osobhandClaude Opus 5
97e65f2adf
The int8-quantised HNSW index compared vectors with a scalar loop that the compiler vectorised for the x86-64 baseline (SSE2), while the f32 path it was measured against goes through `clawhdf5-accel` and runs AVX2. So the ~13% throughput cost recorded for `quantized_index` was a missing kernel rather than a property of int8. `clawhdf5_accel::dot_i8` adds a scalar fallback and an AVX2 path: sign-extend each 16-byte half to i16, then `madd_epi16`, which multiplies and sums adjacent pairs straight into i32 lanes. It is dispatched through the same detected backend as the f32 kernels, and the index now calls it. Integer arithmetic, so the SIMD path must agree with scalar bit for bit — tested at lengths that are and are not multiples of the block, and at the -128 extreme for overflow. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
clawhdf5-ann
HNSW approximate nearest neighbor index stored as HDF5.
Features
- Build and query HNSW indexes persisted in HDF5 format
- Pure Rust, no C dependencies
- Efficient similarity search for high-dimensional vectors
Usage
use clawhdf5_ann::HnswIndex;
let index = HnswIndex::from_hdf5("vectors.h5").unwrap();
let neighbors = index.search(&query, 10);
License
MIT