ONNC
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About
ONNC (Open Neural Network Compiler) is a specialized compilation framework designed for deep learning accelerators that support ONNX (Open Neural Network Exchange) operators. It enables seamless model transformation into DLA-specific binaries, ensuring that ONNX models execute efficiently across various deep learning accelerators. ONNC, an open-source tool, is notable for its support of NVDLA-based hardware, allowing the compilation of models into NVDLA Loadable files and facilitating system-level exploration of inference designs. It integrates with the LLVM compiler, offering a modular framework that can adapt to both compatible and unique DLA designs. The compiler is structured into distinct phases, providing reusable optimizations and a flexible pass manager, making it accessible for AI researchers and engineers familiar with LLVM. ONNC also supports a vibrant community of developers contributing through various sub-projects, tutorials, and GitHub collaboration.
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Task
Features
• open-source
• community-driven development
• retargetable compilation framework
• extensive documentation and tutorials
• five-phase ai compilation process
• reusable compiler optimizations
• modular framework for optimization
• integration with llvm
• nvdla backend for model compilation
• support for onnx operators
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