From the 1 of 8 linked papers with an AI index.
5 papers · 1 filter
Can Large Language Models Recover Semantic Optimization Opportunities That Compilers Miss?
Hailong Jiang, Feng Yu, Emran Hossain +4
Optimizing compilers miss profitable transformations when their enabling semantics are absent from the analyzed program representation. We ask whether large language models (LLMs)…
BMOA: Baseline-Mechanism-Outcome Attribution for Compiler-Induced Numerical Deviations
Hailong Jiang, Emran Hossain, Feng Yu +4
The paper presents BMOA, a diagnostic framework that separates baseline, compiler mechanism, and outcome to attribute observed floating-point differences to compiler behavior and n…
Decode-Time Grammars: Constrained LLM Generation over a Refinement Order of Grammar Fragments
Shuoming Zhang, Ruiyuan Xu, Haofeng Li +7
Large language models now write a growing share of the world's code, increasingly inside agents and serving systems that compile, execute, or dispatch generated code without line-b…
The New Compiler Stack: A Survey on the Synergy of LLMs and Compilers
Shuoming Zhang, Jiacheng Zhao, Qiuchu Yu +4
This survey has provided a systematic overview of the emerging field of LLM-enabled compilation by addressing several key research questions. We first answered how LLMs are being i…
LEGO-Compiler: Enhancing Neural Compilation Through Translation Composability
Shuoming Zhang, Jiacheng Zhao, Chunwei Xia +4
Large language models (LLMs) have the potential to revolutionize how we design and implement compilers and code translation tools. However, existing LLMs struggle to handle long an…