- Fix syntax error in run.sh: remove extra quote and correct --log-path to --log-file
- Comment out HNSW algorithm implementation in enc.rs and algorithms.rs to simplify codebase
- Bump version to 0.3.1 in Cargo.toml
- Remove HNSW implementation guide and test files
- Add comprehensive project writeup documentation
- Add rayon dependency for parallel processing
- Implement rayon::broadcast for proper TFHE server key distribution across threads
- Fix bitonic sort to handle non-power-of-2 input sizes by padding to nearest 2^k
- Add parallel execution for recursive calls and comparison operations
- Update API to accept encrypted max values for safe padding
- Add Send/Sync traits for EncryptedNeighbor to enable thread safety
- Modify perform_knn_selection to support bitonic sort requirements
- Bump version to 0.2.0
This resolves the bitonic sort correctness issue where non-power-of-2 array sizes
caused incorrect results. The algorithm now properly pads from 100 to 128 elements
and should produce deterministic, correct results.
- Restructure code into separate modules: data, algorithms, logging, cache
- Add efficient caching system for keys and encrypted distances
- Implement three sorting algorithms: selection, bitonic, heap
- Add comprehensive logging with timestamps and progress tracking
- Configure musl target for static compilation
- Support command-line algorithm selection and cache control
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add plain KNN implementation with JSONL data processing
- Create Docker deployment setup with python:3.13-slim base
- Add comprehensive OJ-style testing system with accuracy validation
- Update README with detailed scoring mechanism explanation
- Add run.sh script following competition manual requirements
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add Cargo.toml with TFHE, CSV, and Serde dependencies
- Add .gitignore for Rust target directory
- Include Iris dataset for machine learning experiments
- Add plain KNN implementation binary
- Update LICENSE to MIT and improve README
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
