[HN Gopher] Show HN: A GPU-accelerated binary vector index
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       Show HN: 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.
        
       Author : andes314
       Score  : 27 points
       Date   : 2025-02-17 00:45 UTC (1 days ago)
        
 (HTM) web link (rlafuente.com)
 (TXT) w3m dump (rlafuente.com)
        
       | martinloretz wrote:
       | Great work. Can you elaborate on how the radix selection works
       | and how to get that working with float's and inner product
       | distance? I just quickly checked the code, I'm not familiar with
       | radix selection, but really interested in making extremely fast
       | GPU indices.
        
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