Provides a comprehensive environment for C/C++ developers building GPU-accelerated applications.
Directives for parallel computing, is a new open parallel programming standard designed to enable all scientific and technical programmers.
Accelerate applications on GPU platforms by adding compiler directives to existing code.
Compile and optimize their CUDA applications to run on x86-based workstations, servers and clusters.
Enjoy GPU acceleration directly from your Fortran program using CUDA Fortran from The Portland Group.
Enables acceleration on your GPU or multi-core processor using Python.
Gives you access to CUDA fuctionality from your Python code.
An advanced productivity tool that generates vectorized C++ (AVX) and CUDA C code from .NET assemblies (MSIL) or Java archives (bytecode)
OpenCL is a low-level API for GPU computing that can run on CUDA-powered GPUs.
This is a novel approach to develop GPU applications on .NET, combining the CUDA with Microsoft’s F#.