GPU-Accelerated Physical Simulation Framework

Parallel physics simulation platform for robotics and graphics applications

Project Overview:

This project addresses the challenge of performing physically accurate simulations of complex environments in real-time. By leveraging GPU acceleration through CUDA, the framework achieves significant performance improvements while maintaining simulation accuracy, enabling applications in robotics, computer graphics, and VR/AR.

Key Features:

  • Unified constraint-based physical simulation supporting rigid bodies, soft bodies, and fluids
  • Highly parallel implementation of collision detection and constraint solving
  • Spatial data structures optimized for GPU execution patterns
  • Stable numerical integration methods suitable for interactive applications
  • API compatibility with common robotics and graphics frameworks

Technical Implementation:

The core of the framework consists of a parallel constraint solver that processes thousands of constraints simultaneously on the GPU. For collision detection, a hierarchical spatial subdivision approach is used to efficiently cull non-colliding pairs of objects. Both broad-phase and narrow-phase collision detection are implemented as parallel algorithms.

The framework uses a position-based dynamics approach for soft body simulation, allowing for stable and efficient simulation of deformable objects. Fluid simulation is implemented using a smooth particle hydrodynamics (SPH) method, with neighbor finding accelerated through GPU-optimized spatial hashing.

Performance Results:

  • 50-100x speedup over equivalent CPU implementations for rigid body simulation
  • Real-time performance with up to 100,000 rigid bodies or 1 million particles
  • Stable simulation at large time steps, suitable for interactive applications
  • Efficient scaling across different NVIDIA GPU architectures

Applications:

The framework has been successfully applied to robotic simulation for reinforcement learning, real-time physics for game engines, and interactive visualization for scientific applications. Its performance characteristics make it particularly suitable for applications requiring both accuracy and interactivity, such as virtual prototyping and realistic VR environments.