Uploaded June 2026 | Updated September 2026, 3 weeks ago
2026 EuroLLVM Developers' Meeting
llvm.org/devmtg/2026-04
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Title: Python Bindings for IR2Vec
Speaker: Nishant Sachdeva
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Slides: llvm.org/devmtg/2026-04/slides/student_technical_talk/student_technical_talk_sachdeva.pdf
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IR2Vec is a widely adopted framework for generating vector embeddings from LLVM IR to enable machine-learning-driven compiler optimizations. This work introduces native Python bindings for IR2Vec using pybind11, enabling seamless and efficient integration with Python-based ML ecosystems such as PyTorch and TensorFlow. By replacing subprocess-based CLI invocation with a direct programmatic interface, the bindings eliminate process overhead, provide inbuilt C++-Python type conversion, and support robust exception handling. The implementation and usage are demonstrated through practical embedding-generation examples. The project is currently under active development for upstream integration into the LLVM monorepo, with multiple pull requests already accepted, and is available in beta form via TestPyPI.
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Videos Edited by Bash Films: BashFilms.com
2026 EuroLLVM Developers' Meeting
llvm.org/devmtg/2026-04
------
Title: Python Bindings for IR2Vec
Speaker: Nishant Sachdeva
------
Slides: llvm.org/devmtg/2026-04/slides/student_technical_talk/student_technical_talk_sachdeva.pdf
-----
IR2Vec is a widely adopted framework for generating vector embeddings from LLVM IR to enable machine-learning-driven compiler optimizations. This work introduces native Python bindings for IR2Vec using pybind11, enabling seamless and efficient integration with Python-based ML ecosystems such as PyTorch and TensorFlow. By replacing subprocess-based CLI invocation with a direct programmatic interface, the bindings eliminate process overhead, provide inbuilt C++-Python type conversion, and support robust exception handling. The implementation and usage are demonstrated through practical embedding-generation examples. The project is currently under active development for upstream integration into the LLVM monorepo, with multiple pull requests already accepted, and is available in beta form via TestPyPI.
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Videos Edited by Bash Films: BashFilms.com
