DCIM-3DRec: A 3D Reconstruction Accelerator with Digital Computing-in-Memory and Octree-Based Scheduler

Learning-based 3D reconstruction has evolved rapidly with promising quality, while it requires high-performance hardware for interactive applications. In this work, a reconstruction accelerator called DCIM-3DRec is presented which leverages digital computing-in-memory (DCIM) design to facilitate learning-based reconstruction deployment on realtime and low-power edge platforms. The DCIM-3DRec is designed with the following features: a reconfigurable DCIM macro array for high data reuse and macro utilization, and an Octree-based subdivision scheduler for efficient management of 3D space prediction. The DCIM-3DRec accelerator is implemented and evaluated in TSMC 55 nm technology, with a DCIM macro efficiency of 19.4 TOPS/W at INT8. Overall, the DCIM-3DRec accelerator achieves 23× performance gain and four orders of magnitude energy efficiency improvement compared to a Nvidia RTX3090 GPU.