PTStore (Prefix Tensor Store): Distributed Prefix Caching and Replication for High Throughput Inference Serving

Abstract:Inspired by the design of client caching in Content Delivery Networks (CDNs), PTStore distributes and replicates popular tensors that form reusable KV cache prefixes, which are the main technique used by state of art approaches to accelerate inferences. This reduces the latency of accessing the KV cache and alleviates load imbalance caused by a disproportionately large number of requests on servers containing popular tensors. Furthermore, thanks to decentralization, PTStore allows the expansion of the size of the KV cache for LLM inference by orders of magnitude. As a result, PTStore can execute inferences on long passage Q\&A datasets 5-6 times more efficiently than current baselines, which do not aggregate memory across different nodes and GPUs and therefore require regenerating the KV cache.

Artificial Intelligence (cs.AI); Distributed, Parallel, and Cluster Computing (cs.DC)

arXiv:2607.22648 [cs.AI]

(or arXiv:2607.22648v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2607.22648 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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