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Copy file name to clipboardExpand all lines: README.md
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@@ -85,6 +85,13 @@ If all requirements are satisfied, run the following command to install PyPI pac
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$ python3 -m pip install pycubool
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```
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### Documentation
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The following links give a brief start guide for new users:
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-[C API example](https://github.com/JetBrains-Research/cuBool/blob/master/docs/examples/transitive_closure_cpp.md) - complete C++ application to compute transitive closure of an example graph
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-[Python API usage](https://github.com/JetBrains-Research/cuBool/blob/master/docs/examples/python_examples.md) - complete and detailed set of the python API usage examples for all lib features
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## Getting started
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This section gives instructions to build the library from sources.
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> without cuda backend support.
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Before the CUDA setup process, validate your system NVIDIA driver with `nvidia-smi`
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command. if it is need, install required driver via `ubuntu-drivers devices` and
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command. Install required driver via `ubuntu-drivers devices` and
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`apt install <driver>` commands respectively.
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The following commands grubs the required GCC compilers for the CC and CXX compiling
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├── python - pycubool related sources
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│ ├── pycubool - cubool library wrapper for python (similar to pygraphblas)
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│ ├── tests - regression tests for python wrapper
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│ ├── examples - short script files with python api usage examples
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│ └── data - generate data for pycubool regression tests
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