Comments (1)
Not just loop tiles, Ansor should be tuning such as unroll、block tile、vectorize and the implementation of the kernel(for many kernels, decide which kernels can be fused). but Ansor still lacks the ability of tensorize, So does not perform well on computationally intensive operators such as gemm and conv.
The above are just some rough instructions. if you want more detailed information, We recommend you to view the source code.
Tune config in TPAT
Tvm Source Code
cuda kernel code from tvm is just auto tuning from for loop tile? what is cuda kernel code tuning arguments in TVM Ansor?
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Related Issues (20)
- RandomNormal not supported for frontend ONNX HOT 1
- Support CUDA 11.5 and TensorRT 8.2.1.3? HOT 1
- 无法跑通 example HOT 1
- Support for dynamic shape ? HOT 2
- No radical Subgraph optimization for TensorRT HOT 1
- precision for one hot plugin is wrong HOT 2
- Is maintained of this repo? HOT 1
- Fail to run example test_onehot_dynamic_direct.py HOT 12
- Half model error HOT 8
- Error when running one_hot example HOT 6
- support for one hot plugin with dynamic axis other than batch_size dim HOT 4
- Is there a talk or article about of the implementation of this project? HOT 1
- unsupported ptx version error
- out of memeory HOT 2
- so build succeed, tensorrt run error HOT 6
- Could you provide simple tutorial on how to run onnx_to_plugin for simple operator? HOT 4
- KeyError int8 HOT 1
- so build succeed, tensorrt run error one hot example HOT 11
- 好久不维护了吗?
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