[Jeff Geerling] routinely tinkers around with Raspberry Pi compute module, which unlike the regular RPi 4, includes a PCI-e lane. 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.
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. 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. Unfortunately, the PCI-e slot on the IO board wasn’t designed with a power-hungry chip in mind, so [Jeff] brought in a full-blown ATX power supply to power the GPU. To avoid problems with differing ground planes, an adapter was fashioned for the Raspberry Pi to be powered from the PSU as well. Plugging in the card yielded promising results initially. 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. A BAR allows a PCI device to map its memory into the CPU’s memory space and keep track of the base address of that mapped memory range.
AMD kindly provides Linux drivers for the kernel. [Jeff] walks through cross-compiling the kernel and has a nice docker container that quickly reproduces the built environment. There was a bug that prevented compilation with AMD drivers included, so he wasn’t able to get a fully built kernel. Since the video, he has been slowly wading through the issue in a fascinating thread on GitHub. Everything from running out of memory space for the Pi to PSP memory training for the GPU itself has been encountered.
The ever-expanding capabilities of the plucky little compute module are a wonderful thing to us here at Hackaday, as we saw it get NVMe boot earlier this year. We’re looking forward to the progress [Jeff] makes with GPUs. Video after the break.
Continue reading “Raspberry Pi With Some Serious Graphical Muscle”
