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We explore the use of GPU for accelerating large scale nearest neighborsearch and we propose a fast vector-quantization-based exhaustive nearestneighbor search algorithm that can achieve high accuracy without any indexingconstruction specifically designed for cosine similarity. This algorithm uses anovel XOR-friendly binary quantization method to encode floating-point numberssuch that high-complexity multiplications can be optimized as low-complexitybitwise operations. Experiments show that, our quantization method takes shortpreprocessing time, and helps make the search speed of our exhaustive searchmethod much more faster than that of popular approximate nearest neighboralgorithms when high accuracy is needed.

Fast top-K Cosine Similarity Search through XOR-Friendly Binary Quantization on GPUs