STREAMINGGS: Voxel-Based Streaming 3D Gaussian Splatting with Memory Optimization and Architectural Support
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 × speedup and 62.9 × energy savings over mobile Ampere GPUs.
Authors
- Wenchao Ding
- Minyi Guo (ORCID: https://orcid.org/0000-0003-0034-2302)
- Jieru Zhao (ORCID: https://orcid.org/0000-0001-8211-2812)
- Guangda Liu (ORCID: https://orcid.org/0000-0001-8905-7641)
- Chenqi Zhang (ORCID: https://orcid.org/0000-0002-2054-6196)
- Yu Feng (ORCID: https://orcid.org/0000-0002-2192-5737)
- Chentao Wu (ORCID: https://orcid.org/0000-0002-6882-3754)
Institutions
- Shanghai Jiao Tong University (CN)
- Fudan University (CN)
Publication Details
- Published
- 2025-06-22
- DOI
- https://doi.org/10.1109/dac63849.2025.11132470
- Citations
- 2
- Primary Topic
- Computer Graphics and Visualization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 7.08