zwang4/awesome-machine-learning-in-compilers
A curated list of research papers, datasets, and tools applying machine learning to compilers and program optimization.
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This repository aggregates academic papers, software tools, benchmarks, and datasets focused on using machine learning for compiler optimization and systems tuning. It covers topics such as iterative compilation, instruction-level optimization, parallelism mapping, cost modeling, and auto-tuning. The list is organized by theme including surveys, domain-specific optimizations, learning program representations, and memory/cache analysis.
Frequently asked
- What is zwang4/awesome-machine-learning-in-compilers?
- A curated list of research papers, datasets, and tools applying machine learning to compilers and program optimization.
- Is awesome-machine-learning-in-compilers open source?
- Yes — zwang4/awesome-machine-learning-in-compilers is open source, released under the CC0-1.0 license.
- How popular is awesome-machine-learning-in-compilers?
- zwang4/awesome-machine-learning-in-compilers has 1.7k stars on GitHub.
- Where can I find awesome-machine-learning-in-compilers?
- zwang4/awesome-machine-learning-in-compilers is on GitHub at https://github.com/zwang4/awesome-machine-learning-in-compilers.