https://github.com/vietnoirien/sand_cmulation
A high-performance particle simulation system with advanced spatial partitioning in C++.
https://github.com/vietnoirien/sand_cmulation
2d-arrays cpp17 openmp simulation-engine
Last synced: 4 days ago
JSON representation
A high-performance particle simulation system with advanced spatial partitioning in C++.
- Host: GitHub
- URL: https://github.com/vietnoirien/sand_cmulation
- Owner: Vietnoirien
- Created: 2025-04-18T10:13:16.000Z (9 days ago)
- Default Branch: main
- Last Pushed: 2025-04-20T09:34:03.000Z (7 days ago)
- Last Synced: 2025-04-20T10:22:25.519Z (7 days ago)
- Topics: 2d-arrays, cpp17, openmp, simulation-engine
- Language: C++
- Homepage:
- Size: 855 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Sand_Cmulation
A high-performance particle simulation system with advanced spatial partitioning in C++.
## Overview
Sand_Cmulation is a CS50X final project that implements a particle-based sand simulation with efficient spatial queries and grid operations. The system uses a combination of grid-based storage and spatial hashing to achieve high-performance particle operations.
## Features
- High-performance spatial partitioning with O(1) lookups
- Thread-safe operations with OpenMP parallelization
- Advanced spatial queries (radius, box, k-nearest neighbors)
- Memory-efficient particle storage
- Real-time memory usage monitoring
- Optimized batch operations
## Current Status
The project is currently in development. The grid system is visually functional, demonstrating the basic particle simulation capabilities.
## Grid System
The core of the simulation is the `GridSpatialConnector` which provides a unified interface between the grid storage and spatial hash systems:
### Key Components
- **Grid**: Stores particles in a 2D array
- **SpatialHash**: Provides O(1) spatial lookups
- **QuerySystem**: Handles advanced spatial queries
- **GridOperations**: Manages grid-level operations
### Performance Metrics
The following metrics were measured on an i9 9900KF processor with DDR4 @ 3200MHz:
- Insertion: ~613k particles/second
- Queries: ~49k queries/second
- Batch sync: ~2.4M updates/second
- Movement: ~79k moves/second
## Usage Examples
```cpp
// Initialize systems
Grid grid(1000, 1000);
SpatialHash spatialHash;
GridSpatialConnector connector(grid, spatialHash);
// Basic particle operations
Particle sand;
connector.addParticle(x, y, sand);
connector.moveParticle(oldX, oldY, newX, newY);
// Get neighboring cells
auto neighbors = connector.getNeighbors(x, y);
// Advanced spatial queries
Vector2D pos(x, y);
float radius = 5.0f;
auto nearbyParticles = connector.queryRadius(pos, radius);
// Box query
Vector2D min(x1, y1), max(x2, y2);
auto particlesInBox = connector.queryBox(min, max);
// K-nearest neighbors
auto nearestParticles = connector.queryKNearest(pos, 10);
```
## API Categories
### Particle Operations
- `addParticle()`: Add new particle
- `removeParticle()`: Remove particle
- `moveParticle()`: Move particle with boundary checking
- `getNeighbors()`: Get valid neighboring cells
### Basic Spatial Queries
- `queryArea()`: Simple area query
- `isValidPosition()`: Position validation
- `isEmpty()`: Cell emptiness check
### Advanced Spatial Queries
- `queryRadius()`: Radius-based search
- `queryRadiusFiltered()`: Filtered radius search
- `queryBox()`: Box-bounded search
- `queryKNearest()`: K-nearest neighbors
- `queryDenseRegions()`: Density-based search
### Grid Properties
- `getWidth()`: Grid width
- `getHeight()`: Grid height
- `getParticle()`: Particle access
### System Operations
- `update()`: System sync
- `clear()`: System reset
- `batchSyncDirtyStates()`: Force sync
### Performance Monitoring
- `getMetrics()`: Performance metrics
- `resetMetrics()`: Reset counters
### Memory Management
- `getCurrentMemoryUsage()`: Get current memory usage
- `getPeakMemoryUsage()`: Get peak memory usage
- `getMemoryAllocationMap()`: Get detailed memory allocation map
## Current Interface
The current user interface is minimal and designed primarily to visually verify that the grid system is working correctly. As this is a CS50X final project, the focus has been on implementing the core simulation functionality rather than a polished UI.
## Future Improvements
- Implement a more user-friendly interface
- Add more particle types and interactions
- Optimize memory usage for larger simulations
- Add persistence for saving/loading simulation states
## Building the Project
```bash
make
```
## Running the Simulation
```bash
./sand_simulation
```
## Requirements
- C++17 compatible compiler
- OpenMP for parallel processing
- SDL2 library