A comprehensive toolkit for optimizing 3D NAND flash storage performance, reliability, and efficiency through advanced defect handling, performance optimization, firmware integration, and NAND characterization.
-
NAND Defect Handling
- 🛡️ Advanced BCH and LDPC error correction implementations
- 🔄 Dynamic bad block management
- ⚖️ Intelligent wear leveling algorithms
-
Performance Optimization
- 🗜️ Adaptive data compression (LZ4/Zstandard)
- 🚄 Multi-policy caching system (LRU, LFU, FIFO, TTL)
- ⚡ Parallel access operations
-
Firmware Integration
- 📝 Template-based firmware specification generation
- ✅ Comprehensive validation with schema and semantic rules
- 🧪 Automated test bench execution
-
NAND Characterization
- 📊 Data collection and statistical analysis
- 📈 Visualization of wear patterns and error distributions
- 🔍 Performance and reliability assessment
-
User Interfaces
- 🖥️ Intuitive GUI with dashboard and monitoring
- 💻 Interactive command-line interface
- 🔌 Python API for integration with other tools
- Python 3.9 or higher
- pip (Python package installer)
# Clone the repository
git clone https://github.com/muditbhargava66/3D-NAND-Flash-Storage-Optimization-Tool.git
# Navigate to the project directory
cd 3d-nand-optimization-tool
# Create a virtual environment (recommended)
python -m venv venv
source venv/bin/activate.bat # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Install in development mode
pip install -e .from nand_optimization import NANDController
from nand_optimization.utils import Config
# Load configuration
config = Config.from_file('config.yaml')
# Create controller and initialize
controller = NANDController(config, simulation_mode=True)
controller.initialize()
# Perform basic operations
controller.write_page(0, 0, b'Hello, NAND world!')
data = controller.read_page(0, 0)
print(data) # b'Hello, NAND world!'
# Clean up
controller.shutdown()Launch the graphical user interface for interactive operation:
python src/main.py --gui
Use the command-line interface for script-based or terminal operations:
# Basic CLI mode
python src/main.py --gui
# With custom configuration
python src/main.py --gui --config /path/to/config.yaml
# Run performance test script
python scripts/performance_test.py --iterations 100 --test-type all --simulatefrom nand_optimization import NANDController, ECCHandler, DataCompressor
from nand_optimization.utils import Config
# Setup
config = Config.from_file('config.yaml')
controller = NANDController(config)
controller.initialize()
# Batch operations using context manager
with controller.batch_operations():
for i in range(10):
controller.write_page(i, 0, f"Page {i} data".encode())
# Advanced features
ecc = ECCHandler(config)
compressor = DataCompressor(algorithm='lz4', level=5)
# Compress and encode data with ECC
data = b'Original data that needs protection and compression'
compressed = compressor.compress(data)
encoded = ecc.encode(compressed)
# Write encoded data
controller.write_page(10, 0, encoded)
# Clean up
controller.shutdown()The tool is highly configurable through YAML configuration files.
The default configuration file is located at resources/config/config.yaml:
# NAND Flash Configuration
nand_config:
page_size: 4096 # Page size in bytes
block_size: 256 # pages per block
num_blocks: 1024
oob_size: 128
num_planes: 1
# Optimization Configuration
optimization_config:
error_correction:
algorithm: "bch" # Options: "bch", "ldpc", "none"
bch_params:
m: 8 # Galois Field parameter
t: 4 # Error correction capability
compression:
algorithm: "lz4" # Options: "lz4", "zstd"
level: 3 # Compression level (1-9)
enabled: true # Enable/disable compression
caching:
capacity: 1024 # Cache capacity
policy: "lru" # Cache eviction policy
enabled: true # Enable/disable caching
# See documentation for full configuration optionsFor detailed configuration options, see the Configuration Guide.
The tool follows a modular architecture with clear separation of concerns:
┌─────────────────────────────┐ ┌─────────────────────────────┐
│ User Interface │◄────►│ Configuration Manager │
└───────────────┬─────────────┘ └─────────────────────────────┘
│
▼
┌─────────────────────────────┐
│ NAND Controller │
└───┬───────────┬───────────┬─┘
│ │ │
▼ ▼ ▼
┌─────────┐ ┌─────────┐ ┌─────────┐
│ NAND │ │ Perf │ │Firmware │
│ Defect │ │ Opt │ │ Int │
│Handling │ │ │ │ │
└────┬────┘ └────┬────┘ └────┬────┘
│ │ │
▼ ▼ ▼
┌─────────┐ ┌─────────┐ ┌─────────┐
│ Error │ │ Data │ │ Spec │
│ Corr │ │ Comp │ │ Gen │
└─────────┘ └─────────┘ └─────────┘
For more details, see the System Architecture documentation.
3d-nand-optimization-tool/
├── .github/
│ ├── ISSUE_TEMPLATE/
│ │ ├── bug_report.md
│ │ ├── feature_request.md
│ │ └── config.yml
│ ├── PULL_REQUEST_TEMPLATE.md
│ └── workflows/
│ ├── build.yml
│ └── lint.yml
├── docs/
│ ├── design_docs/
│ │ ├── system_architecture.md
│ │ ├── nand_defect_handling.md
│ │ ├── performance_optimization.md
│ │ ├── firmware_integration.md
│ │ └── nand_characterization.md
│ ├── CONTRIBUTING.md
│ ├── user_manual.md
│ └── api_reference.md
├── src/
│ ├── nand_defect_handling/
│ │ ├── __init__.py
│ │ ├── bch.py
│ │ ├── ldpc.py
│ │ ├── error_correction.py
│ │ ├── bad_block_management.py
│ │ └── wear_leveling.py
│ ├── performance_optimization/
│ │ ├── __init__.py
│ │ ├── data_compression.py
│ │ ├── caching.py
│ │ └── parallel_access.py
│ ├── firmware_integration/
│ │ ├── __init__.py
│ │ ├── firmware_specs.py
│ │ ├── test_benches.py
│ │ └── validation_scripts.py
│ ├── nand_characterization/
│ │ ├── __init__.py
│ │ ├── data_collection.py
│ │ ├── data_analysis.py
│ │ └── visualization.py
│ ├── ui/
│ │ ├── __init__.py
│ │ ├── main_window.py
│ │ ├── settings_dialog.py
│ │ └── result_viewer.py
│ ├── utils/
│ │ ├── __init__.py
│ │ ├── config.py
│ │ ├── logger.py
│ │ ├── file_handler.py
│ │ ├── nand_simulator.py
│ │ └── nand_interface.py
│ ├── nand_controller.py
│ ├── __init__.py
│ └── main.py
├── tests/
│ ├── __init__.py
│ ├── unit/
│ │ ├── __init__.py
│ │ ├── test_nand_defect_handling.py
│ │ ├── test_performance_optimization.py
│ │ ├── test_firmware_integration.py
│ │ └── test_nand_characterization.py
│ └── integration/
│ ├── __init__.py
│ └── test_integration.py
├── examples/
│ ├── basic_operations.py
│ ├── error_correction.py
│ ├── compression.py
│ ├── caching.py
│ ├── wear_leveling.py
│ ├── firmware_generation.py
│ └── examples.md
├── logs/
├── data/
│ ├── nand_characteristics/
│ │ ├── vendor_a/
│ │ └── vendor_b/
│ └── test_results/
├── resources/
│ ├── images/
│ └── config/
│ ├── config.yaml
│ ├── template.yaml
│ └── test_cases.yaml
├── scripts/
│ ├── validate.py
│ ├── performance_test.py
│ └── characterization.py
├── requirements.txt
├── pyproject.toml
├── MANIFEST.in
├── tox.ini
├── mypi.ini
├── CODE_OF_CONDUCT.md
├── CHANGELOG.md
├── .readthedocs.yaml
├── .gitignore
├── LICENSE
└── README.md
Comprehensive documentation is available in the docs directory:
- User Manual - Installation, configuration, and usage guide
- API Reference - Detailed API documentation
- Design Documents - Architecture and module-specific designs
The examples directory contains sample code demonstrating various features:
- Basic Operations - Reading, writing, and erasing
- Error Correction - Using BCH and LDPC coding
- Data Compression - LZ4 and Zstandard compression
- Caching - Using different eviction policies
- Wear Leveling - Advanced wear leveling techniques
- Firmware Generation - Creating firmware specs
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
See CONTRIBUTING.md for more information.
For development setup:
# Install development dependencies
pip install -r requirements-dev.txt
# Setup pre-commit hooks
pre-commit install
# Run code formatting
tox -e format
# Run type checking
tox -e type
# Run linting
tox -e lintThe project uses pytest for testing:
# Run all tests
pytest
# Run specific test categories
pytest tests/unit/
pytest tests/integration/
# Run tests with coverage report
pytest --cov=src tests/
# Run specific test file
pytest tests/unit/test_nand_defect_handling.py| Python Version | Linux | macOS | Windows |
|---|---|---|---|
| 3.9 | ✅ | ✅ | ✅ |
| 3.10 | ✅ | ✅ | ✅ |
| 3.11 | ✅ | ✅ | ✅ |
| 3.12 | ✅ | ✅ | ✅ |
| 3.13 | ✅ | ✅ | ✅ |
This project is licensed under the MIT License - see the LICENSE file for details.
Enjoy using the 3D NAND Optimization Tool?
⭐️ Star the repo and consider contributing!
📫 Contact: @muditbhargava66 🐛 Report Issues: Issue Tracker
© 2025 Mudit Bhargava. MIT License