sqrtspace-experiments/dashboard

Interactive Dashboard

A comprehensive Streamlit dashboard for exploring space-time tradeoffs in computing systems.

Features

1. Overview Page

• Visualizes Williams' theoretical bound: TIME[t] ⊆ SPACE[√(t log t)]
• Shows the fundamental space-time tradeoff curve
• Compares theoretical vs practical bounds

2. Theoretical Explorer

• Interactive parameter adjustment
• Real-time visualization of space requirements for given time bounds
• Constant factor analysis

3. Experimental Results

• Maze Solver: BFS vs memory-limited algorithms
• Sorting: In-memory vs checkpointed sorting
• Streaming: Sliding window performance
• Summary of all experimental findings

4. Real-World Systems

• Databases: Query optimization and join algorithms
• LLMs: Memory optimization techniques
• Distributed Computing: MapReduce and shuffle optimization

5. Tradeoff Calculator

• Input your system parameters
• Get recommendations for optimal configurations
• Compare different strategies

6. Interactive Demos

• Sorting visualizer
• Cache hierarchy simulator
• Live demonstrations of space-time tradeoffs

Running the Dashboard

Option 1: Using the launcher script

cd dashboard
python run_dashboard.py

Option 2: Direct streamlit command

cd dashboard
pip install -r requirements.txt
streamlit run app.py

The dashboard will open in your default browser at http://localhost:8501

Technology Stack

• Streamlit: Interactive web framework
• Plotly: Advanced interactive visualizations
• Pandas: Data manipulation
• NumPy: Numerical computations

Customization

The dashboard is fully customizable:

• Add new visualizations to app.py
• Modify color schemes in the CSS section
• Add new pages in the sidebar navigation
• Import real experimental data to replace simulated data

Screenshots

The dashboard includes:

• Dark theme optimized for data visualization
• Responsive layout for different screen sizes
• Interactive controls for exploring parameters
• Real-time updates as you adjust settings