High-Performance Physics Engine

Overview

This physics engine is a research project aimed at leveraging high-performance computing (HPC) to simulate complex physical systems. It is designed to test and apply mathematical derivations in matrix form while utilizing modern hardware acceleration, including CUDA for GPU offloading and Fortran for optimizing critical tight-loop calculations. The engine is primarily intended for researchers and enthusiasts interested in high-performance simulation and physics engines.

The main goals of this project are:

• Learning: Gain hands-on experience with CUDA, C++, Fortran, and advanced physics simulations.
• Research: Implement custom mathematical derivations and algorithms, converting them into matrix operations suitable for GPU parallelism.
• Optimization: Leverage both CPU and GPU for optimal performance in physics calculations.

Key Technologies

• C/C++: The main programming language, serving as the backbone of the engine. C++ is used for the core physics simulation logic and management.
• CUDA: Used for offloading heavy computational tasks, such as matrix operations, collision detection, and force calculations, to the GPU. CUDA accelerates large-scale parallel processing for high-performance simulations.
• Fortran: Used for performance-critical, small-scale numerical calculations that don’t require GPU parallelization. This allows for fast array manipulations and tight-loop optimizations.

The goal is to have the most computationally expensive tasks (such as matrix operations and large-scale simulations) run on the GPU, while Fortran is utilized for smaller, intensive calculations on the CPU.

Features

• GPU-Accelerated Physics: Harness the power of modern GPUs to parallelize large physics simulations.
• Custom Derivations: Implement and test your own mathematical models and simulations.
• Optimized Calculations: Use Fortran for efficient array handling and tight-loop operations.
• CMake Build System: The project uses CMake for cross-platform building and configuration.

Setup

Prerequisites

• CUDA Toolkit: Ensure that you have a compatible NVIDIA GPU and the CUDA toolkit installed for GPU acceleration. Follow the installation guide on the NVIDIA CUDA website.
• Fortran Compiler: A Fortran compiler (e.g., GNU Fortran or Intel Fortran) is required for compiling the Fortran parts of the code.
• CMake: The build system for the project. You can download and install CMake from here.
• CuBLAS (Optional): For optimized matrix operations, you can use NVIDIA's CuBLAS library. This is optional but recommended for high-performance computations.

Installing the Project

1. Clone the repository:

   git clone https://github.com/StevenKight/Physics-Engine.git
   cd Physics-Engine
   

2. Create a build directory:

   mkdir build
   cd build
   

3. Run CMake to configure the project:

   cmake ..
   

4. Build the project:

   make
   

Using the Engine

Detailed usage instructions and examples will be provided in the Wiki section of this repository as the project progresses.

Wiki

Note: The Wiki is currently under construction. As the project evolves, more detailed documentation will be added.

The Wiki will include:

The Wiki contains detailed notes and derivations for the mathematical models used in the engine. Here, you will find:

• Full derivations of the equations for forces, motion, and collisions.
• Descriptions of how these equations are converted into matrix operations for GPU computation.
• In-depth explanations of how CUDA and Fortran are leveraged for performance optimization.

Performance Considerations

This engine is optimized for high-performance computing. The majority of computationally intensive tasks (such as matrix operations, collision detection, and force calculations) are offloaded to the GPU using CUDA. For smaller-scale, non-parallelizable tasks, Fortran is used to ensure tight-loop optimizations without the overhead of parallelization.

Performance Tuning

• The use of CuBLAS for matrix operations can be enabled for even faster computations on compatible NVIDIA GPUs.
• Keep an eye on the GPU usage with tools like nvidia-smi to monitor and optimize resource consumption during simulations.

Future Work

This engine is under active development. Future goals include:

• Integration with rendering pipelines (custom or via Blender/Unity plugins).
• Development of a plugin or shared library interface for use in other applications.
• Implementation of advanced constraint systems and soft-body dynamics.
• Support for mixed-precision arithmetic to optimize GPU throughput.
• Further optimization of Fortran routines for CPU-bound tasks.
• Comprehensive testing and benchmarking against existing physics engines.
• Documentation of the engine's architecture and design patterns.

License

This project is licensed under the GNU General Public License v3.0 (GPL-3.0).

You are free to use, modify, and distribute this software under the terms of the GPL v3. This means that any derivative works or redistributions must also be licensed under the GPL v3, ensuring the same freedoms to all users.

The full license text can be found in the LICENSE file.

Contributions

While contributions are not yet officially open, feel free to explore the repository, open issues, or submit suggestions for future improvements. If you’re interested in contributing, please reach out to discuss potential areas of collaboration.