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Apache TVM is an open source machine learning compiler framework for CPUs, GPUs, and machine learning accelerators. It aims to enable machine learning engineers to optimize and run computations efficiently on any hardware backend. The vision of the Apache TVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging machine learning models for any hardware platform. Compilation of deep learning models in Keras, MXNet, PyTorch, Tensorflow, CoreML, DarkNet and more. Start using TVM with Python today, build out production stacks using C++, Rust, or Java the next day.
Features
- Compilation of deep learning models into minimum deployable modules
- Infrastructure to automatic generate and optimize models on more backend with better performance
- Compilation and minimal runtimes commonly unlock ML workloads on existing hardware
- CPUs, GPUs, browsers, microcontrollers, FPGAs and more
- Automatically generate and optimize tensor operators on more backends
- TVM adopts apache committer model
Project Samples
