Neo: Real-Time On-Device 3D Gaussian Splatting with Reuse-and-Update Sorting Acceleration

While 3D Gaussian Splatting (3DGS) has emerged as a promising technique for immersive AR/VR experiences, its practical adoption critically depends on whether real-time rendering can be achieved on resource-constrained devices, such as Meta Ray-Ban Display and Google Android XR Glasses. However, existing solutions struggle to achieve high frame rates, especially for high-resolution rendering. Our analysis identifies the sorting stage in the 3DGS rendering pipeline as the major bottleneck due to its high memory bandwidth demand. This paper presents Neo, which introduces a reuse-and-update sorting algorithm that exploits temporal redundancy in Gaussian ordering across consecutive frames and devises a hardware accelerator optimized for this algorithm. By efficiently tracking and updating Gaussian depth ordering instead of re-sorting from scratch, Neo significantly reduces redundant computations and memory bandwidth pressure. Experimental results show that Neo achieves up to 12.4x and 5.5x higher throughput than state-of-the-art edge GPU and ASIC solution, respectively, while reducing DRAM traffic by 94.6% and 81.4%. These improvements make high-quality and low-latency on-device 3D rendering more practical.