mirror of
https://github.com/ruvnet/RuVector.git
synced 2026-05-31 13:29:29 +00:00
fd7a9fce7d
Optimizations applied: - FlatVectors: contiguous f32 slab (eliminates Vec<Vec> indirection) - VisitedSet: O(1) clear via generation counter (replaces HashSet) - 4-accumulator ILP for L2 distance (auto-vectorized) - Flat PQ distance table (cache-line friendly) - Parallel medoid finding via rayon - Zero-copy save (write flat slab directly) - Optional simsimd feature for hardware NEON/AVX2/AVX-512 - Optional gpu feature with Metal/CUDA/Vulkan dispatch stubs Results (5K vectors, 128d): - Search: 90µs → 55µs (1.6x faster) - Build: 6.9s → 6.2s (10% faster) - Recall@10: 0.998 (maintained) - 17 tests passing Co-Authored-By: claude-flow <ruv@ruv.net>
28 lines
775 B
TOML
28 lines
775 B
TOML
[package]
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name = "ruvector-diskann"
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version.workspace = true
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edition.workspace = true
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authors.workspace = true
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license.workspace = true
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repository.workspace = true
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description = "DiskANN/Vamana — SSD-friendly approximate nearest neighbor search with product quantization"
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[features]
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default = []
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gpu = [] # Feature flag for GPU acceleration (CUDA/Metal stubs)
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simd = ["simsimd"]
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[dependencies]
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memmap2 = { workspace = true }
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rayon = { workspace = true }
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serde = { workspace = true }
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serde_json = { workspace = true }
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bincode = { workspace = true }
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thiserror = { workspace = true }
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rand = { workspace = true }
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parking_lot = "0.12"
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bytemuck = { version = "1.14", features = ["derive"] }
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simsimd = { workspace = true, optional = true }
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[dev-dependencies]
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tempfile = "3.9"
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