31 citations · 31 across the 3 of their papers we have counts for
3 papers
cs.LG2026
MTServe: Efficient Serving for Generative Recommendation Models with Hierarchical Caches
Xin Wang, Chi Ma, Shaobin Chen +14
Generative recommendation (GR) offers superior modeling capabilities but suffers from prohibitive inference costs due to the repeated encoding of long user histories. While cross-r…
cs.DB2026
HierarchicalKV: A GPU Hash Table with Cache Semantics for Continuous Online Embedding Storage
Haidong Rong, Jiashu Yao, Matthias Langer +12
Traditional GPU hash tables preserve every inserted key -- a dictionary assumption that wastes scarce High Bandwidth Memory (HBM) when embedding tables routinely exceed single-GPU…
cs.DC2022★ 31 cited
Merlin HugeCTR: GPU-accelerated Recommender System Training and Inference
Joey Wang, Yingcan Wei, Minseok Lee +9
In this talk, we introduce Merlin HugeCTR. Merlin HugeCTR is an open source, GPU-accelerated integration framework for click-through rate estimation. It optimizes both training and…