hipify-clang#

hipify-clang is a Clang-based tool for translating NVIDIA 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. It parses complex constructs successfully or else reports an error.

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

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

  • It is very well supported as a compiler extension.

Disadvantages:

  • You must ensure that the input CUDA code is correct as incorrect code can’t be translated to HIP.

  • You must install CUDA and in case of multiple installations, specify using --cuda-path option.

  • You must provide all the includes and defines to successfully translate the code.

Dependencies#

hipify-clang requires:

LLVM release version

Latest supported CUDA version

Windows

Linux

3.8.0 1, 3.8.1 1, 3.9.0 1, 3.9.1 1

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 due to Clang bug 38811 patch for 7.0.0 2 patch for 7.0.1 2 patch for 7.1.0 2

❌ due to Clang bug 36384

8.0.0, 8.0.1

10.0

Works only with patch due to Clang bug 38811 patch for 8.0.0 2 patch for 8.0.1 2

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 due to Clang bug 47332 patch for 10.0.0 3 patch for 10.0.1 3

Works only with patch due to Clang bug 47332 patch for 10.0.0 3 patch for 10.0.1 3

11.0.0

11.0.0

11.0.0

11.0.1, 11.1.0, 11.1.1

Works only with patch due to Clang bug 47332 patch for 11.0.0 3

Works only with patch due to Clang bug 47332 patch for 11.0.0 3

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

Works only with patch due to Clang bug 54609 patch for 14.0.0 2 patch for 14.0.1 2 patch for 14.0.2 2 patch for 14.0.3 2 patch for 14.0.4 2

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, 18.1.2, 18.1.3, 18.1.4, 18.1.5, 18.1.6, 18.1.7, 18.1.8 4

12.3.2 4

Latest stable config

Latest stable config

19.0.0 git

12.5.1

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

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

3 Download the patch and unpack it into your LLVM source directory. This overwrites the Cuda.cpp file. You 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. However, you can also download a release archive and build or install it. In case of multiple versions of LLVM installed, set CMAKE_PREFIX_PATH so that CMake can find the desired version of LLVM. For example, -DCMAKE_PREFIX_PATH=D:\LLVM\18.1.8\dist.

Usage#

To process a file, hipify-clang needs access to the same headers that are required to compile it with Clang:

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

hipify-clang arguments are supplied first, followed by a separator -- and the arguments to be passed to Clang for compiling the input file:

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

hipify-clang also supports the hipification of multiple files that can be specified in a single command with absolute or relative paths:

./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, specify the hipify-clang option --clang-resource-directory= 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:

./hipify-clang square.cu --cuda-path=/usr/local/cuda-12.3 --clang-resource-directory=/usr/llvm/18.1.8/dist/lib/clang/18

For more information, refer to the Clang manual for compiling CUDA.

Using JSON compilation database#

For some hipification automation (starting from Clang 8.0.0), you can also 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>

You can provide the compilation database in the compile_commands.json file or generate using Clang based on CMake. You can specify multiple source files as well.

To provide Clang options, use compile_commands.json file, whereas to provide hipify-clang options, use hipify-clang command line.

Note

Don’t use the options separator -- to avoid compilation error caused due to the hipify-clang options being provided before the separator.

Here’s an example demonstrating 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 provide an overview of what is hipified and what is not, and the hipification statistics:

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

This generates intro.cu.csv file with statistics:

list of stats

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

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

Building hipify-clang#

After cloning the HIPIFY repository (git clone https://github.com/ROCm/HIPIFY.git), 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

To ensure LLVM being found or in case of multiple LLVM instances, specify the path to the root folder containing the LLVM distributive:

-DCMAKE_PREFIX_PATH=/usr/llvm/18.1.8/dist

On Windows, specify the following option for CMake in the first place: -G "Visual Studio 17 2022". Build the generated hipify-clang.sln using Visual Studio 17 2022 instead of Make. See Windows testing for the supported tools for building.

As debug build type -DCMAKE_BUILD_TYPE=Debug is supported and tested, it is recommended to build LLVM+Clang in debug mode.

Also, 64-bit build mode (-Thost=x64 on Windows) is supported, hence it is recommended to build LLVM+Clang 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 is equipped with unit tests using LLVM lit or FileCheck.

Build LLVM+Clang from sources, as prebuilt binaries are not exhaustive for testing. Before building, ensure that the software required for building belongs to 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
    
  3. 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, and build project INSTALL.

  3. Install CUDA version 7.0 or greater.

    • In case of multiple CUDA installations, specify the particular version using 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. Install cuDNN belonging to the version corresponding to the CUDA version:

    • To specify the path to cuDNN, use the CUDA_DNN_ROOT_DIR option:

      Linux:

      -DCUDA_DNN_ROOT_DIR=/usr/include
      

      Windows:

      -DCUDA_DNN_ROOT_DIR=D:/CUDA/cuDNN/9.2.1
      
  5. [Optional] Install CUB 1.9.8 for CUDA < 11.0 only; for CUDA >= 11.0, the CUB shipped with CUDA will be used for testing.

    • To specify the path to CUB, use the CUDA_CUB_ROOT_DIR option (only for CUDA < 11.0):

      Linux:

      -DCUDA_CUB_ROOT_DIR=/srv/git/CUB
      

      Windows:

      -DCUDA_CUB_ROOT_DIR=D:/CUDA/CUB
      
  6. Install Python version 2.7 or greater.

  7. Install lit and FileCheck; these are distributed with LLVM.

    • Install lit into Python:

      Linux:

      python /usr/llvm/18.1.8/llvm-project/llvm/utils/lit/setup.py install
      

      Windows:

      python D:/LLVM/18.1.8/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/18.1.8/build/bin/llvm-lit
      

      Windows:

      -DLLVM_EXTERNAL_LIT=D:/LLVM/18.1.8/build/Release/bin/llvm-lit.py
      
    • FileCheck:

      Linux:

      Copy from /usr/llvm/18.1.8/build/bin/ to CMAKE_INSTALL_PREFIX/dist/bin.

      Windows:

      Copy from D:/LLVM/18.1.8/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:

    No installation required. 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 - 18.1.8, CUDA 7.0 - 12.3.2, cuDNN 5.1.10 - 9.2.1

  • Ubuntu 22-23: LLVM 13.0.0 - 18.1.8, CUDA 7.0 - 12.3.2, cuDNN 8.0.5 - 9.2.1

Minimum build system requirements for the above configurations:

  • CMake 3.16.8, GNU C/C++ 9.2, Python 3.0.

Recommended build system requirements:

  • CMake 3.30.0, GNU C/C++ 13.2, Python 3.12.4.

Here’s how to build 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/18.1.8/dist \
-DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-12.3.2 \
-DCUDA_DNN_ROOT_DIR=/usr/local/cudnn-9.2.1 \
-DLLVM_EXTERNAL_LIT=/usr/llvm/18.1.8/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 18.1.8:
--    - CMake module path  : /usr/llvm/18.1.8/dist/lib/cmake/llvm
--    - Clang include path : /usr/llvm/18.1.8/dist/include
--    - LLVM Include path  : /usr/llvm/18.1.8/dist/include
--    - Binary path        : /usr/llvm/18.1.8/dist/bin
-- Linker detection: GNU ld
-- ---- The below configuring for hipify-clang testing only ----
-- Found Python: /usr/bin/python3.12 (found version "3.12.4") 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  :
--    - cuDNN path         : /usr/local/cudnn-9.2.1
--    - CUB path           :
-- 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-9.2.1
--    - CUB path           : /usr/local/cuda-12.3.2/include/cub
-- 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 18.1.8 - will be used for testing
x86_64 - Platform architecture
Linux 6.5.0-15-generic - Platform OS
64 - hipify-clang binary bitness
64 - python 3.12.4 binary bitness
===============================================================
-- Testing: 106 tests, 12 threads --
Testing Time: 6.91s

Total Discovered Tests: 106
  Passed: 106 (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

17.0.1 6 - 18.1.8 7

7.0 - 12.3.2

8.0.5  - 9.2.1

2019.16.11.37, 2022.17.10.4

3.30.0

3.12.4

19.0.0git

7.0 - 12.5.1

8.0.5  - 9.2.1

2019.16.11.37, 2022.17.10.4

3.30.0

3.12.4

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

To build LLVM 14.x.x correctly using Visual Studio 2017, add -DLLVM_FORCE_USE_OLD_TOOLCHAIN=ON to corresponding CMake command line.

You can also build LLVM < 14.x.x correctly using Visual Studio 2017 without the LLVM_FORCE_USE_OLD_TOOLCHAIN option.

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

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

Building with testing support using 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/18.1.8/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/9.2.1 \
-DLLVM_EXTERNAL_LIT=D:/LLVM/18.1.8/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 18.1.8:
--    - CMake module path  : D:/LLVM/18.1.8/dist/lib/cmake/llvm
--    - Clang include path : D:/LLVM/18.1.8/dist/include
--    - LLVM Include path  : D:/LLVM/18.1.8/dist/include
--    - Binary path        : D:/LLVM/18.1.8/dist/bin
-- ---- The below configuring for hipify-clang testing only ----
-- Found Python: C:/Users/TT/AppData/Local/Programs/Python/Python312/python.exe (found version "3.12.4") found components: Interpreter
-- Found lit: C:/Users/TT/AppData/Local/Programs/Python/Python312/Scripts/lit.exe
-- Found FileCheck: D:/LLVM/18.1.8/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/9.2.1
--    - CUB path           :
-- 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/9.2.1
--    - CUB path           : C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.3/include/cub
-- 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.