ARM 4-BIT PQ: SIMD-based Acceleration for Approximate Nearest Neighbor Search on ARM
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Abstract (arXiv)
We accelerate the 4-bit product quantization (PQ) on the ARM architecture. Notably, the drastic performance of the conventional 4-bit PQ strongly relies on x64-specific SIMD register, such as AVX2; hence, we cannot yet achieve such good performance on ARM. To fill this gap, we first bundle two 128-bit registers as one 256-bit component. We then apply shuffle operations for each using the ARM-specific NEON instruction. By making this simple but critical modification, we achieve a dramatic speedup for the 4-bit PQ on an ARM architecture. Experiments show that the proposed method consistently achieves a 10x improvement over the naive PQ with the same accuracy.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 12 of its 26 references that are in the map. First posted on arXiv 3 Mar 2022.
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12 of 26 references.
References · 12
- 2017Billion-scale similarity search with GPUscited by 2,477
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- 2017Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graphcited by 103
- 2018Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighborscited by 37
- 2021Multiplying Matrices Without Multiplyingcited by 30
- 2019Graph-based Nearest Neighbor Search: From Practice to Theorycited by 19
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- 2017Accelerated Nearest Neighbor Search with Quick ADCcited by 9
- 2018Link and code: Fast indexing with graphs and compact regression codescited by 9
- 2019Learning to Route in Similarity Graphscited by 9
- 2017Bolt: Accelerated Data Mining with Fast Vector Compressioncited by 7
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