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In computing, CUDA is a proprietary [1] 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.
Forward compatibility or upward compatibility is a design characteristic that allows a system to accept input intended for a later version of itself. The concept can be applied to entire systems, electrical interfaces , telecommunication signals , data communication protocols , file formats , and programming languages .
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.
rCUDA, which stands for Remote CUDA, is a type of middleware software framework for remote GPU virtualization. Fully compatible with the CUDA application programming interface ( API ), it allows the allocation of one or more CUDA-enabled GPUs to a single application.
Forward compatibility for mono receivers with stereo signals was achieved by sending the sum of both left and right audio channels in one signal and the difference in another signal. That allows mono FM receivers to receive and decode the sum signal while ignoring the difference signal, which is necessary only for separating the audio channels.
Even on similar systems, the details of implementing a compatibility layer can be quite intricate and troublesome; a good example is the IRIX binary compatibility layer in the MIPS architecture version of NetBSD. [25] A compatibility layer requires the host system's CPU to be (upwardly) compatible to that of the foreign
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3]
A flag day, as used in system administration, is a change which requires a complete restart or conversion of a sizable body of software or data.The change is large and expensive, and—in the event of failure—similarly difficult and expensive to reverse.