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VTA: Open, Modular, Deep Learning Accelerator Stack
===================================================
VTA (versatile tensor accelerator) is an open-source deep learning accelerator complemented with an end-to-end TVM-based compiler stack.

The key features of VTA include:

- Generic, modular, open-source hardware
  - Streamlined workflow to deploy to FPGAs.
  - Simulator support to prototype compilation passes on regular workstations.
- Driver and JIT runtime for both simulator and FPGA hardware back-end.
- End-to-end TVM stack integration
  - Direct optimization and deployment of models from deep learning frameworks via TVM.
  - Customized and extensible TVM compiler back-end.
  - Flexible RPC support to ease deployment, and program FPGAs with the convenience of Python.

Learn more about VTA [here](https://tvm.apache.org/docs/vta/index.html).