6 papers
Weave: Fine-Grained Dynamic SM Scheduling in an MoE Megakernel for Compute-Communication Overlap
Ziyu Huang, Yangjie Zhou, Chenhao Zhu +15
Mixture-of-Experts (MoE) inference under expert parallelism (EP) turns each MoE layer into a distributed computation with costly dispatch and combine communication. State-of-the-ar…
Dissecting How Die Scaling Breaks GPU Fine-grained Scheduling
Xiaoze Fan, Jianhao Wang, Weihao Cui +8
Modern GPUs are no longer physically symmetric. Die scaling leads to both manufacturing-driven floorsweeping and cache and memory partitioning. The former creates chip-specific com…
gMatch: Fine-Grained and Hardware-Efficient Subgraph Matching on GPUs
Weitian Chen, Shixuan Sun, Cheng Chen +3
Subgraph matching is a core operation in graph analytics, supporting a broad spectrum of applications from social network analysis to bioinformatics. Recent GPU-based approaches ac…
Efficient Densest Flow Queries in Transaction Flow Networks (Complete Version)
Jiaxin Jiang, Yunxiang Zhao, Lyu Xu +4
Transaction flow networks are crucial in detecting illicit activities such as wash trading, credit card fraud, cashback arbitrage fraud, and money laundering. \revise{Our collabora…
Revisiting the Design of In-Memory Dynamic Graph Storage
Jixian Su, Chiyu Hao, Shixuan Sun +7
The effectiveness of in-memory dynamic graph storage (DGS) for supporting concurrent graph read and write queries is crucial for real-time graph analytics and updates. Various meth…
FlowWalker: A Memory-efficient and High-performance GPU-based Dynamic Graph Random Walk Framework
Junyi Mei, Shixuan Sun, Chao Li +9
Dynamic graph random walk (DGRW) emerges as a practical tool for capturing structural relations within a graph. Effectively executing DGRW on GPU presents certain challenges. First…