Add high-performance 2D Boids simulation with WebGPU + Svelte 5, deploy via GitHub Pages

[Copilot]

Implements a 10,000+ agent Boids simulation targeting 60 FPS using WebGPU compute shaders (WGSL), with a Svelte 5 UI and automatic GitHub Pages deployment.

Simulation Engine

• 3-pass GPU pipeline: spatial grid binning (atomic) → boid logic → instanced triangle render
• Toroidal topology with Minimum Image Convention across all distance/velocity calculations
• Agent types: Boids (cohesion + alignment + separation + predator avoidance + goal seeking + obstacle avoidance) and Predators (flock-centre pursuit + obstacle avoidance)
• Obstacles as analytical shapes (circle/box) passed via uniform buffer; avoidance via SDF steering
• Goals as global attractors with configurable strength weight
• WebGL2 CPU-fallback (WebGLFallback.js) using a JS spatial hash + instanced rendering for browsers without WebGPU

UI (Svelte 5 runes)

• Toolbox: Add/Move Goal, Add/Move Obstacle (click-drag interaction)
• Sliders: separation, cohesion, alignment weights; perception radius; max speed; boid count (up to 20,000); predator count
• Toggles: Show Grid, Debug Vectors
• GPU/WebGL status badge + live FPS counter

Deployment

• .github/workflows/deploy.yml: builds on push to main, uploads dist/ via actions/upload-pages-artifact, deploys with actions/deploy-pages
• vite.config.js sets base: '/Boids/' to match the Pages subdirectory

One-time repo setup: Settings → Pages → Source → GitHub Actions

Original prompt

​Project Goal: Create a high-performance 2D Boids simulation in the browser using Vite, Svelte, and WebGPU (or highly optimized WebGL Compute). Target: 10,000+ agents at 60 FPS.
​1. Core Simulation Engine
​Topology: Toroidal (wrap-around) with Minimum Image Convention for distance and velocity calculations.
​Agent Types: * Boids (Prey): Standard Cohesion, Alignment, Separation + Predator Avoidance + Goal Seeking + Obstacle Avoidance.
​Predators: Pursuit behavior (target flock center) + Obstacle Avoidance.
​Obstacles & Goals: * Represent obstacles as Analytical Shapes (Circles/Boxes) passed as a Uniform Buffer to the GPU.
​Goals are global attractors with a "Strength" weight.
​2. Technical Stack & Optimization
​Framework: Svelte 5 (for UI/State) + Vite.
​Compute Strategy: Use WebGPU Compute Shaders (WGSL).
​Pass 1: Spatial Partitioning (Grid-based Binning) on the GPU to avoid O(n^2).
​Pass 2: Boid Logic (Update Velocity/Position).
​Pass 3: Render (Vertex/Fragment shaders using the Boid Buffer).
​Alternative (if WebGPU is unavailable): Use a Data Texture approach in WebGL where boid positions are stored in pixels.
​3. Features & UI (Svelte)
​Interaction Mode: A "Toolbox" to toggle between:
​Add/Move Goal: Click and drag to move a global attractor.
​Add/Move Obstacle: Click to spawn, drag to reposition.
​Simulation Controls: * Sliders for: Separation weight, Cohesion weight, Alignment weight, Perception Radius, and Max Speed.
​Toggle for "Show Grid" and "Debug Vectors."
​Count Slider: Dynamically spawn/despawn boids up to 20,000.
​4. Implementation Details
​Obstacle Avoidance: Use a "Steer-to-Avoid" raycasting logic or an Analytical SDF inside the shader for real-time avoidance of moving shapes.
​Toroidal Sensing: Ensure the spatial grid lookups use % (modulo) to check neighbor cells across the screen boundaries.

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[LowWeiLin]

@copilot This should be set up to deploy via GitHub actions/GitHub pages

[Copilot]

@copilot This should be set up to deploy via GitHub actions/GitHub pages

Already set up in commit ee29821:

• .github/workflows/deploy.yml — triggers on every push to main (plus manual workflow_dispatch), installs deps, runs npm run build, uploads dist/ with actions/upload-pages-artifact, then deploys via actions/deploy-pages.
• vite.config.js — sets base: '/Boids/' so all asset paths resolve correctly under the GitHub Pages subdirectory (https://lowweilin.github.io/Boids/).

One-time repo setup needed: Settings → Pages → Source → GitHub Actions.