Particle Engine
Developed a GPU-accelerated particle simulation visualizing emergent behaviors and ecosystem dynamics among thousands of species.
Context
Inspired by the work of Digital Genius' "Simulating Particle Life", I wanted to build a particle simulation that could visualize emergent life-patterns. However, traditional CPU-based simulations struggled to render and compute complex interactions among thousands of species in real time, limiting exploration of emergent patterns in artificial ecosystems.
The Problem
High computational cost and low frame rates hindered real-time visualization of large-scale particle interactions, making it difficult to simulate emergent life-like behaviors for large amounts of particles.
Approach
Leveraged OpenGL and compute shaders in C++ to implement a massively parallel particle simulation. Designed custom attraction/repulsion rules for species interactions and optimized rendering for interactive performance.
Architecture
Core simulation written in C++ using OpenGL 4.3+ and GLSL compute shaders for parallel computation. GLFW and GLAD used for window/context and OpenGL management. CMake for cross-platform builds.
Results
Achieved real-time visualization of 100,000+ interacting particles
Demonstrated emergence of stable and dynamic patterns resembling biological ecosystems
Reduced per-frame computation time by >80% compared to CPU implementations
Enabled interactive exploration and parameter tuning for emergent behaviors
What I Learned
Gained expertise in GPU programming, parallel computation, and real-time visualization. Learned the challenges of designing scalable interaction rules and optimizing data transfer between CPU and GPU.
Impact Summary
Simulated emergent life-patterns using GPU; visualized thousands of interacting species in real-time.