DCGAN inference on a microcontroller: 12.6M parameters, 512KB SRAM, 26-second generation, pure C [P]

Just thought I'd share, I ran a DCGAN on a dual core RISC-V microcontroller, the CH32H417 generating 64x64 cat faces. This is a new RISC-V MCU, so no TFLite, no CMSIS NN and no external memory. It's a pure C inference engine, bit-identical to PyTorch reference outputs. The model is 12.6M parameters with int8 per channel quantization. Intermediate activations are d in DTCM and layer weights stream from SD card using double buffering so the next layer loads while the current one computes.