3 papers
cs.PF2026
PipeWeave: Synergizing Analytical and Learning Models for Unified GPU Performance Prediction
Kaixuan Zhang, Yunfan Cui, Shuhao Zhang +8
The rapid expansion of Transformer-based large language models has dramatically increased the need for high-performance GPUs. As a result, there is growing demand for fast, accurat…
cs.PF2026
WaveTune: Wave-aware Bilinear Modeling for Efficient GPU Kernel Auto-tuning
Kaixuan Zhang, Chutong Ding, Shiyou Qian +6
The rapid adoption of Large Language Models (LLMs) has made GPU inference efficiency an increasingly critical system concern. The runtime of LLM workloads is largely dominated by t…
cs.SE2025
LLM-SrcLog: Towards Proactive and Unified Log Template Extraction via Large Language Models
Jiaqi Sun, Wei Li, Heng Zhang +4
Log parsing transforms raw logs into structured templates containing constants and variables. It underpins anomaly detection, failure diagnosis, and other AIOps tasks. Current pars…