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In computing, CUDA is a proprietary [2] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on 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.
The Quadro line of GPU cards emerged in an effort towards market segmentation by Nvidia. [citation needed] In introducing Quadro, Nvidia was able to charge a premium for essentially the same graphics hardware in professional markets, and direct resources to properly serve the needs of those markets.
The page "3D Settings" » "Configure SLI, Surround, PhysX" in the Nvidia Control panel and the CUDA sample application "simpleP2P" use such APIs to realize their services in respect to their NVLink features. On the Linux platform, the command line application with sub-command "nvidia-smi nvlink" provides a similar set of advanced information ...
The number of threads in a block is limited, but grids can be used for computations that require a large number of thread blocks to operate in parallel and to use all available multiprocessors. CUDA is a parallel computing platform and programming model that higher level languages can use to exploit parallelism.
Oracle Application Server 10g was the first platform designed for grid computing, providing full lifecycle support for SOA. This platform allows for the efficient management and deployment of applications across a distributed computing environment, making it a robust solution for enterprise-level applications.
Free and open-source drivers support a large portion (but not all) of the features available in GeForce-branded cards. For example, as of January 2014 [update] nouveau driver lacks support for the GPU and memory clock frequency adjustments, and for associated dynamic power management. [ 62 ]