Accelerated Nearest Neighbor Search with Quick ADC

Abstract : Efficient Nearest Neighbor (NN) search in high-dimensional spaces is a foundation of many multimedia retrieval systems. Because it offers low responses times, Product Quantization (PQ) is a popular solution. PQ compresses high-dimensional vectors into short codes using several sub-quantizers, which enables in-RAM storage of large databases. This allows fast answers to NN queries, without accessing the SSD or HDD. The key feature of PQ is that it can compute distances between short codes and high-dimensional vectors using cache-resident lookup tables. The efficiency of this technique, named Asymmetric Distance Computation (ADC), remains limited because it performs many cache accesses. In this paper, we introduce Quick ADC, a novel technique that achieves a 3 to 6 times speedup over ADC by exploiting Single Instruction Multiple Data (SIMD) units available in current CPUs. Efficiently exploiting SIMD requires algorithmic changes to the ADC procedure. Namely, Quick ADC relies on two key modifications of ADC: (i) the use 4-bit sub-quantizers instead of the standard 8-bit sub-quantizers and (ii) the quantization of floating-point distances. This allows Quick ADC to exceed the performance of state-of-the-art systems, e.g., it achieves a Recall@100 of 0.94 in 3.4 ms on 1 billion SIFT descriptors (128-bit codes).
Type de document :
Communication dans un congrès
ICMR 2017 - ACM International Conference on Multimedia Retrieval, Jun 2017, Bucarest, Romania. pp.159-166, Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval. 〈10.1145/3078971.3078992〉
Liste complète des métadonnées

https://hal.inria.fr/hal-01660730
Contributeur : Davide Frey <>
Soumis le : lundi 11 décembre 2017 - 12:25:05
Dernière modification le : mercredi 16 mai 2018 - 11:24:13

Lien texte intégral

Identifiants

Citation

Fabien André, Anne-Marie Kermarrec, Nicolas Le Scouarnec. Accelerated Nearest Neighbor Search with Quick ADC. ICMR 2017 - ACM International Conference on Multimedia Retrieval, Jun 2017, Bucarest, Romania. pp.159-166, Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval. 〈10.1145/3078971.3078992〉. 〈hal-01660730〉

Partager

Métriques

Consultations de la notice

264