Add c++ and python local deploy example (#5)

* add deploy example

* fix pylint complain and add more information into readme.

* Test deploy in xilinx FPGA board and udpate ReadMe.md

* Fix python deploy bug.

* add synset support and fix error report

* add bitstream flash logic

* address review comments.

* add bitstream flash file

* change file name

* fix plint complain

* return once no input parameter
8 files changed
tree: e40003a08cbe23f1a66d6e64b4db80ffa3f8a14d
  1. apps/
  2. config/
  3. hardware/
  4. include/
  5. src/
  6. tests/
  7. .asf.yaml
  8. .gitignore
  9. Jenkinsfile
  10. LICENSE
  11. NOTICE
  12. README.md
README.md

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.