A GPU-accelerated binary vector index
This is a vector index I built that supports insertion and k-nearest neighbors (k-NN) querying, optimized for GPUs. It operates entirely in CUDA and can process queries on half a billion vectors in under 200 milliseconds. The codebase is structured as a standalone library with an HTTP API for remote access. It’s intended for high-performance search tasks—think similarity search, AI model retrieval, or reinforcement learning replay buffers. The codebase is located at https://github.com/rodlaf/BinaryGPUIndex.
A GPU-accelerated binary vector index launched on February 17, 2025 with 65 votes, #446 of 5,999 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
This GPU-accelerated vector index enables fast insertion and k-nearest neighbor queries on massive datasets, processing half a billion vectors in under 200 milliseconds. Built entirely in CUDA, it operates as a standalone library with an HTTP API for remote access. It targets developers building high-performance search systems, including similarity search, AI model retrieval, and reinforcement learning replay buffers.
written from the facts on this page · September 2026
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