brainy/src/hnsw
David Snelling cff9ae8215 feat: add GPU acceleration for embeddings with smart device auto-detection
Add comprehensive GPU support for embedding generation while maintaining optimized CPU processing for distance calculations:

- Add device option to TransformerEmbeddingOptions (auto, cpu, webgpu, cuda, gpu)
- Implement smart auto-detection of best available GPU (WebGPU for browsers, CUDA for Node.js)
- Add automatic CPU fallback if GPU initialization fails
- Fix misleading GPU acceleration claims in distance functions and HNSW search
- Update documentation to accurately reflect GPU usage (embeddings only)
- Add comprehensive example demonstrating GPU acceleration usage
- Maintain full backward compatibility with existing code

Performance improvements: 3-5x faster embedding generation when GPU is available, while keeping faster CPU processing for 384-dim vector distance calculations.
2025-08-05 20:00:04 -07:00
..
distributedSearch.ts fix(build): resolve TypeScript compilation errors in optimization modules 2025-08-03 16:51:20 -07:00
hnswIndex.ts feat: add GPU acceleration for embeddings with smart device auto-detection 2025-08-05 20:00:04 -07:00
hnswIndexOptimized.ts fix(core): resolve TypeScript compilation errors and test failures 2025-08-04 20:00:38 -07:00
optimizedHNSWIndex.ts fix(build): resolve TypeScript compilation errors in optimization modules 2025-08-03 16:51:20 -07:00
partitionedHNSWIndex.ts feat(partitioning): simplify partition strategies and enable auto-tuning of semantic clusters 2025-08-03 17:26:41 -07:00
scaledHNSWSystem.ts feat(partitioning): simplify partition strategies and enable auto-tuning of semantic clusters 2025-08-03 17:26:41 -07:00