TPU-KNN: K Nearest Neighbor Search at Peak FLOP/sDownload PDF

Published: 31 Oct 2022, Last Modified: 09 Jan 2023NeurIPS 2022 AcceptReaders: Everyone
Keywords: TPU, K-nearest neighbor search, Approximate nearest neighbor search, roofline model, accelerator
Abstract: This paper presents a novel nearest neighbor search algorithm achieving TPU (Google Tensor Processing Unit) peak performance, outperforming state-of-the-art GPU algorithms with similar level of recall. The design of the proposed algorithm is motivated by an accurate accelerator performance model that takes into account both the memory and instruction bottlenecks. Our algorithm comes with an analytical guarantee of recall in expectation and does not require maintaining sophisticated index data structure or tuning, making it suitable for applications with frequent updates. Our work is available in the open-source package of Jax and Tensorflow on TPU.
Supplementary Material: pdf
TL;DR: Novel nearest neighbor search algorithm achieving TPU peak performance with recall guarantee.
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