R He, J McAuley - 2016 IEEE 16th international conference on …, 2016 - ieeexplore.ieee.org
Predicting personalized sequential behavior is a key task for recommender systems. In order to predict user actions such as the next product to purchase, movie to watch, or place to visit …
We present Recipe, a principled approach for converting concurrent DRAM indexes into crash-consistent indexes for persistent memory (PM). The main insight behind Recipe is that …
FaSST is an RDMA-based system that provides distributed in-memory transactions with serializability and durability. Existing RDMA-based transaction processing systems use one …
B Lu, X Hao, T Wang, E Lo - arXiv preprint arXiv:2003.07302, 2020 - arxiv.org
Byte-addressable persistent memory (PM) brings hash tables the potential of low latency, cheap persistence and instant recovery. The recent advent of Intel Optane DC Persistent …
F Xia, D Jiang, J Xiong, N Sun - 2017 USENIX Annual Technical …, 2017 - usenix.org
Hybrid memory systems consisting of DRAM and Non-Volatile Memory are promising to persist data fast. The index design of existing key-value stores for hybrid memory fails to …
Index structures are one of the most important tools that DBAs leverage to improve the performance of analytics and transactional workloads. However, building several indexes …
L Lersch, X Hao, I Oukid, T Wang… - Proceedings of the VLDB …, 2019 - dl.acm.org
Persistent memory (PM) is fundamentally changing the way database index structures are built by enabling persistence, high performance, and (near) instant recovery all on the …
X Wei, R Chen, H Chen, B Zang - ACM Transactions on Storage (TOS), 2021 - dl.acm.org
RDMA (Remote Direct Memory Access) has gained considerable interests in network- attached in-memory key-value stores. However, traversing the remote tree-based index in …
P Li, Y Hua, J Jia, P Zuo - Proceedings of the VLDB Endowment, 2021 - dl.acm.org
Index structures in memory systems become important to improve the entire system performance. The promising learned indexes leverage deep-learning models to …