A Dead Macbook GPU Shouldn’t Stop You, With This BGA Soldering Hack

On some 2011 Macbook Pro models, there is a tendency for the Radeon GPU to fail. This should mean game over for the computer, but surprisingly salvation is offered by its having not one but two GPUs on board. The Intel processor also has a GPU, and Apple use a pile of logic in an FPGA to switch at will between them. The community have produced fresh FPGA code to revive a dead Mac on its Intel GPU, but at the expense of losing brightness control. [Ayilm1] has brought back the brightness with a clever BGA reworking hack that gains access to a brightness control line present on the Intel BD82HM65 Platform Controller Hub chip but not used in the Macbook.

We’re used to impressive soldering work here at Hackaday, and we’ve seen our share of wiring direct to the balls on an upturned BGA chip. This is a similar idea but at another level, as a section of the top insulation on an in-place BGA is removed to expose the microvia above the ball carrying the required signal. A tiny wire is soldered to the exposed pad and taken to a piece of copper tape stuck down to provide mechanical strength, and a piece of enameled copper wire is run from that to the other side of the PCB where lies its destination. It comes with FPGA code to take advantage of it, but even for non-Macbook owners, it’s an extremely impressive piece of work. It’s not the first fine-soldering Macbook fix we’ve seen, either.

Thanks [lightpink784] for the tip.

Help Us Throw More Cycles At The Coronavirus Problem

The Hackaday community has answered the call and put their computers put to work folding proteins found in the coronavirus. Team_Hack-a-Day ranks #44 in the world so far this month, and I’ve seen us rank as high as #19 on 24-hour leaderboards.

Want to join the fight? Donate some of those computing cycles you’re not using to battling SARS‑CoV‑2. You’re probably not an epidemiologist or a vaccine researcher, but you can make their jobs easier by providing them with the data they need through the Folding@home Project.

As Dan Maloney explained in his excellent article on protein folding, understanding the incredibly complex folding behavior of the proteins in the virus will be key to finding treatments and possibly a vaccine. Folding@home connects countless computers via the internet and is now the largest supercomputer in the world, consisting of over 3.5 million CPUs and over half a million GPUs. The resulting data is freely available to researchers.

Let’s take a look at how easy it is to get up and running, how a GPU can supercharge a setup, and dip into the stats for Team_Hack-a-Day’s effort.

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GPU Turned Into Radio Transmitter To Defeat Air-Gapped PC

Another week, another exploit against an air-gapped computer. And this time, the attack is particularly clever and pernicious: turning a GPU into a radio transmitter.

The first part of [Mikhail Davidov] and [Baron Oldenburg]’s article is a review of some of the basics of exploring the RF emissions of computers using software-defined radio (SDR) dongles. Most readers can safely skip ahead a bit to section 9, which gets into the process they used to sniff for potentially compromising RF leaks from an air-gapped test computer. After finding a few weak signals in the gigahertz range and dismissing them as attack vectors due to their limited penetration potential, they settled in on the GPU card, a Radeon Pro WX3100, and specifically on the power management features of its ATI chipset.

With a GPU benchmarking program running, they switched the graphics card shader clock between its two lowest power settings, which produced a strong signal on the SDR waterfall at 428 MHz. They were able to receive this signal up to 50 feet (15 meters) away, perhaps to the annoyance of nearby hams as this is plunk in the middle of the 70-cm band. This is theoretically enough to exfiltrate data, but at a painfully low bitrate. So they improved the exploit by forcing the CPU driver to vary the shader clock frequency in one megahertz steps, allowing them to implement higher throughput encoding schemes. You can hear the change in signal caused by different graphics being displayed in the video below; one doesn’t need much imagination to see how malware could leverage this to exfiltrate pretty much anything on the computer.

It’s a fascinating hack, and hats off to [Davidov] and [Oldenburg] for revealing this weakness. We’ll have to throw this on the pile with all the other side-channel attacks [Samy Kamkar] covered in his 2019 Supercon talk.

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Java On GPUs And FPGAs

There was a time when running a program on an array of processors meant that you worked in some high-powered lab somewhere. Now your computer probably has plenty of processors hiding in its GPU and if you have an FPGA, you have everything you need to make something custom. The idea behind TornadoVM is to modify OpenJDK and GraalVM to support running some Java code on parallel architectures supported by OpenCL. The system can utilize multi-core CPUs, GPUs (NVIDIA and AMD), Intel integrated GPUs, and Intel FPGAs.

If you want to try your hand at accelerated Java, there are some docker containers to get you started fast. There’ are also quite a few examples, such as a computer vision application.

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Magnets Make This Panda Move

A single board computer on a desk is fine for quick demos but for taking it into the wild (or even the rest of the house) you’re going to want a little more safety from debris, ESD, and drops. As SBCs get more useful this becomes an increasingly relevant problem to solve, plus a slick enclosure can be the difference between a nice benchtop hack and something that looks ready to sell as a product. [Chris] (as ProjectSBC) has been working on a series of adaptable cases called the MagClick Case System for the LattePanda Alpha SBC which are definitely worth a look.

The LattePanda Alpha isn’t a run-of-the-mill SBC; it’s essentially the mainboard from a low power ultrabook and contains up to an Intel Core M series processor, 8GB RAM, and 64GB of eMMC. Not to mention an onboard Atmega32u4, WiFi, Gigabit Ethernet, and more. It has more than enough horsepower to be used as an everyday desktop computer or even a light gaming system if you break PCIe out of one the m.2 card slots. But [Chris] realized that such adaptability was becoming a pain as he had to move it from case-to-case as his use needs changed. Thus the MagClick Case System was born.

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Bike-Mounted Synthetic-Aperture Radar Makes Detailed Images

Synthetic-aperture radar, in which a moving radar is used to simulate a very large antenna and obtain high-resolution images, is typically not the stuff of hobbyists. Nobody told that to [Henrik Forstén], though, and so we’ve got this bicycle-mounted synthetic-aperture radar project to marvel over as a result.

Neither the electronics nor the math involved in making SAR work is trivial, so [Henrik]’s comprehensive write-up is invaluable to understanding what’s going on. First step: build a 6-GHz frequency modulated-continuous wave (FMCW) radar, a project that [Henrik] undertook some time back that really knocked our socks off. His FMCW set is good enough to resolve human-scale objects at about 100 meters.

Moving the radar and capturing data along a path are the next steps and are pretty simple, but figuring out what to do with the data is anything but. [Henrik] goes into great detail about the SAR algorithm he used, called Omega-K, a routine that makes use of the Fast Fourier Transform which he implemented for a GPU using Tensor Flow. We usually see that for neural net applications, but the code turned out remarkably detailed 2D scans of a parking lot he rode through with the bike-mounted radar. [Henrik] added an auto-focus routine as well, and you can clearly see each parked car, light pole, and distant building within range of the radar.

We find it pretty amazing what [Henrik] was able to accomplish with relatively low-budget equipment. Synthetic-aperture radar has a lot of applications, and we’d love to see this refined and developed further.

[via r/electronics]

Fake Graphics Cards And How To Fix Them

When shopping online, there’s plenty of great deals out there on modern graphics hardware. Of course, if you’re like [Dawid] and bought a GTX1050 Ti for $48 from Wish, you probably suspect it’s too good to be true. Of course, you’d be correct.

[Dawid] notes from the outset that the packaging the card ships in is unusual. While it’s covered in NVIDIA and GeForce branding, there’s no note of the model number or even the overarching series. The card is loosely packed in bubblewrap, free to bounce around in transit. Upon installation, the card reports itself as a GTX1050 Ti, but refuses to properly work with NVIDIA drivers and routinely causes a Blue Screen of Death.

Upon disassembly, it becomes apparent that the card is merely a poorly manufactured GTS450 Revision 2, over five generations older than the card it was advertised as. Thanks to the mismatch between the actual hardware and what the card reports as, the drivers are unable to properly work with the card.

For those that have been scammed, there is some hope. [Phil] has had experience with several of these cards, which similarly misreport their actual hardware. To correct this, the cards need to have their BIOS flashed to reflect reality, but the fake cards don’t work with NVIDIA’s NVFlash tool. Instead, they must be flashed manually using an EEPROM programmer. Once the cards are flashed with an appropriate BIOS, they can be used with the proper drivers and will function properly, albeit with much less performance than was advertised.

It’s an interesting insight into the state of online shopping platforms, and the old adage remains true – if it’s too good to be true, it probably is. Plus, hacking GPUs can often have great results. Video after the break.

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