In particular, Linux detected the card and correctly mapped the BARs (Base Address Register), which had been a problem in the past for him with other devices. Plugging in the card yielded promising results initially. To avoid problems with differing ground planes, an adapter was fashioned for the Raspberry Pi to be powered from the PSU as well. Unfortunately, the PCI-e slot on the IO board wasn’t designed with a power-hungry chip in mind, so brought in a full-blown ATX power supply to power the GPU. In a situation similar to putting a V8 on a lawnmower, the Raspberry Pi 4 pulls around 5-10 watts and the GPU can pull 230 watts. While you likely wouldn’t be running games with such as setup, there are many kinds of unique and interesting compute-based workloads that can be offloaded onto a GPU. With some luck, he was able to obtain an AMD Radeon RX 6700 XT GPU card and decided to try and plug it into the Raspberry Pi 4 Compute Module. routinely tinkers around with Raspberry Pi compute module, which unlike the regular RPi 4, includes a PCI-e lane. Posted in Raspberry Pi Tagged cern, computer model, COVID, pandemic, self-hosted, transmission, virus For other ways of using your own computing power to help fight Covid, don’t forget about for using up all those extra CPU and GPU cycles.

One of the goals of this project is that it is freely available and runs on relatively inexpensive hardware, so hopefully plenty of people around the world are able to easily run it to further develop understanding of how the virus spreads. Of course, this only generates statistical likelihoods of virus transmission but it does help get a more accurate understanding of specific situations.įor more information on how all of this works, the group at CERN also released a paper about their model. It can run on a number of different Pi hardware although recommends using the Pi 4 as the model does take up a significant amount of computer resources. The program, called the Covid-19 Airborne Risk Assessment (CARA), is able to take in a number of metrics about the size and shape of an area, the number of countermeasures already in place, and plenty of other information in order to provide a computer-generated model of the number of virus particles predicted as a function of time.

By now we all know of ways to do that physically, but now thanks to and a team at CERN we can also model virus exposure directly on our own self-hosted Raspberry Pis. But even if you aren’t working on a new vaccine or trying to curb the virus with some other seemingly miraculous technology, there are a few other ways to help prevent the spread of the virus. Despite the best efforts of scientists around the world, the current global pandemic continues onward.

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