NVIDIA GPU Ampere generation or later (compute capability >= 80)
You can follow the standard TVM installation flow. Because auto-pipelining feature requires changes to TVM source, you need to build TVM from source following the instructions.
You can follow the steps below, and refer to https://tvm.apache.org/docs/install/from_source.html and https://tvm.apache.org/docs/install/from_source.html#python-package-installation for trouble-shooting. If you encounter errors, please file an issue.
Key steps
# start from an NVIDIA docker
docker run -it --gpus all -v /path/to/this/repo:/tvm -w /tvm nvidia/cuda:11.4.0-cudnn8-devel-ubuntu20.04 bash
# inside the docker, install all the dependencies
apt-get update
apt-get install -y python3 python3-pip python3-dev python3-setuptools gcc libtinfo-dev zlib1g-dev build-essential cmake libedit-dev libxml2-dev git llvm
pip install numpy decorator attrs tornado psutil 'xgboost>=1.1.0' cloudpickle matplotlib torch pytest
# create build directory
mkdir build
cp cmake/config.cmake.template build/config.cmake
# build the TVM shared library
cd build
cmake ..
make -j8
# expose the TVM python directory to PYTHONPATH
export TVM_HOME=/tvm
export PYTHONPATH=$TVM_HOME/python:${PYTHONPATH}
We prepare a docker image where everything is installed and you can directly start running the following steps. The image is build just using the scripts in the previous part.
docker run -it --gpus all -w /tvm hguyue1/alcop:latest bash
# inside the docker
export TVM_HOME=/tvm
export PYTHONPATH=$TVM_HOME/python:${PYTHONPATH} # to use tvm python package
The source code is in /tvm of the docker image. Environment variable TVM_HOME is also set to /tvm.
cd ${TVM_HOME}/auto_pipeline_exp/single_op
python3 dense_tensorcore_in_topi.py # baseline
python3 dense_tensorcore_autopipeline_example.py # optimizedcd ${TVM_HOME}/auto_pipeline_exp/single_op
sh run.sh- TOPI template with support for pipelining and shared memory swizzling: tvm/python/tvm/topi/exp_cuda/*
- Auto-pipelining program transformation pass: tvm/python/tvm/contrib/auto_pipeline.py
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