… [58] appears suitable for billion-scale datasets with quantization … on GPUs, which we compare
against in Section 6.4 on the largest (billion-scale) public benchmarks for similarity search. …

… In this paper, we present RobustiQ, a novel billion-scale ANN similarity search framework.
RobustiQ includes a three-level hierarchical inverted indexing structure based on Vector and …

… In this subsection we introduce several billion-scale similarity retrieval systems that apply VQ…
-the-art systems for billion-scale high-dimensional ANN search. Their indexing structure and …

… for billion-scale dataset In this subsection we introduce several billion-scale similarity …
PQT [21] is the first retrieval system that can handle billion-scale dataset on GPU. PQT uses …

… GPU-based ANNS method which works efficiently on billion-scale datasets that cannot entirely
fit in the GPU … Billion-scale similarity search with gpus. IEEE Transactions on Big Data 7, 3 …

… GPU-based ANNS method which works efficiently on billion-scale datasets that cannot entirely
fit in the GPU … Billion-scale similarity search with gpus. IEEE Transactions on Big Data 7, 3 …

… This competition1 compares ANNS algorithms at billion-scale … , often the bottleneck in serving
billion-scale indices, where the … We compiled six diverse billion-scale datasets, four newly …

… Additionally, GGrid [39] leverages GPU-… GPU-based Batch search [30] optimizes brute-force,
approximate, and compressed-domain search to facilitate billion-scale similarity search. The …

… general purpose graphics processing units (GPU) to show impressive performance on billion
scale image datasets, with relatively small (128) dimensions. However, PQ, similar to other …

… Rapid advances in GPU hardware and multiple areas of Deep Learning open up a new
opportunity for billion-scale information retrieval with exhaustive search. Building on top of the …