A single GPU card can cost thousands, but one YouTuber built his own for a fraction of the price, using 8,192 RISC-V microcontrollers.
bitluni, real name Matthias Balwierz, constructed a DIY GPU using CH570 RISC-V microcontrollers sourced from AliExpress. The cluster delivers a QVGA resolution of 320x200, with each MCU responsible for a single pixel. Despite the project nearly driving him "mad," bitluni pushed through, refining the PCB design and scaling the build to 8,192 chips.
The project began as an experiment in parallel computing but evolved into much more, and, at some cost, bitluni noted that prior GPU builds had already strained his sanity. This iteration, while visually modest, demonstrates the potential of microcontroller clusters for tasks beyond basic graphics.

bitluni found his cluster outperformed his 8-core PC CPU in hashing tests, drawing just 4 watts, a glimpse of untapped efficiency. For those who don't know, hashing was once the reason why GPU prices skyrocketed as GPUs were found to be extremely proficient at hashing during the cryptocurrency mining boom.
Though impractical for mainstream use, the build sparks interest in RISC-V for distributed computing, and the possibilities when you're willing to lose a little sanity in an attempt to manifest that idea burrowing away in your brain. bitluni has already hinted at a next-gen version with 32,000 chips, and that will undoubtedly be an interesting build, but at what cost will it be to bitluni?


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Which hashing algorithm did the MCU cluster outperform the 8-core PC CPU on, and what were the comparative hash rates?
How is video output generated and synchronized at 320x200 resolution from individual single-pixel MCUs?
What limitations or bottlenecks did bitluni encounter that make this approach impractical for mainstream GPU tasks?
What differences did bitluni mention (or show) between this build and his proposed 32,000-chip next-gen design regarding layout or expected challenges?
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Hopefully not too much, as this is an extremely interesting series and worth a watch if you are into GPUs or hardware in general.






