough supporting documentation to build your own.
A quick note for the PC Master Race: this thing might run Quake eventually. It’s not a powerhouse. That said, [Bunnie] had a hard time finding an open source GPU for the Novena laptop, and the drivers for the VideoCore IV in the Raspi have only recently been open sourced. A completely open GPU simply doesn’t exist, and short of a few very, very limited thesis projects there hasn’t been anything like this before.
Right now, the GPL-GPU has 3D graphics acceleration working with VGA on a PCI bus. The plan is to update this late-90s setup to interfaces that make a little more sense, and add DVI and HDMI output. Not bad for a failed Kickstarter, right?
Hold on to your hats, because this is a good one. It’s a tale of disregarding the laws of physics, cancelled crowdfunding campaigns, and a menagerie of blogs who take press releases at face value.
Meet Silent Power (Google translation). It’s a remarkably small and fairly powerful miniature gaming computer being put together by a team in Germany. The specs are pretty good for a completely custom computer: an i7 4785T, GTX 760, 8GB of RAM and a 500GB SSD. Not a terrible machine for something that will eventually sell for about $930 USD, but what really puts this project in the limelight is the innovative cooling system and small size. The entire machine is only 16x10x7 cm, accented with a very interesting “copper foam” heat sink on top. Sounds pretty cool, huh? It does, until you start to think about the implementation a bit. Then it’s a descent into madness and a dark pit of despair.
There are a lot of things that are completely wrong with this project, and in true Hackaday fashion, we’re going to tear this one apart, figuring out why this project will never exist.
Continue reading “Behold! The Most Insane Crowdfunding Campaign Ever”
The Raspberry Pi has been around for two years now, and still there’s little the hardware hacker can actually do with the integrated GPU. That just changed, as the Raspberry Pi foundation just announced a library for Fourier transforms using the GPU.
For those of you who haven’t yet taken your DSP course, fourier transforms take a function (or audio signal, radio signal, or what have you) and output the fundamental frequency. It’s damn useful for everything from software defined radios to guitar pedals, and the new GPU_FFT library is about ten times faster at this task than the Raspi’s CPU.
You can get a copy of the GPU_FFT library by running rpi-update on your pi. If you happen to build anything interesting – something with a software defined radio or even a guitar pedal – you’re more than welcome to send it in to the Hackaday tips line. We’d love to see what you’re up to.
Unless you’re bit-banging a CRT interface or using a bunch of resistors to connect a VGA monitor to your project, odds are you’re using proprietary hardware as a graphics engine. The GPU on the Raspberry Pi is locked up under an NDA, and the dream of an open source graphics processor has yet to be realized. [Frank Bruno] at Silicon Spectrum thinks he has the solution to that: a completely open source GPU implemented on an FPGA.
Right now, [Frank] has a very lightweight 2D and 3D engine well-suited for everything from servers to embedded devices. If their Kickstarter meets its goal, they’ll release their project to the world, giving every developer and hardware hacker out there a complete, fully functional, open source GPU.
Given the difficulties [Bunnie] had finding a GPU that doesn’t require an NDA to develop for, we’re thinking this is an awesome project that gets away from the closed-source binary blobs found on the Raspberry Pi and other ARM dev boards.
When Intel and Apple released Thunderbolt, hallelujahs from the Apple choir were heard. Since very little in any of Apple’s hardware lineup is upgradeable, an external video card is the best of all possible world. Unfortunately, Intel doesn’t seem to be taking kindly to the idea of external GPUs. That hasn’t stopped a few creative people like [Larry Gadea] from figuring it out on their own. Right now he’s running a GTX 570 through the Thunderbolt port of his MacBook Air, and displaying everything on the internal LCD. A dream come true.
[Larry] is doing this with a few fairly specialized bits of hardware. The first is a Thunderbolt to ExpressCard/34 adapter, after that an ExpressCard to PCI-E adapter. Couple that with a power supply, GPU, and a whole lot of software configuration, and [Larry] had a real Thunderbolt GPU on his hands.
There are, of course, a few downsides to running a GPU through a Thunderbolt port. The current Thunderbolt spec is equivalent to a PCI-E 4X slot, a quarter of what is needed to get all the horsepower out of high-end GPUs. That being said, it is an elegant-yet-kludgy way for better graphics performance on the MBA,
Demo video below.
Continue reading “A Macbook Air and a Thunderbolt GPU”
The latest update in the Veronica 6502 computer project is this finalized VGA board which now has a home in the machine’s backplane.
We’ve been glued to the updates [Quinn Dunki] has been posting about the project for many months now. Getting the GPU working proved to take quite a bit of time, but we learned a ton just by following along. The video output had humble beginnings way back in March. That breadboarded circuit got complicated very quickly and that was before it was even interfaced with the CPU. As you can see from the image above, etching and populating the GPU board really cleans up the build. We’re sure it’s robust enough to move around at this point. We wonder if she’s planning on showing it off at a Maker Faire or another geeky gathering?
It really has become clear how wise [Quinn] was to design a backplane board early on. It plays right into the modular concept. She was even smart enough to include that SIL pin header on the near side of the board which was used heavily while prototyping this video module.