Fast-Gaussian-Rasterization

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fast-gaussian-rasterization is a high-performance 3D Gaussian Splatting rasterizer that uses geometry shaders and global CUDA sorting. It can achieve a 5-10x speedup in rendering compared to vanilla implementations.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is fast-gaussian-rasterization?

fast-gaussian-rasterization is a cutting-edge 3D Gaussian Splatting rasterizer engineered for high-performance rendering. Leveraging a geometry-shader-based approach and global CUDA sorting, this tool significantly accelerates rendering, offering a 5-10x speedup over traditional software CUDA rasterizers. It's particularly effective for scenarios with a high pixel-to-point ratio, such as large Gaussians and high-resolution rendering. The tool is designed for seamless integration, allowing users to replace existing `diff_gaussian_rasterization` imports with `fast_gauss` for immediate performance gains. It supports NVIDIA GPUs with CUDA and OpenGL interop, making it suitable for both Linux and Windows environments.

Best used for

Ideal for developers and data scientists who need to significantly accelerate 3D Gaussian Splatting rendering, optimize graphics performance, and integrate high-speed rasterization into their projects. Especially valuable for applications requiring real-time or high-resolution 3D visualizations on NVIDIA GPUs.

Common actions

accelerate 3D rendering

optimize graphics pipelines

implement Gaussian Splatting

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Capabilities

Key features

Geometry-shader-based rasterization
Global CUDA sorting
5-10x rendering speedup
Drop-in replacement
NVIDIA GPU compatibility
Offline rendering support

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What kind of performance improvement can I expect with fast-gaussian-rasterization?

You can expect a 5-10x speedup in rendering compared to the vanilla `diff-gaussian-rasterization` for real-time applications. For offline rendering, it typically achieves a 2-3x speedup. The most significant gains are seen with high pixel-to-point ratios, such as large Gaussians and high-resolution outputs.

What are the system requirements for using fast-gaussian-rasterization?

This project requires an NVIDIA GPU that supports CUDA and OpenGL interoperability. It has been tested on Linux and Windows. WSL (Windows Subsystem for Linux) and macOS are not supported. For offline rendering, a valid EGL environment is also necessary.

Does fast-gaussian-rasterization support backward passes for training?

Currently, backward passes are not supported. The developers are exploring ways to implement this functionality in future updates. The tool is primarily focused on high-performance forward rendering for visualization and inference tasks at this time.

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