5 citations · 10 across the 18 of their papers we have counts for
6 papers · 1 filter
Exact Acceleration of Subgraph Graph Neural Networks by Eliminating Computation Redundancy
Qian Tao, Xiyuan Wang, Muhan Zhang +3
Graph neural networks (GNNs) have become a prevalent framework for graph tasks. Many recent studies have proposed the use of graph convolution methods over the numerous subgraphs o…
LSMGraph: A High-Performance Dynamic Graph Storage System with Multi-Level CSR
Song Yu, Shufeng Gong, Qian Tao +9
The growing volume of graph data may exhaust the main memory. It is crucial to design a disk-based graph storage system to ingest updates and analyze graphs efficiently. However, e…
AsymKV: Enabling 1-Bit Quantization of KV Cache with Layer-Wise Asymmetric Quantization Configurations
Qian Tao, Wenyuan Yu, Jingren Zhou
Large language models have shown exceptional capabilities in a wide range of tasks, such as text generation and video generation, among others. However, due to their massive parame…
Towards a Converged Relational-Graph Optimization Framework
Yunkai Lou, Longbin Lai, Bingqing Lyu +5
The recent ISO SQL:2023 standard adopts SQL/PGQ (Property Graph Queries), facilitating graph-like querying within relational databases. This advancement, however, underscores a sig…
A Survey of Distributed Graph Algorithms on Massive Graphs
Lingkai Meng, Yu Shao, Long Yuan +7
Distributed processing of large-scale graph data has many practical applications and has been widely studied. In recent years, a lot of distributed graph processing frameworks and…
A Modular Graph-Native Query Optimization Framework
Bingqing Lyu, Xiaoli Zhou, Longbin Lai +4
Complex Graph Patterns (CGPs), which combine pattern matching with relational operations, are widely used in real-world applications. Existing systems rely on monolithic architectu…