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[Project] Minor readme fixes
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README.md

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@@ -94,14 +94,6 @@ if you want to build library from the command line only.
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- [CUDA Hello world program](https://developer.nvidia.com/blog/easy-introduction-cuda-c-and-c/)
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- [CUDA CMake tutorial](https://developer.nvidia.com/blog/building-cuda-applications-cmake/)
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## Python Setup
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After the build process, the shared library object `libcubool.so` is placed
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inside the build directory. Export into the environment or add into bash
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profile the variable `CUBOOL_PATH=/path/to/the/libcubool.so` with appropriate
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path to your setup. Then you will be able to use `pycubool` python wrapper,
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which uses this variable in order to located library object.
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## Get and run
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Run the following commands in the command shell to download the repository,
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> $ export CUDAHOSTCXX=/usr/bin/g++-8
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> ```
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## Python Wrapper
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After the build process, the shared library object `libcubool.so` is placed
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inside the build directory. Export into the environment or add into bash
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profile the variable `CUBOOL_PATH=/path/to/the/libcubool.so` with appropriate
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path to your setup. Then you will be able to use `pycubool` python wrapper,
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which uses this variable in order to located library object.
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## Directory structure
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```
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CuBoolInstanceDesc desc{};
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desc.memoryType = CUBOOL_GPU_MEMORY_TYPE_GENERIC;
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status = CuBool_Instance_New(&desc, &I);
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if (status == CUBOOL_STATUS_DEVICE_NOT_PRESENT) {
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/* System does not provide Cuda compatible device */
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return 1;
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}
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/* System may not provide Cuda compatible device */
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CHECK(CuBool_Instance_New(&desc, &I));
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/* Input graph G */
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