ARM 4-BIT PQ: SIMD-BASED ACCELERATION FOR APPROXIMATE NEAREST NEIGHBOR SEARCH ON ARM

被引:2
作者
Matsui, Yusuke [1 ]
Imaizumi, Yoshiki [2 ]
Miyamoto, Naoya [2 ]
Yoshifuji, Naoki [2 ]
机构
[1] Univ Tokyo, Tokyo, Japan
[2] Fixstars Corp, Tokyo, Japan
来源
2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2022年
关键词
ARM; nearest neighbor search; product quantization; SIMD;
D O I
10.1109/ICASSP43922.2022.9746589
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
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.
引用
收藏
页码:2080 / 2084
页数:5
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