EdgeDAE: Acceleration of Diffusion Action Experts for Real-Time Physical AI with Tiny VLAs on Edge FPGA-GPU Systems
A heterogeneous FPGA-GPU system that strategically partitions workloads based on computational characteristics, offload the perception-heavy vision-transformer to GPU while accelerating DAE inference on FPGA through complete on-chip parameter storage in BRAM/URAM.