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name: gsplat-optimizer description: Optimize 3D Gaussian Splat scenes for real-time rendering on iOS, macOS, and visionOS. Use when working with .ply or .splat files, targeting mobile/Apple GPU performance, or needing LOD, pruning, or compression strategies for 3DGS scenes.

Gaussian Splat Optimizer

Optimize 3D Gaussian Splatting scenes for real-time rendering on Apple platforms (iOS, macOS, visionOS) using Metal.

When to Use

• Optimizing .ply or .splat files for mobile/Apple GPU targets
• Reducing gaussian count for performance (pruning strategies)
• Implementing Level-of-Detail (LOD) for large scenes
• Compressing splat data for bandwidth/storage constraints
• Profiling and optimizing Metal rendering performance
• Targeting specific FPS goals on Apple hardware

Quick Start

Input: Provide a .ply/.splat file path, target device class, and FPS target.

Copy# Analyze a splat file
python ~/.claude/skills/gsplat-optimizer/scripts/analyze_splat.py scene.ply --device iphone --fps 60

Output: The skill provides:

1. Point/gaussian pruning plan (opacity, size, error thresholds)
2. LOD scheme suggestion (distance bins, gaussian subsets)
3. Compression recommendation (if bandwidth/storage bound)
4. Metal profiling checklist with shader/compute tips

Optimization Workflow

Step 1: Analyze the Scene

First, understand your scene characteristics:

• Gaussian count: Total number of splats
• Opacity distribution: Histogram of opacity values
• Size distribution: Gaussian scale statistics
• Memory footprint: Estimated GPU memory usage

Step 2: Determine Target Device

Step 3: Apply Pruning

If gaussian count exceeds device budget:

1. Opacity threshold: Remove gaussians with opacity < 0.01-0.05
2. Size culling: Remove sub-pixel gaussians (< 1px at target resolution)
3. Importance pruning: Use LODGE algorithm for error-proxy selection
4. Foveated rendering: For Vision Pro, reduce density in peripheral view

See references/pruning-strategies.md for details.

Step 4: Implement LOD (Large Scenes)

For scenes exceeding single-frame budget:

1. Distance bins: Near (0-10m), Mid (10-50m), Far (50m+)
2. Hierarchical structure: Octree or LoD tree for spatial queries
3. Chunk streaming: Load/unload based on camera position
4. Smooth transitions: Opacity blending at chunk boundaries

See references/lod-schemes.md for details.

Step 5: Apply Compression (If Needed)

For bandwidth/storage constraints:

See references/compression.md for details.

Step 6: Profile and Optimize Metal

1. Choose storage mode: Private for static data, Shared for dynamic
2. Optimize shaders: Function constants, thread occupancy
3. Profile with Xcode: GPU Frame Capture, Metal System Trace
4. Iterate: Measure, optimize, repeat

See references/metal-profiling.md for details.

Key Metrics

Reference Implementation

MetalSplatter is the primary reference for Swift/Metal gaussian splatting:

• Repository: https://github.com/scier/MetalSplatter
• Supports iOS, macOS, visionOS
• ~8M splat capacity with v1.1 optimizations
• Stereo rendering for Vision Pro

Getting Started with MetalSplatter

Copygit clone https://github.com/scier/MetalSplatter.git
cd MetalSplatter
open SampleApp/MetalSplatter_SampleApp.xcodeproj
# Set to Release scheme for best performance

Resources

Reference Documentation

• Pruning Strategies - Gaussian reduction techniques
• LOD Schemes - Level-of-detail approaches
• Compression - Bandwidth/storage optimization
• Metal Profiling - Apple GPU optimization

Research Papers

• LODGE - LOD for large-scale scenes
• FLoD - Flexible LOD for variable hardware
• Voyager - City-scale mobile rendering
• 3DGS Compression Survey

Apple Developer Resources

• Metal Best Practices Guide
• Metal Shader Performance (Tech Talk)
• Optimize GPU Renderers (WWDC23)