TheRock/rocm-systems/projects/hip/docs/faq.rst

.. meta::
  :description: This page lists frequently asked questions about HIP
  :keywords: AMD, ROCm, HIP, FAQ, frequently asked questions

*******************************************************************************
Frequently asked questions
*******************************************************************************

This topic provides answers to frequently asked questions from new HIP users and
users familiar with NVIDIA CUDA.

HIP support
===========

What hardware does HIP support?
-------------------------------

HIP supports AMD GPUs. See
:ref:`prerequisites of the install guide<install_prerequisites>` for detailed
information.

What operating systems does HIP support?
----------------------------------------

Linux as well as Windows are supported by ROCm. The exact versions are listed in
the system requirements for :ref:`rocm-install-on-linux:supported_distributions`
and :ref:`rocm-install-on-windows:supported-skus-win`.

.. note::
   Not all HIP runtime API functions are yet supported on Windows.
   A note is added to those functions' documentation in the
   :ref:`HIP runtime API reference<runtime_api_reference>`.

What libraries does HIP provide?
--------------------------------

HIP provides key math and AI libraries. See :doc:`rocm:reference/api-libraries`
for the full list.

What CUDA features can be ported to HIP?
-----------------------------------------------

The :doc:`NVIDIA CUDA runtime API supported by HIP<hipify:reference/tables/CUDA_Runtime_API_functions_supported_by_HIP>`
and :doc:`NVIDIA CUDA driver API supported by HIP<hipify:reference/tables/CUDA_Driver_API_functions_supported_by_HIP>`
pages describe which CUDA APIs can be automatically converted to HIP equivalents.
The :ref:`HIP runtime API reference<runtime_api_reference>` describes each HIP API and
its limitations, if any, compared with the equivalent CUDA API.

The kernel language features are documented in the
:doc:`/how-to/hip_cpp_language_extensions` page.

Relation to other GPGPU frameworks
==================================

How easy is it to port CUDA code to HIP?
-----------------------------------------------

The `HIPIFY <https://github.com/ROCm/HIPIFY>`_ tools can automatically convert
almost all CUDA runtime code to HIP. Most device code needs no additional
conversion because HIP and CUDA have the same signatures for math and built-in
functions except for the name. Once ported to HIP, code can be optimized for AMD GPU
architectures.

Additional porting might be required to deal with architecture feature
queries or CUDA capabilities that HIP doesn't support.

To better understand the syntax differences, see :doc:`CUDA to HIP API Function Comparison <reference/api_syntax>`
or the :doc:`HIP porting guide <how-to/hip_porting_guide>`.

Compiler related questions
==========================

How to use HIP-Clang to build HIP programs?
-------------------------------------------

:doc:`hipcc <hipcc:index>` is a compiler driver. This means it is not a compiler
but calls the appropriate compiler and sets some options.

The underlying compiler is :doc:`amdclang++ <llvm-project:index>`,
and can be called directly.

What is HIP-Clang?
------------------

HIP-Clang is a Clang/LLVM-based compiler used to compile HIP programs for AMD
platforms. The executable is named :doc:`amdclang++ <llvm-project:index>` on
Linux and ``clang++`` on Windows.

Can I link HIP device code with host code compiled with another compiler such as gcc, icc, or clang?
----------------------------------------------------------------------------------------------------

Yes. HIP generates object code that conforms to the GCC ABI, and links with libstdc++.
This means you can compile host code with the compiler of your choice and link the
generated host object code with device code.

Can HIP applications be compiled with a C compiler?
---------------------------------------------------

HIP is a C/C++ API that can be used with C compilers. However, this applies only
to the API itself. Device code and the syntax for calling kernels must be
compiled with a supported compiler like :doc:`hipcc <hipcc:index>`. The code
objects that are generated with ``hipcc`` can, however, be used with a C
compiler, as shown in the code examples below.

The following is the HIP device code, assumed to be saved in ``device.hip``:

.. code-block:: c++

  #include <hip/hip_runtime.h>

  __global__ void kernel(double* array, size_t size){
      const int x = threadIdx.x + blockIdx.x * blockDim.x;
      if(x < size){array[x] = x;}
  };

  extern "C"{
      hipError_t callKernel(int blocks, int threadsPerBlock, double* array, size_t size){
          kernel<<<blocks, threadsPerBlock, 0, hipStreamDefault>>>(array, size);
          return hipGetLastError();
      }
  }

The following is the host code, written in C, saved in ``host.c``:

.. code-block:: c

  #include <hip/hip_runtime_api.h>
  #include <stdio.h>
  #include <stdlib.h>

  #define HIP_CHECK(c) {                                \
     if (c != hipSuccess){                              \
        printf("HIP Error : %s", hipGetErrorString(c)); \
        printf(" %s %d\n", __FILE__, __LINE__);         \
        exit(c);                                        \
     }                                                  \
  }

  // Forward declaration - the implementation needs to be compiled with
  // a device compiler like hipcc or amdclang++
  hipError_t callKernel(int blocks, int threadsPerBlock, double* array, size_t size);

  int main(int argc, char** argv) {
      int blocks = 1024;
      int threadsPerBlock = 256;
      size_t arraySize = blocks * threadsPerBlock;
      double* d_array;
      double* h_array;
      h_array = (double*)malloc(arraySize * sizeof(double));

      HIP_CHECK(hipMalloc((void**)&d_array, arraySize * sizeof(double)));
      HIP_CHECK(callKernel(blocks, threadsPerBlock, d_array, arraySize));
      HIP_CHECK(hipMemcpy(h_array, d_array, arraySize * sizeof(double), hipMemcpyDeviceToHost));
      HIP_CHECK(hipFree(d_array));

      free(h_array);
      return 0;
  }

These files are then compiled and linked using

.. code-block:: shell

  hipcc -c device.hip
  gcc host.c device.o $(hipconfig --cpp_config) -L/opt/rocm/lib -lamdhip64

assuming the default installation of ROCm in ``/opt/rocm``.

How to guard code specific to the host or the GPU?
--------------------------------------------------

The compiler defines the ``__HIP_DEVICE_COMPILE__`` macro only when compiling
device code.

Refer to the :doc:`how-to/hip_porting_guide` for more information.