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arXiv · 2504.14903

ColBERT-serve: Efficient Multi-Stage Memory-Mapped Scoring

Kaili Huang·Thejas Venkatesh·Uma Dingankar·Antonio Mallia·Daniel Campos·Jian Jiao·Christopher Potts·Matei Zaharia·Kwabena Boahen·Omar Khattab·Saarthak Sarup·Keshav Santhanam
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Abstract

We study serving retrieval models, specifically late interaction models like ColBERT, to many concurrent users at once and under a small budget, in which the index may not fit in memory. We present ColBERT-serve, a novel serving system that applies a memory-mapping strategy to the ColBERT index, reducing RAM usage by 90% and permitting its deployment on cheap servers, and incorporates a multi-stage architecture with hybrid scoring, reducing ColBERT's query latency and supporting many concurrent queries in parallel.

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Kaili Huang, Thejas Venkatesh, Uma Dingankar, Antonio Mallia, Daniel Campos, Jian Jiao, Christopher Potts, Matei Zaharia, Kwabena Boahen, Omar Khattab, Saarthak Sarup, Keshav Santhanam. 2025-04-21. ColBERT-serve: Efficient Multi-Stage Memory-Mapped Scoring. https://arxiv.org/abs/2504.14903

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