Jasper¶
Fast and scalable GPU-native ANNS index.
Jasper is a GPU-native approximate nearest neighbor search (ANNS) index designed for speed and scalability. Drawing on the Vamana graph index, Jasper delivers state-of-the-art construction throughput and query performance entirely on the GPU.
Why Jasper?¶
- Fast construction. Jasper matches or exceeds state-of-the-art GPU-based ANNS libraries in index build throughput, and scales out to billion-vector datasets.
- Directional beam search. Jasper supports directional beam search, a faster search algorithm and index layout for both device-memory and host-memory search.
- Index insert, update, and delete. Jasper supports index updates without rebuilding the entire index.
- RaBitQ quantization. Jasper supports RaBitQ for vector quantization, which achieves higher performance than traditional product quantization and maps naturally to GPU computations.
Query Performance¶
Query throughput vs. recall on agnews-mxbai dataset (1024 dimensions) using NVIDIA RTX 6000 blackwell server edition GPU. 1
Papers¶
- GPU-Accelerated ANNS: Quantized for Speed, Built for Change, VLDB 2026.
- Directional Beam Search, VecDB Workshop 2026.
Citation¶
@misc{mccoy2026gpuacceleratedannsquantizedspeed,
title={GPU-Accelerated ANNS: Quantized for Speed, Built for Change},
author={Hunter McCoy and Zikun Wang and Prashant Pandey},
year={2026},
eprint={2601.07048},
archivePrefix={arXiv},
primaryClass={cs.DB},
url={https://arxiv.org/abs/2601.07048},
}