3 papers
cs.SE2026
AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning
Zepeng Li, Jie Ren, Zhanyong Tang +2
Large Language Models (LLMs) show promise for code compilation tasks, but applying them to runtime performance tuning is difficult due to complex microarchitectural effects and noi…
cs.CR2025
Accelerating Private Large Transformers Inference through Fine-grained Collaborative Computation
Yuntian Chen, Zhanyong Tang, Tianpei Lu +3
Homomorphic encryption (HE) and secret sharing (SS) enable computations on encrypted data, providing significant privacy benefits for large transformer-based models (TBM) in sensit…
cs.SE2024
Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization
Huanting Wang, Patrick Lenihan, Zheng Wang
Supervised machine learning techniques have shown promising results in code analysis and optimization problems. However, a learning-based solution can be brittle because minor chan…