Port to the latest stable Chisel release (#33)

* modernize build.sbt

* fix some imports

* ignore target directory generated by sbt

* TensorGemm: explicitly define adder interface

* use ChiselStage instead of Driver

* setResource is now addResource

* add toInt in order to fix warning
11 files changed
tree: abf8ba5a9b2a8e7d19cb6c79b4dce0836ae07c78
  1. apps/
  2. config/
  3. hardware/
  4. include/
  5. src/
  6. tests/
  7. .asf.yaml
  8. .gitignore
  9. Jenkinsfile
  11. NOTICE
  12. 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.