研究边缘设备上3D高斯点绘的能效平衡，探索实时渲染的可行边界。
Splats under Pressure: Exploring Performance-Energy Trade-offs in Real-Time 3D Gaussian Splatting under Constrained GPU Budgets
- 用降频与功耗限制模拟不同显卡性能，测试真实场景下的表现
- 发现帧率、能耗与渲染复杂度呈可预测的能效关系曲线
- 为头戴设备和瘦客户端部署3D高斯点绘提供关键优化参考
我们研究在不同高斯点数量和GPU计算预算下，边缘客户端实现实时3D高斯点绘光栅化的可行性。不依赖多台物理设备，而是通过在单块高端显卡上降频和施加功耗限制，模拟多种显卡性能层级。系统性地测量各性能层级下的帧率、运行时行为与功耗，覆盖不同复杂度场景、渲染管线及优化策略，分析帧率-功耗曲线、每帧能耗和每瓦性能等能效关系。该方法可逼近从嵌入式到消费级高端显卡的广泛性能范围。目标是探索客户端3DGS光栅化的实际性能下限，并评估其在能源受限环境（如独立头戴设备、瘦客户端）中的部署潜力。研究提供了边缘部署3DGS系统能效权衡的早期洞见。
原文摘要 · Abstract (English)
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.
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