GRAIJun 9, 2025

STREAMINGGS: Voxel-Based Streaming 3D Gaussian Splatting with Memory Optimization and Architectural Support

arXiv:2506.09070v12 citationsh-index: 8DAC
Originality Incremental advance
AI Analysis

This addresses the performance bottleneck for real-time 3D rendering on resource-constrained mobile devices, representing a strong domain-specific improvement.

The paper tackled the problem of 3D Gaussian Splatting (3DGS) failing to achieve real-time 90 FPS on mobile devices, achieving only 2-9 FPS, by introducing STREAMINGGS, a co-design that achieved up to 45.7x speedup and 62.9x energy savings over mobile GPUs.

3D Gaussian Splatting (3DGS) has gained popularity for its efficiency and sparse Gaussian-based representation. However, 3DGS struggles to meet the real-time requirement of 90 frames per second (FPS) on resource-constrained mobile devices, achieving only 2 to 9 FPS.Existing accelerators focus on compute efficiency but overlook memory efficiency, leading to redundant DRAM traffic. We introduce STREAMINGGS, a fully streaming 3DGS algorithm-architecture co-design that achieves fine-grained pipelining and reduces DRAM traffic by transforming from a tile-centric rendering to a memory-centric rendering. Results show that our design achieves up to 45.7 $\times$ speedup and 62.9 $\times$ energy savings over mobile Ampere GPUs.

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