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://docs.tvm.ai/vta/index.html).