140 citations · 268 across the 8 of their papers we have counts for
8 papers
Decoupling Disaggregated Memory Optimizations from Indexing: A Compiler-Runtime Approach
Xinpeng Zhao, Zeling Long, Chaichon Wongkham +5
Disaggregated memory (DM) decouples compute and memory into independently scalable pools, connected over a slower interconnect rather than a local bus. This decoupling is exactly w…
Aker: Density-Aware Approximate Caching for Vector Search (Extended Version)
Sukjoon Oh, Minki Kang, Dohyun Kim +5
Disk-based approximate nearest neighbor search (ANNS) incurs high I/O overhead due to frequent disk accesses during index traversal. Approximate caching, which reuses the results o…
EMA: Approximate Nearest Neighbor Search with General Attribute Filtering and Dynamic Updates
Mocheng Li, Baotong Lu, James Cheng +1
Filtering Approximate Nearest Neighbor (FANN) search is a critical and emerging task for strengthening the query capability of vector databases, supporting applications such as rec…
DEX: Scalable Range Indexing on Disaggregated Memory [Extended Version]
Baotong Lu, Kaisong Huang, Chieh-Jan Mike Liang +2
Memory disaggregation can potentially allow memory-optimized range indexes such as B+-trees to scale beyond one machine while attaining high hardware utilization and low cost. Desi…
Are Updatable Learned Indexes Ready?
Chaichon Wongkham, Baotong Lu, Chris Liu +3
Recently, numerous promising results have shown that updatable learned indexes can perform better than traditional indexes with much lower memory space consumption. But it is unkno…
APEX: A High-Performance Learned Index on Persistent Memory
Baotong Lu, Jialin Ding, Eric Lo +2
The recently released persistent memory (PM) offers high performance, persistence, and is cheaper than DRAM. This opens up new possibilities for indexes that operate and persist da…
Dash: Scalable Hashing on Persistent Memory
Baotong Lu, Xiangpeng Hao, Tianzheng Wang +1
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 Mem…
High Performance Depthwise and Pointwise Convolutions on Mobile Devices
Pengfei Zhang, Eric Lo, Baotong Lu
Lightweight convolutional neural networks (e.g., MobileNets) are specifically designed to carry out inference directly on mobile devices. Among the various lightweight models, dept…