@@ -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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-
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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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-
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## Get and run
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Run the following commands in the command shell to download the repository,
@@ -127,6 +119,14 @@ $ sh ./scripts/tests_run_all.sh
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> $ export CUDAHOSTCXX=/usr/bin/g++-8
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> ` ` `
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+ # # Python Wrapper
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+
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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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+
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# # Directory structure
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` ` `
@@ -241,12 +241,8 @@ int main() {
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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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-
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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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