Installing HIP SDK

On Windows, in addition to installing the GPU driver, you need to install the HIP SDK. Choose one of the two options below:

✅ Automatic installation
✅ Stable and supported by AMD
❌ Older code
❌ No Machine Learning support (PyTorch and TensorFlow will not work)

Installation

1. Visit the AMD HIP SDK for Windows website
2. Download the latest version for your OS
3. Run the installer and follow the on-screen instructions

❌ Manual installation
❌ Unstable and unsupported by AMD
✅ Newer code
✅ Machine Learning support (required for PyTorch, TensorFlow, etc.)

Installation

1. Visit the ROCm SDK nightly tarballs website
2. Download a recent therock-dist-windows-gfx<GPUARCH>...tar.gz file:
   • If you don't know your <GPUARCH>, check the TechPowerUp GPU database. Example: for AMD Radeon RX 9070, the <GPUARCH> (Shader ISA) is 1201
   • Alternatively, download any tar.gz file, unpack it and run the included hipInfo.exe to determine your <GPUARCH> (gcnArchName)
3. Extract the .tar.gz file to a directory of your choice (you can use 7-Zip)
   • Note: You may need to extract twice (first the .tar.gz, then the .tar file)
4. Set the HIP_PATH environment variable to the extracted directory path (instructions here)
   • The directory must contain a bin subdirectory
   • The bin directory must contain various .dll files, including rocblas.dll

Verification

ZLUDA includes a small CUDA application that tests the loading and initialization of all performance libraries. Run it using:

zluda.exe -- cuda_check.exe

The output should look like this:

nvcuda    : OK (C:\hip_sdk\bin\amdhip64_7.dll)
nvml      : OK
cufft11   : OK
cudnn9    : OK (C:\hip_sdk\bin\MIOpen.dll)
cudnn8    : OK (C:\hip_sdk\bin\MIOpen.dll)
cublaslt13: OK (C:\hip_sdk\bin\libhipblaslt.dll)
cusparse12: OK
cufft12   : OK
cublas13  : OK (C:\hip_sdk\bin\rocblas.dll)
cublaslt12: OK (C:\hip_sdk\bin\libhipblaslt.dll)
cublas12  : OK (C:\hip_sdk\bin\rocblas.dll)
cusparse11: OK

The path in parentheses is the path to the underlying HIP SDK library.

Caveats and Known Issues:

• The path shown in parentheses indicates the underlying HIP SDK library, but is not guaranteed to be used. If an application loads the library from a different path before loading ZLUDA, ZLUDA will use the already-loaded library instead
• cuda_check.exe may sometimes hang and not close due to a bug in MIOpen
• When using the official HIP SDK, cuda_check.exe will fail to load cudnn8 and cudnn9 because the official SDK does not include MIOpen