Splats under Pressure: Exploring Performance-Energy Trade-offs in Real-Time 3D Gaussian Splatting under Constrained GPU Budgets

TL;DR

This paper explores the performance and energy trade-offs of real-time 3D Gaussian Splatting on constrained GPUs by emulating various GPU capabilities on a single high-end GPU, assessing its viability for edge devices.

Contribution

It introduces an emulation-based approach to simulate different GPU performance levels and analyzes power-performance relationships for 3D Gaussian Splatting in energy-constrained environments.

Findings

Emulation accurately approximates diverse GPU capabilities.

Power-performance curves reveal lower bounds for real-time 3DGS.

Energy efficiency varies significantly across GPU performance levels.

Abstract

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.