Add hipfort

compat.yml

@@ -34,7 +34,7 @@ vendors:
       C:
         nvidiahip: indirectok
       F:
-        hipfortran: nope
+        nvidiahipfortran: nope
     SYCL:
       C:
         nvidiasycl: nonvendorok
@@ -84,7 +84,7 @@ vendors:
       C:
         amdhipc: fullok 
       F:
-        hipfortran: nope 
+        nvidiahipfortran: nope 
     SYCL:
       C:
         amdsyclc: indirectok
@@ -130,7 +130,7 @@ vendors:
       C:
         intelhipc: somesupport
       F:
-        hipfortran: nope
+        intelhipfortran: nope
     SYCL:
       C:
         intelsyclc: fullok
@@ -168,7 +168,7 @@ descriptions:
   cudac: "CUDA C/C++ is supported on NVIDIA GPUs through the <a href='https://developer.nvidia.com/cuda-toolkit'>CUDA Toolkit</a>"
   cudafortran: "CUDA Fortran, a proprietary Fortran extension, is supported on NVIDIA GPUs via the <a href='https://developer.nvidia.com/hpc-sdk'>NVIDIA HPC SDK</a>"
   nvidiahip: "<a href='https://github.com/ROCm-Developer-Tools/HIP'>HIP</a> programs can directly use NVIDIA GPUs via a CUDA backend; HIP is maintained by AMD"
-  hipfortran: "No such thing like HIP for Fortran"
+  nvidiahipfortran: "No such thing like HIP for Fortran, but AMD offers Fortran interfaces to HIP and ROCm libraries in <a href='https://github.com/ROCmSoftwarePlatform/hipfort'>hipfort</a>"
   nvidiasycl: 'SYCL can be used on NVIDIA GPUs with <em>experimental</em> support either in 
               <a href="https://github.com/codeplaysoftware/sycl-for-cuda/blob/cuda/sycl/doc/GetStartedWithSYCLCompiler.md#build-sycl-toolchain-with-support-for-nvidia-cuda">SYCL</a> directly or in <a href="https://github.com/intel/llvm/blob/sycl/sycl/doc/GetStartedGuide.md#build-dpc-toolchain-with-support-for-nvidia-cuda">DPC++</a>, 
               or via <a href="https://github.com/illuhad/hipSYCL">hipSYCL</a>'
@@ -199,6 +199,7 @@ descriptions:
   intelcudac: "<a href='https://github.com/oneapi-src/SYCLomatic'>SYCLomatic</a> translates CUDA code to SYCL code, allowing it to run on Intel GPUs; also, Intel's <a href='https://www.intel.com/content/www/us/en/developer/tools/oneapi/dpc-compatibility-tool.html'>DPC++ Compatibility Tool</a> can transform CUDA to SYCL"
   intelcudafortran: "No direct support, only via ISO C bindings, but at least an example can be <a href='https://github.com/codeplaysoftware/SYCL-For-CUDA-Examples/tree/master/examples/fortran_interface'>found on GitHub</a>; it's pretty scarce and not by Intel itself, though"
   intelhipc: "<a href='https://github.com/CHIP-SPV/chip-spv'>CHIP-SPV</a> supports mapping CUDA and HIP to OpenCL and Intel's Level Zero, making it run on Intel GPUs"
+  intelhipfortran: "No such thing like HIP for Fortran"
   intelsyclc: "<a href='https://www.khronos.org/sycl/'>SYCL</a> is the prime programming model for Intel GPUs; actually, SYCL is only a standard, while Intel's implementation of it is called <a href='https://www.intel.com/content/www/us/en/developer/tools/oneapi/data-parallel-c-plus-plus.html'>DPC++</a> (<em>Data Parallel C++</em>), which extends the SYCL standard in various places; actually actually, Intel namespaces everything <em>oneAPI</em> these days, so the <em>full</em> proper name is Intel oneAPI DPC++ (which incorporates a C++ compiler and also a library)"
   intelopenacc: "OpenACC can be used on Intel GPUs by translating the code to OpenMP with <a href='https://github.com/intel/intel-application-migration-tool-for-openacc-to-openmp'>Intel's Source-to-Source translator</a>"
   intelopenmp: "Intel has <a href='https://www.intel.com/content/www/us/en/develop/documentation/get-started-with-cpp-fortran-compiler-openmp/top.html'>extensive support for OpenMP</a> through their latest compilers"