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Open, Modular, Deep Learning Accelerator

Home Page: https://tvm.apache.org/

License: Apache License 2.0

CMake 0.42% Makefile 3.57% Scala 43.54% Python 5.95% C++ 24.20% Verilog 3.98% Tcl 9.97% C 6.56% Shell 1.81%
tvm vta tensor hardware machine-learning

tvm-vta's Introduction

VTA Hardware Design Stack

Build Status

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.

tvm-vta's People

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