4 papers
ComFuse: Fusing Complex Memory-Intensive Subgraphs with Compute-Intensive Kernels For Modern GPU Architectures
Di Mu, Tengyuan Jin, Zhenkun Wang +6
Modern deep learning workloads increasingly comprise heterogeneous computation graphs that combine compute-intensive operators with memory-intensive subgraphs. Existing deep learni…
Dynamically Detect and Fix Hardness for Efficient Approximate Nearest Neighbor Search
Zhiyuan Hua, Qiji Mo, Zebin Yao +8
Approximate Nearest Neighbor Search (ANNS) has become a fundamental component in many real-world applications. Among various ANNS algorithms, graph-based methods are state-of-the-a…
Demystifying and Enhancing the Efficiency of Large Language Model Based Search Agents
Tiannuo Yang, Zebin Yao, Bowen Jin +4
Large Language Model (LLM)-based search agents have shown remarkable capabilities in solving complex tasks by dynamically decomposing problems and addressing them through interleav…
Abnormality Forecasting: Time Series Anomaly Prediction via Future Context Modeling
Sinong Zhao, Wenrui Wang, Hongzuo Xu +5
Identifying anomalies from time series data plays an important role in various fields such as infrastructure security, intelligent operation and maintenance, and space exploration.…