12 citations · 12 across the 5 of their papers we have counts for
5 papers
T-LLM Compiler: Trusted LLM-based Code Optimization and Verification Framework
Zahra Fazel, Sunanda Gamage, Shayan Shirahmad Gale Bagi +5
Recent advances in Large Language Models (LLMs) have opened opportunities to apply high-level code transformations to the field of code optimization, and it has since emerged as on…
Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization
Dongjie Chen, Ping Zhao, Bohua Zhan +11
Recent advances in large language models (LLMs) have enabled automated kernel generation and optimization, but most existing approaches rely on surface signals such as compilation…
VecTrans: Enhancing Compiler Auto-Vectorization through LLM-Assisted Code Transformations
Zhongchun Zheng, Kan Wu, Long Cheng +7
Auto-vectorization is a fundamental optimization for modern compilers to exploit SIMD parallelism. However, state-of-the-art approaches still struggle to handle intricate code patt…
ACPO: AI-Enabled Compiler Framework
Amir H. Ashouri, Muhammad Asif Manzoor, Duc Minh Vu +7
The key to performance optimization of a program is to decide correctly when a certain transformation should be applied by a compiler. This is an ideal opportunity to apply machine…
MLGOPerf: An ML Guided Inliner to Optimize Performance
Amir H. Ashouri, Mostafa Elhoushi, Yuzhe Hua +4
For the past 25 years, we have witnessed an extensive application of Machine Learning to the Compiler space; the selection and the phase-ordering problem. However, limited works ha…