Skip to content

@a127a127 a127a127 released this Mar 11, 2019 · 57 commits to master since this release

Release Note

New Features

  • NVDLA Backend

    • The first open-source compiler backend that supports NVIDIA Deep Learning Accelerator (NVDLA)

    • Initial release of nv_full hardwre configuration support

    • Support status for the models in the ONNX model zoo - ONNC can compile 6 models and run on NVDLA virtual platform successfully. 2 models are not supported by nv_full configuration. The other 4 models need support for more operators.

      Models Official NVDLA compiler ONNC compiler
      bvlc_alexnet O O
      bvlc_googlenet X O
      bvlc_reference_caffenet O O
      bvlc_reference_rcnn_ilsvrc13 O O
      densenet121 X Need more operator support
      inception_v1 X O
      inception_v2 X Need more operator support
      resnet50 O O
      shufflenet X Need more operator support
      squeezenet X Need more operator support
      vgg19 X nv_full can not support this model
      zfnet512 X nv_full can not support this model
  • Framework Support

    • Interpreter Interface - Target backend now can write a customized interpreter.
    • Vanilla Backend - A template for porting a new backend
    • Statistic API
  • Tools

    • ONNI
      • Add more verbose level for debugging or benchmarking (level 1 to 4)
      • Add flag --dry-run : Do not do the inference, just print statistics.
      • Add flag --onnx-opt: Enable onnx optimizer.
      • Add flag -fLinearScanAlgo=<string>: Select linear scan algorithm: first-fit, best-fit. (default is first-fit)
      • Add flag --enable-x86-fuse-conv-relu: Enable x86 fuse conv relu.
  • Documentation

Assets 2
You can’t perform that action at this time.