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The Cg dialect has only ever had one compiler, in the form of Nvidia's Cg toolkit. Microsoft has released two compilers for HLSL. The original compiler was the closed-source FXC (Effect Compiler), supported until 2015. It was deprecated in favor of the open-source LLVM-based DXC (DirectXShaderCompiler) with support for newer HLSL features. [21]
C/C++ programmers can use 'CUDA C/C++', compiled to PTX with nvcc, Nvidia's LLVM-based C/C++ compiler, or by clang itself. [9] Fortran programmers can use 'CUDA Fortran', compiled with the PGI CUDA Fortran compiler from The Portland Group. [needs update] Python programmers can use the cuNumeric library to accelerate applications on Nvidia GPUs.
CUDA code runs on both the central processing unit (CPU) and graphics processing unit (GPU). NVCC separates these two parts and sends host code (the part of code which will be run on the CPU) to a C compiler like GNU Compiler Collection (GCC) or Intel C++ Compiler (ICC) or Microsoft Visual C++ Compiler, and sends the device code (the part which will run on the GPU) to the GPU.
ROCm [3] is an Advanced Micro Devices (AMD) software stack for graphics processing unit (GPU) programming. ROCm spans several domains: general-purpose computing on graphics processing units (GPGPU), high performance computing (HPC), heterogeneous computing.
C++ Accelerated Massive Parallelism (C++ AMP) is a native programming model that contains elements that span the C++ programming language and its runtime library. It provides an easy way to write programs that compile and execute on data-parallel hardware, such as graphics cards ( GPUs ).
Intel oneAPI DPC++/C++ Compiler is available for Windows and Linux and supports compiling C, C++, SYCL, and Data Parallel C++ (DPC++) source, targeting Intel IA-32, Intel 64 (aka x86-64), Core, Xeon, and Xeon Scalable processors, as well as GPUs including Intel Processor Graphics Gen9 and above, Intel X e architecture, and Intel Programmable Acceleration Card with Intel Arria 10 GX FPGA. [5]
The ability to write shaders that can be used on any hardware vendor's graphics card that supports the OpenGL Shading Language. Each hardware vendor includes the GLSL compiler in their driver, thus allowing each vendor to create code optimized for their particular graphics card’s architecture.
As in OpenMP, the programmer can annotate C, C++ and Fortran source code to identify the areas that should be accelerated using compiler directives and additional functions. [2] Like OpenMP 4.0 and newer, OpenACC can target both the CPU and GPU architectures and launch computational code on them.