hipify-clang#

hipify-clang is a Clang-based tool for translating CUDA sources into HIP sources.

It translates CUDA source into an abstract syntax tree (AST), which is traversed by transformation matchers. After applying all the matchers, the output HIP source is produced.

Advantages:

  • hipify-clang is a translator; any complex constructs will be parsed successfully, or an error will be reported.

  • It supports Clang options like -I, -D, and –cuda-path.

  • There’s seamless support of new CUDA versions, as the Clang front-end is statically linked into hipify-clang and does all the syntactical parsing of a CUDA source to HIPIFY.

  • There’s ease of support as a compiler extension.

Disadvantages:

  • You must ensure the input CUDA code is correct; incorrect code will not be translated to HIP.

  • CUDA should be installed and provided in case of multiple installations by --cuda-path option.

  • All the includes and defines should be provided to transform code successfully.

Dependencies#

hipify-clang requires:

LLVM release version

Latest supported CUDA version

Windows

Linux

3.8.01, 3.8.11, 3.9.01, 3.9.11

7.5

+

+

4.0.0, 4.0.1, 5.0.0, 5.0.1, 5.0.2

8.0

+

+

6.0.0, 6.0.1

9.0

+

+

7.0.0, 7.0.1, 7.1.0

9.2

works only with patch (Clang bug 38811)

not working (Clang bug 36384)

8.0.0, 8.0.1

10.0

works only with patch (Clang bug 38811)

+

9.0.0, 9.0.1

10.1

+

+

10.0.0, 10.0.1

11.0.0

+

+

10.0.0, 10.0.1

11.0.1, 11.1.0, 11.1.1

works only with patch (Clang bug 47332)
works only with patch (Clang bug 47332)

11.0.0

11.0.0

+

+

11.0.0

11.0.1, 11.1.0, 11.1.1

works only with patch (Clang bug 47332)
works only with patch (Clang bug 47332)

11.0.1, 11.1.0

11.2.2

+

+

12.0.0, 12.0.1, 13.0.0, 13.0.1

11.5.1

+

+

14.0.0, 14.0.1, 14.0.2, 14.0.3, 14.0.4

11.7.1

+

14.0.5, 14.0.6, 15.0.0, 15.0.1, 15.0.2, 15.0.3, 15.0.4, 15.0.5, 15.0.6, 15.0.7

11.8.0

+

+

16.0.0, 16.0.1, 16.0.2, 16.0.3, 16.0.4, 16.0.5, 16.0.6

12.2.2

+

+

17.0.1, 17.0.2, 17.0.3, 17.0.4, 17.0.5, 17.0.6, 18.1.0, 18.1.1, 18.1.24

12.3.24

LATEST STABLE CONFIG

LATEST STABLE CONFIG

19.0.0 git

12.3.2

+

+

1 LLVM 3.x is no longer supported (but might still work).

2 Download the patch and unpack it into your LLVM distributive directory; a few header files will be overwritten. You don’t need to rebuild LLVM.

3 Download the patch and unpack it into your LLVM source directory; the Cuda.cpp file will be overwritten. You’ll need to rebuild LLVM.

4 Represents the latest supported and recommended configuration.

In most cases, you can get a suitable version of LLVM+Clang with your package manager.

Failing that or having multiple versions of LLVM, you can download a release archive, build or install it, and set CMAKE_PREFIX_PATH so CMake can find it. For instance: -DCMAKE_PREFIX_PATH=D:\LLVM\18.1.2\dist

Usage#

To process a file, hipify-clang needs access to the same headers that would be required to compile it with Clang. For example:

./hipify-clang square.cu --cuda-path=/usr/local/cuda-12.3 -I /usr/local/cuda-12.3/samples/common/inc

hipify-clang arguments are given first, followed by a separator (--), and then the arguments you’d pass to Clang if you were compiling the input file. For example:

./hipify-clang cpp17.cu --cuda-path=/usr/local/cuda-12.3 -- -std=c++17

hipify-clang also supports the hipification of multiple files that might be specified in a single command line with absolute or relative paths. For example:

./hipify-clang cpp17.cu ../../square.cu /home/user/cuda/intro.cu --cuda-path=/usr/local/cuda-12.3 -- -std=c++17

To use a specific version of LLVM during hipification, the hipify-clang option --clang-resource-directory= must be specified to point to the Clang resource directory, which is the parent directory for the include folder that contains __clang_cuda_runtime_wrapper.h and other header files used during the hipification process. For example:

./hipify-clang square.cu --cuda-path=/usr/local/cuda-12.3 --clang-resource-directory=/usr/llvm/18.1.2/dist/lib/clang/18

The Clang manual for compiling CUDA may be useful.

Using JSON compilation database#

For some hipification automation (starting from Clang 8.0.0), it is also possible to provide a Compilation Database in JSON format in the compile_commands.json file:

-p <folder containing compile_commands.json> or
-p=<folder containing compile_commands.json>

The compilation database should be provided in the compile_commands.json file or generated by Clang based on CMake; multiple source files can be specified as well.

Only Clang options must be provided in the compile_commands.json file; hipify-clang options can only be provided in the hipify-clang command line.

Note

Do not use the options separator --. A compilation error will occur if the hipify-clang options are provided before the separator.

Here’s an example of the compile_commands.json usage:

[
  {
    "directory": "<test dir>",
    "command": "hipify-clang \"<CUDA dir>\" -I./include -v",
    "file": "cd_intro.cu"
  }
]

Hipification statistics#

The options --print-stats and --print-stats-csv help show an overall picture of what is hipified and what is not, and obtain the hipification statistics. For example:

hipify-clang intro.cu -cuda-path="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.3.2" --print-stats
[HIPIFY] info: file 'intro.cu' statistics:
CONVERTED refs count: 40
UNCONVERTED refs count: 0
CONVERSION %: 100.0
REPLACED bytes: 604
[HIPIFY] info: file 'intro.cu' statistics:
  CONVERTED refs count: 40
  UNCONVERTED refs count: 0
  CONVERSION %: 100.0
  REPLACED bytes: 604
  TOTAL bytes: 5794
  CHANGED lines of code: 34
  TOTAL lines of code: 174
  CODE CHANGED (in bytes) %: 10.4
  CODE CHANGED (in lines) %: 19.5
  TIME ELAPSED s: 0.41
[HIPIFY] info: CONVERTED refs by type:
  error: 2
  device: 2
  memory: 16
  event: 9
  thread: 1
  include_cuda_main_header: 1
  type: 2
  numeric_literal: 7
[HIPIFY] info: CONVERTED refs by API:
  CUDA Driver API: 1
  CUDA RT API: 39
[HIPIFY] info: CONVERTED refs by names:
  cuda.h: 1
  cudaDeviceReset: 1
  cudaError_t: 1
  cudaEventCreate: 2
  cudaEventElapsedTime: 1
  cudaEventRecord: 3
  cudaEventSynchronize: 3
  cudaEvent_t: 1
  cudaFree: 4
  cudaFreeHost: 3
  cudaGetDeviceCount: 1
  cudaGetErrorString: 1
  cudaGetLastError: 1
  cudaMalloc: 3
  cudaMemcpy: 6
  cudaMemcpyDeviceToHost: 3
  cudaMemcpyHostToDevice: 3
  cudaSuccess: 1
  cudaThreadSynchronize: 1
hipify-clang intro.cu -cuda-path="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.3.2" --print-stats-csv

The generated file with statistics is intro.cu.csv:

list of stats

In the case of multiple source files, the statistics will be provided per file and in total.

For a list of hipify-clang options, run hipify-clang --help.

Building hipify-clang#

Once you’ve cloned the HIPIFY repository (git clone https://github.com/ROCm/HIPIFY.git), you must run the following commands from the HIPIFY root folder.

cd .. \
mkdir build dist \
cd build

cmake \
-DCMAKE_INSTALL_PREFIX=../dist \
-DCMAKE_BUILD_TYPE=Release \
../hipify

make -j install

Having not found or multiple LLVM instances, the root folder with the LLVM distributive must be specified in the CMake command line to build hipify-clang. For example:

-DCMAKE_PREFIX_PATH=/usr/llvm/18.1.2/dist

On Windows, the following option should be specified for CMake in the first place: -G "Visual Studio 17 2022". The generated hipify-clang.sln should be built by Visual Studio 17 2022 instead of Make. See Windows testing for the supported tools for building.

Debug build type -DCMAKE_BUILD_TYPE=Debug is supported and tested. LLVM+Clang should be built in debug mode.

64-bit build mode (-Thost=x64 on Windows) is also supported. LLVM+Clang should be built in 64-bit mode.

You can find the binary at ./dist/hipify-clang or at the folder specified by the -DCMAKE_INSTALL_PREFIX option.

Testing hipify-clang#

hipify-clang has unit tests using LLVM lit/FileCheck.

LLVM+Clang should be built from sources, as pre-built binaries are not exhaustive for testing. Before building, ensure that the software required for building is of an appropriate version.

LLVM <= 9.0.1#

  1. Download LLVM + Clang sources

  2. Build LLVM+Clang:

    cd .. \
    mkdir build dist \
    cd build
    

    Linux:

    cmake \
      -DCMAKE_INSTALL_PREFIX=../dist \
      -DLLVM_SOURCE_DIR=../llvm \
      -DLLVM_TARGETS_TO_BUILD="X86;NVPTX" \
      -DLLVM_INCLUDE_TESTS=OFF \
      -DCMAKE_BUILD_TYPE=Release \
      ../llvm
    make -j install
    

    Windows:

    cmake \
      -G "Visual Studio 16 2019" \
      -A x64 \
      -Thost=x64 \
      -DCMAKE_INSTALL_PREFIX=../dist \
      -DLLVM_SOURCE_DIR=../llvm \
      -DLLVM_TARGETS_TO_BUILD="NVPTX" \
      -DLLVM_INCLUDE_TESTS=OFF \
      -DCMAKE_BUILD_TYPE=Release \
      ../llvm
    

    Run Visual Studio 16 2019, open the generated LLVM.sln, build all, and build the INSTALL project.

LLVM >= 10.0.0#

  1. Download LLVM project sources.

  2. Build LLVM project:

    cd .. \
    mkdir build dist \
    cd build
    

    Linux:

    cmake \
      -DCMAKE_INSTALL_PREFIX=../dist \
      -DLLVM_TARGETS_TO_BUILD="" \
      -DLLVM_ENABLE_PROJECTS="clang" \
      -DLLVM_INCLUDE_TESTS=OFF \
      -DCMAKE_BUILD_TYPE=Release \
      ../llvm-project/llvm
    make -j install
    

    Windows:

    cmake \
      -G "Visual Studio 17 2022" \
      -A x64 \
      -Thost=x64 \
      -DCMAKE_INSTALL_PREFIX=../dist \
      -DLLVM_TARGETS_TO_BUILD="" \
      -DLLVM_ENABLE_PROJECTS="clang" \
      -DLLVM_INCLUDE_TESTS=OFF \
      -DCMAKE_BUILD_TYPE=Release \
      ../llvm-project/llvm
    

    Run Visual Studio 17 2022, open the generated LLVM.sln, build all, build project INSTALL.

  3. Ensure you’ve installed CUDA version 7.0 or greater.

    • Having multiple CUDA installations to choose a particular version, you must specify the DCUDA_TOOLKIT_ROOT_DIR option:

      Linux:

      -DCUDA_TOOLKIT_ROOT_DIR=/usr/include
      

      Windows:

      -DCUDA_TOOLKIT_ROOT_DIR="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.3"
      
      -DCUDA_SDK_ROOT_DIR="C:/ProgramData/NVIDIA Corporation/CUDA Samples/v12.3"
      
  4. Ensure cuDNN of the version corresponding to CUDA version is installed.

    • Specify the path to cuDNN using the CUDA_DNN_ROOT_DIR option:

      Linux:

      -DCUDA_DNN_ROOT_DIR=/usr/include
      

      Windows:

      -DCUDA_DNN_ROOT_DIR=D:/CUDA/cuDNN/8.9.7
      
  5. Ensure CUB of the version corresponding to CUDA version is installed.

    • Path to CUB should be specified by the CUDA_CUB_ROOT_DIR option:

      Linux:

      -DCUDA_CUB_ROOT_DIR=/srv/git/CUB
      

      Windows:

      -DCUDA_CUB_ROOT_DIR=D:/CUDA/CUB/cub-2.1.0
      
  6. Ensure Python version 2.7 or greater is installed.

  7. Ensure lit and FileCheck are installed; these are distributed with LLVM.

    • Install lit into Python:

      Linux:

      python /usr/llvm/18.1.2/llvm-project/llvm/utils/lit/setup.py install
      

      Windows:

      python D:/LLVM/18.1.2/llvm-project/llvm/utils/lit/setup.py install
      

      In case of errors similar to ModuleNotFoundError: No module named 'setuptools', upgrade the setuptools package:

      ``python -m pip install --upgrade pip setuptools``
      
    • Starting with LLVM 6.0.1, specify the path to the llvm-lit Python script using the LLVM_EXTERNAL_LIT option:

      Linux:

      -DLLVM_EXTERNAL_LIT=/usr/llvm/18.1.2/build/bin/llvm-lit
      

      Windows:

      -DLLVM_EXTERNAL_LIT=D:/LLVM/18.1.2/build/Release/bin/llvm-lit.py
      
    • FileCheck:

      Linux:

      Copy from /usr/llvm/18.1.2/build/bin/ to CMAKE_INSTALL_PREFIX/dist/bin.

      Windows:

      Copy from D:/LLVM/18.1.2/build/Release/bin to CMAKE_INSTALL_PREFIX/dist/bin.

      Alternatively, specify the path to FileCheck in the CMAKE_INSTALL_PREFIX option.

  8. To run OpenGL tests successfully on:

    Linux:

    Install GL headers (on Ubuntu, use: sudo apt-get install mesa-common-dev)

    Windows:

    There’s nothing to do; all the required headers are shipped with the Windows SDK.

  9. Set the HIPIFY_CLANG_TESTS option to ON: -DHIPIFY_CLANG_TESTS=ON

  10. Build and run tests.

Linux testing#

On Linux, the following configurations are tested:

  • Ubuntu 14: LLVM 4.0.0 - 7.1.0, CUDA 7.0 - 9.0, cuDNN 5.0.5 - 7.6.5

  • Ubuntu 16-19: LLVM 8.0.0 - 14.0.6, CUDA 7.0 - 10.2, cuDNN 5.1.10 - 8.0.5

  • Ubuntu 20-21: LLVM 9.0.0 - 18.1.2, CUDA 7.0 - 12.3.2, cuDNN 5.1.10 - 8.9.7

  • Ubuntu 22-23: LLVM 13.0.0 - 18.1.2, CUDA 7.0 - 12.3.2, cuDNN 8.0.5 - 8.9.7

Minimum build system requirements for the above configurations:

  • CMake 3.16.8, GNU C/C++ 9.2, Python 2.7.

Recommended build system requirements:

  • CMake 3.28.3, GNU C/C++ 13.2, Python 3.12.2.

Here’s an example of building hipify-clang` with testing support on ``Ubuntu 23.10.01:

cmake
-DHIPIFY_CLANG_TESTS=ON \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_INSTALL_PREFIX=../dist \
-DCMAKE_PREFIX_PATH=/usr/llvm/18.1.2/dist \
-DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-12.3.2 \
-DCUDA_DNN_ROOT_DIR=/usr/local/cudnn-8.9.7 \
-DCUDA_CUB_ROOT_DIR=/usr/local/cub-2.1.0 \
-DLLVM_EXTERNAL_LIT=/usr/llvm/18.1.2/build/bin/llvm-lit \
../hipify

The corresponding successful output is:

-- The C compiler identification is GNU 13.2.0
-- The CXX compiler identification is GNU 13.2.0
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working C compiler: /usr/bin/cc - skipped
-- Detecting C compile features
-- Detecting C compile features - done
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: /usr/bin/c++ - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- HIPIFY config:
--    - Build hipify-clang : ON
--    - Test  hipify-clang : ON
--    - Is part of HIP SDK : OFF
-- Found ZLIB: /usr/lib/x86_64-linux-gnu/libz.so (found version "1.2.13")
-- Found LLVM 18.1.2:
--    - CMake module path  : /usr/llvm/18.1.2/dist/lib/cmake/llvm
--    - Clang include path : /usr/llvm/18.1.2/dist/include
--    - LLVM Include path  : /usr/llvm/18.1.2/dist/include
--    - Binary path        : /usr/llvm/18.1.2/dist/bin
-- Linker detection: GNU ld
-- ---- The below configuring for hipify-clang testing only ----
-- Found Python: /usr/bin/python3.12 (found version "3.12.2") found components: Interpreter
-- Found lit: /usr/local/bin/lit
-- Found FileCheck: /GIT/LLVM/trunk/dist/FileCheck
-- Initial CUDA to configure:
--    - CUDA Toolkit path  : /usr/local/cuda-12.3.2
--    - CUDA Samples path  : OFF
--    - cuDNN path         : /usr/local/cudnn-8.9.7
--    - CUB path           : /usr/local/cub-2.1.0
-- Found CUDAToolkit: /usr/local/cuda-12.3.2/targets/x86_64-linux/include (found version "12.3.107")
-- Performing Test CMAKE_HAVE_LIBC_PTHREAD
-- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Success
-- Found Threads: TRUE
-- Found CUDA config:
--    - CUDA Toolkit path  : /usr/local/cuda-12.3.2
--    - CUDA Samples path  : OFF
--    - cuDNN path         : /usr/local/cudnn-8.9.7
--    - CUB path           : /usr/local/cub-2.1.0
-- Configuring done (0.5s)
-- Generating done (0.0s)
-- Build files have been written to: /usr/hipify/build
make test-hipify

The corresponding successful output is:

Running HIPify regression tests
===============================================================
CUDA 12.3.107 - will be used for testing
LLVM 18.1.2 - will be used for testing
x86_64 - Platform architecture
Linux 6.5.0-15-generic - Platform OS
64 - hipify-clang binary bitness
64 - python 3.12.2 binary bitness
===============================================================
-- Testing: 102 tests, 12 threads --
Testing Time: 6.70s

Total Discovered Tests: 102
  Passed: 102 (100.00%)

Windows testing#

Tested configurations:

LLVM

CUDA

cuDNN

Visual Studio

CMake

Python

4.0.0 - 5.0.2

7.0 - 8.0

5.1.10 - 7.1.4

2015.14.0, 2017.15.5.2

3.5.1  - 3.18.0

3.6.4 - 3.8.5

6.0.0 - 6.0.1

7.0 - 9.0

7.0.5  - 7.6.5

2015.14.0, 2017.15.5.5

3.6.0  - 3.18.0

3.7.2 - 3.8.5

7.0.0 - 7.1.0

7.0 - 9.2

7.0.5  - 7.6.5

2017.15.9.11

3.13.3 - 3.18.0

3.7.3 - 3.8.5

8.0.0 - 8.0.1

7.0 - 10.0

7.6.5

2017.15.9.15

3.14.2 - 3.18.0

3.7.4 - 3.8.5

9.0.0 - 9.0.1

7.0 - 10.1

7.6.5

2017.15.9.20, 2019.16.4.5

3.16.4 - 3.18.0

3.8.0 - 3.8.5

10.0.0 - 11.0.0

7.0 - 11.1

7.6.5  - 8.0.5

2017.15.9.30, 2019.16.8.3

3.19.2

3.9.1

11.0.1 - 11.1.0

7.0 - 11.2.2

7.6.5  - 8.0.5

2017.15.9.31, 2019.16.8.4

3.19.3

3.9.2

12.0.0 - 13.0.1

7.0 - 11.5.1

7.6.5  - 8.3.2

2017.15.9.43, 2019.16.11.9

3.22.2

3.10.2

14.0.0 - 14.0.6

7.0 - 11.7.1

8.0.5  - 8.4.1

2017.15.9.57,5 2019.16.11.17, 2022.17.2.6

3.24.0

3.10.6

15.0.0 - 15.0.7

7.0 - 11.8.0

8.0.5  - 8.8.1

2019.16.11.25, 2022.17.5.2

3.26.0

3.11.2

16.0.0 - 16.0.6

7.0 - 12.2.2

8.0.5  - 8.9.5

2019.16.11.29, 2022.17.7.1

3.27.3

3.11.4

17.0.16 - 18.1.27

7.0 - 12.3.2

8.0.5  - 8.9.7

2019.16.11.34, 2022.17.9.5

3.29.0

3.12.2

19.0.0git

7.0 - 12.3.2

8.0.5  - 8.9.7

2019.16.11.34, 2022.17.9.5

3.29.0

3.12.2

5 LLVM 14.x.x is the latest major release supporting Visual Studio 2017.

To build LLVM 14.x.x correctly by Visual Studio 2017, -DLLVM_FORCE_USE_OLD_TOOLCHAIN=ON should be added to a corresponding CMake command line.

LLVM < 14.x.x can be built correctly by Visual Studio 2017 without the LLVM_FORCE_USE_OLD_TOOLCHAIN option.

6 Note that LLVM 17.0.0 was withdrawn due to an issue; please use 17.0.1 or newer instead.

7 Note that LLVM 18.0.0 has never been released; please use 18.1.0 or newer instead.

Building with testing support by Visual Studio 17 2022 on Windows 11:

cmake
-G "Visual Studio 17 2022" \
-A x64 \
-Thost=x64 \
-DHIPIFY_CLANG_TESTS=ON \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_INSTALL_PREFIX=../dist \
-DCMAKE_PREFIX_PATH=D:/LLVM/18.1.2/dist \
-DCUDA_TOOLKIT_ROOT_DIR="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.3" \
-DCUDA_SDK_ROOT_DIR="C:/ProgramData/NVIDIA Corporation/CUDA Samples/v12.3" \
-DCUDA_DNN_ROOT_DIR=D:/CUDA/cuDNN/8.9.7 \
-DCUDA_CUB_ROOT_DIR=D:/CUDA/CUB/cub-2.1.0 \
-DLLVM_EXTERNAL_LIT=D:/LLVM/18.1.2/build/Release/bin/llvm-lit.py \
../hipify

The corresponding successful output is:

-- Selecting Windows SDK version 10.0.22621.0 to target Windows 10.0.22631.
-- The C compiler identification is MSVC 19.39.33523.0
-- The CXX compiler identification is MSVC 19.39.33523.0
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working C compiler: C:/Program Files/Microsoft Visual Studio/2022/Community/VC/Tools/MSVC/14.39.33519/bin/Hostx64/x64/cl.exe - skipped
-- Detecting C compile features
-- Detecting C compile features - done
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: C:/Program Files/Microsoft Visual Studio/2022/Community/VC/Tools/MSVC/14.39.33519/bin/Hostx64/x64/cl.exe - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- HIPIFY config:
--    - Build hipify-clang : ON
--    - Test  hipify-clang : ON
--    - Is part of HIP SDK : OFF
-- Found LLVM 18.1.2:
--    - CMake module path  : D:/LLVM/18.1.2/dist/lib/cmake/llvm
--    - Clang include path : D:/LLVM/18.1.2/dist/include
--    - LLVM Include path  : D:/LLVM/18.1.2/dist/include
--    - Binary path        : D:/LLVM/18.1.2/dist/bin
-- ---- The below configuring for hipify-clang testing only ----
-- Found Python: C:/Users/TT/AppData/Local/Programs/Python/Python312/python.exe (found version "3.12.2") found components: Interpreter
-- Found lit: C:/Users/TT/AppData/Local/Programs/Python/Python312/Scripts/lit.exe
-- Found FileCheck: D:/LLVM/18.1.2/dist/bin/FileCheck.exe
-- Initial CUDA to configure:
--    - CUDA Toolkit path  : C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.3
--    - CUDA Samples path  : C:/ProgramData/NVIDIA Corporation/CUDA Samples/v12.3
--    - cuDNN path         : D:/CUDA/cuDNN/8.9.7
--    - CUB path           : D:/CUDA/CUB/cub-2.1.0
-- Found CUDAToolkit: C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.3/include (found version "12.3.107")
-- Found CUDA config:
--    - CUDA Toolkit path  : C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.3
--    - CUDA Samples path  : C:/ProgramData/NVIDIA Corporation/CUDA Samples/v12.3
--    - cuDNN path         : D:/CUDA/cuDNN/8.9.7
--    - CUB path           : D:/CUDA/CUB/cub-2.1.0
-- Configuring done (1.4s)
-- Generating done (0.1s)
-- Build files have been written to: D:/HIPIFY/build

Run Visual Studio 17 2022, open the generated hipify-clang.sln, and build the project test-hipify.