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Build system fix.
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Christophe Van Gysel committed Apr 5, 2018
1 parent c391bbc commit 9f4ba7c
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1 change: 1 addition & 0 deletions CMakeLists.txt
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Expand Up @@ -51,6 +51,7 @@ set(CUDA_SEPARABLE_COMPILATION ON)
SET(INCLUDE_DIRS
"${gtest_SOURCE_DIR}/include"
"${gmock_SOURCE_DIR}/include"
"${cnmem_SOURCE_DIR}/include"
${CUDA_TOOLKIT_ROOT_DIR}/samples/common/inc
${GLOG_INCLUDE_DIRS}
${GTEST_INCLUDE_DIRS}
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7 changes: 3 additions & 4 deletions README.md
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Expand Up @@ -8,11 +8,10 @@ Requirements & installation

To build the library and manage dependencies, we use [CMake](https://cmake.org/) (version 3.5 and higher). In addition, we rely on the following libraries:

* [CUDA](https://developer.nvidia.com/cuda-zone) (version 8 and higher preferred),
* [glog](https://github.com/google/glog) (version 0.3.4 and higher), and
* [cnmem](https://github.com/NVIDIA/cnmem).
* [CUDA](https://developer.nvidia.com/cuda-zone) (version 8 and higher preferred), and
* [glog](https://github.com/google/glog) (version 0.3.4 and higher).

The tests are implemented using the [googletest and googlemock](https://github.com/google/googletest) frameworks, which CMake will fetch and compile automatically as part of the build pipeline. Finally, you need a CUDA-compatible GPU in order to perform any computations.
The [cnmem](https://github.com/NVIDIA/cnmem) library is used for memory management. The tests are implemented using the [googletest and googlemock](https://github.com/google/googletest) frameworks. CMake will fetch and compile these libraries automatically as part of the build pipeline. Finally, you need a CUDA-compatible GPU in order to perform any computations.

To install `device_matrix`, the following instructions should get you started.

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