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README.md

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What Is AKG

AKG(Auto Kernel Generator) is an optimizer for operators in Deep Learning Networks. It provides the ability to automatically fuse ops with specific patterns. AKG works with MindSpore-GraphKernel to improve the performance of networks running on different hardware backends.

AKG composes with four basic optimization module, normalization, auto schedule, instruction emit and backend optimization.

  • normalization. In order to solve the limitation in expression ability of polyhedral(which can only process static linear programs), the computation IR needs to be normalized first. The mainly optimization of normalization module includes auto-inline, loop partition, common subexpression elimination and so on.

  • auto schedule. Base on polyhedral technology, the auto schedule module mainly have auto-vectorization, auto-tiling, dependency analysis and memory promotion.

  • instruction emit. The instruction emitting module has the optimization about loop normalization, auto pragma and emit instruction.

  • backend optimization. The backend optimization module consists of double buffer optimization, storage rewrite optimization and inject sync optimization.

Hardware Backends Support

At present, Ascend910 and GPU V100/A100 are supported. More Backends are on the list.

Build

Build With MindSpore

See MindSpore README.md for details.

Build Standalone

We suggest you build and run akg together with MindSpore. And we also provide a way to run case in standalone mode for convenience sake. Refer to MindSpore Installation for more information about compilation dependencies.

bash build.sh -t $target // target can set 'gpu' or 'ascend'

Run Standalone

  1. Set Environment
  • Ascend910
    cd tests
    source ./test_env.sh amd64
    export RUNTIME_MODE='air_cloud'
    export PATH=${PATH}:${YOUR_CCEC_COMPILER_PATH}
  • GPU V100/A100
    cd tests
    source ./test_env.sh gpu
  1. Run test
  • Ascend910
    cd tests/operators/vector
    pytest -s test_abs_001.py -m "level0" # run level0 testcases
  • GPU V100/A100
    cd tests/operators/gpu
    python3 test_all.py -s "op_name" #replace op_name with the operator name which you want to test

Contributing

Welcome contributions. See MindSpore Contributor Wiki for more details.

Release Notes

The release notes, see our RELEASE.

License

Apache License 2.0

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AKG(Auto Kernel Generator) is an optimizer for operators in Deep Learning Networks, which provides the ability to automatically fuse ops with specific patterns. spread retract
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