{"ID":2856038,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.11759","arxiv_id":"2510.11759","title":"AwareCompiler: Agentic Context-Aware Compiler Optimization via a Synergistic Knowledge-Data Driven Framework","abstract":"Compiler optimization is crucial for enhancing program performance by transforming the sequence of optimization passes while maintaining correctness. Despite the promising potential of large language models (LLMs)-based agent for software optimization, automating compiler optimization remains challenging due to: (1) semantic misalignment between abstract program representations and concrete optimization passes, (2) inefficient interaction mechanisms between agents and compiler environments, and (3) reward sparsity from the extensive decision-making process within large optimization spaces. This paper introduces \\textbf{AwareCompiler}, an agentic framework for compiler optimization that addresses these challenges through three key innovations: structured knowledge integration and dataset construction, knowledge-driven adaptive pass generation, and data-driven hybrid training pipeline. Experimental results on standard benchmarks demonstrate that AwareCompiler significantly outperforms existing baselines in both performance and efficiency, highlighting the effectiveness of our synergistic knowledge-data-driven approach. Our code is publicly available at https://github.com/LHY-24/AwareCompiler.","short_abstract":"Compiler optimization is crucial for enhancing program performance by transforming the sequence of optimization passes while maintaining correctness. Despite the promising potential of large language models (LLMs)-based agent for software optimization, automating compiler optimization remains challenging due to: (1) se...","url_abs":"https://arxiv.org/abs/2510.11759","url_pdf":"https://arxiv.org/pdf/2510.11759v1","authors":"[\"Hongyu Lin\",\"Haolin Pan\",\"Haoran Luo\",\"Yuchen Li\",\"Kaichun Yao\",\"Libo Zhang\",\"Mingjie Xing\",\"Yanjun Wu\"]","published":"2025-10-13T02:02:36Z","proceeding":"cs.PL","tasks":"[\"cs.PL\",\"cs.AI\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false,"code_links":[{"ID":608306,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2856038,"paper_url":"https://arxiv.org/abs/2510.11759","paper_title":"AwareCompiler: Agentic Context-Aware Compiler Optimization via a Synergistic Knowledge-Data Driven Framework","repo_url":"https://github.com/LHY-24/AwareCompiler","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}