Splats under Pressure: Exploring Performance-Energy Trade-offs in Real-Time 3D Gaussian Splatting under Constrained GPU Budgets
We investigate the feasibility of real-time 3D Gaussian Splatting (3DGS) rasterisation on edge clients with varying Gaussian splat counts and GPU computational budgets. Instead of evaluating multiple physical devices, we adopt an emulation-based approach that approximates different GPU capability tiers on a single high-end GPU. By systematically under-clocking the GPU core frequency and applying power caps, we emulate a controlled range of floating-point performance levels that approximate different GPU capability tiers. At each point in this range, we measure frame rate, runtime behaviour, and power consumption across scenes of varying complexity, pipelines, and optimisations, enabling analysis of power-performance relationships such as FPS-power curves, energy per frame, and performance per watt. This method allows us to approximate the performance envelope of a diverse class of GPUs, from embedded and mobile-class devices to high-end consumer-grade systems. Our objective is to explore the practical lower bounds of client-side 3DGS rasterisation and assess its potential for deployment in energy-constrained environments, including standalone headsets and thin clients. Through this analysis, we provide early insights into the performance-energy trade-offs that govern the viability of edge-deployed 3DGS systems.
在具有不同高斯斑点数量和 GPU 计算资源限制的边缘客户端上，我们研究了实时 3D 高斯泼溅（3DGS）光栅化的可行性。我们没有评估多个物理设备，而是采用了一种基于仿真的方法，在单个高端 GPU 上近似不同的 GPU 性能等级。通过系统地降低 GPU 核心频率并应用功耗限制，我们模拟了受控范围内的浮点性能水平，该范围近似于不同的 GPU 性能等级。在该范围内的每个点上，我们针对不同复杂度的场景、管线和优化方案测量帧率、运行时行为和功耗，从而能够分析如 FPS-功率曲线、每帧能耗和每瓦性能等性能与功耗之间的关系。这种方法使我们能够近似从嵌入式和移动类设备到高端消费级系统的各类 GPU 的性能包络线。我们的目标是探索客户端 3DGS 光栅化的实际下限，并评估其在包括独立头显和瘦客户端在内的能源受限环境中的部署潜力。通过这项分析，我们针对边缘部署 3DGS 系统的可行性所涉及的性能-能耗权衡提供了早期见解。