Trained an diffusion model that runs on 264KB of RAM [P]

I recently bought a Shrike lite which has got 264KB of SRAM. I decided to train an image generation model that generates 32*32 pixel images. The microcontroller also has an FPGA onboard which I used to create two parallel INT8 MAC engines with 16 bit accumulation to speed up calculations, however the system soon hit a memory wall due to the high number of I/O operations, this meant that the system with parallel MAC engines ran slower than the MCU only model (~220 seconds per image vs ~70 seconds per image). It was still a fun project that I enjoyed messing around with. A lot of the images looked weird and noisy because of the heavy quantization and memory limits but some of them came out cool. Full case study here . submitted by /u/PandaBean18 [link] [留言]