17 citations · 39 across the 10 of their papers we have counts for
10 papers
SpecDB: LLM-Generated Customized Databases via Feature-Oriented Decomposition
Yunkai Lou, Longbin Lai, Shunyang Li +2
Mainstream relational databases ship a uniform feature set across deployments, although individual workloads exercise only a fraction of the available subsystems. We investigate wh…
A Few GPUs, A Whole Lotta Scale: Faithful LLM Training Emulation with PrismLLM
Shaoke Xi, ChonLam Lao, Boyi Jia +11
Large language model (LLM) training today runs on clusters spanning thousands of GPUs. While this scale enables rapid model advances, developing, debugging, and performance-tuning…
OpenHospital: A Thing-in-itself Arena for Evolving and Benchmarking LLM-based Collective Intelligence
Peigen Liu, Rui Ding, Yuren Mao +7
Large Language Model (LLM)-based Collective Intelligence (CI) presents a promising approach to overcoming the data wall and continuously boosting the capabilities of LLM agents. Ho…
TrainMover: An Interruption-Resilient Runtime for ML Training
ChonLam Lao, Jiaqi Gao, Jiamin Cao +13
Large-scale ML training jobs are frequently interrupted by hardware and software anomalies, failures, and management events. Existing solutions like checkpoint-restart or runtime r…
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation
Yuxing Han, Ziniu Wu, Peizhi Wu +11
Cardinality estimation (CardEst) plays a significant role in generating high-quality query plans for a query optimizer in DBMS. In the last decade, an increasing number of advanced…
Higher-Order Neighborhood Truss Decomposition
Zi Chen, Long Yuan, Li Han +1
-truss model is a typical cohesive subgraph model and has been received considerable attention recently. However, the -truss model only considers the direct common neighbors…
FSPN: A New Class of Probabilistic Graphical Model
Ziniu Wu, Rong Zhu, Andreas Pfadler +5
We introduce factorize sum split product networks (FSPNs), a new class of probabilistic graphical models (PGMs). FSPNs are designed to overcome the drawbacks of existing PGMs in te…
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation
Rong Zhu, Ziniu Wu, Yuxing Han +5
Query optimizers rely on accurate cardinality estimation (CardEst) to produce good execution plans. The core problem of CardEst is how to model the rich joint distribution of attri…
Taming the Expressiveness and Programmability of Graph Analytical Queries
Lu Qin, Longbin Lai, Kongzhang Hao +6
Graph database has enjoyed a boom in the last decade, and graph queries accordingly gain a lot of attentions from both the academia and industry. We focus on analytical queries in…
A Survey and Experimental Analysis of Distributed Subgraph Matching
Longbin Lai, Zhu Qing, Zhengyi Yang +10
Recently there emerge many distributed algorithms that aim at solving subgraph matching at scale. Existing algorithm-level comparisons failed to provide a systematic view to the pr…