Add vector search benchmarks to benchmarking suite#7399
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) ## Summary Tracking issue: #7297 Optimizes inner product with manual partial sum decomposition (because the compiler can't optimize this because float addition is not associative). Also removes the old benchmarks as they no longer really time the correct thing anymore. The real benchmarks will be finished here: #7399. This change also adds the `vortex-tensor/src/vector_search.rs` file to support that soon. ## Testing N/A Signed-off-by: Connor Tsui <connor.tsui20@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com> Signed-off-by: Connor Tsui <connor.tsui20@gmail.com>
Signed-off-by: Connor Tsui <connor.tsui20@gmail.com>
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Summary
Tracking issue: #7297
Adds a
vector-search-benchcrate similar to VectorDBBench.The benchmark brute-forces cosine similarity search over public VectorDBBench datasets (Cohere, OpenAI, etc).
Since Vortex is not a database, we do not measure things like vector inserts and deletes. instead we just measure storage size and throughput for four targets:
&[f32]Every variant goes through a correctness check against the uncompressed scan before timing.
Not sure if this makes sense to have on a PR benchmark yet since this can only happen on a very specific array tree that will have a very specific optimized implementation.
Testing
N/A