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CUDA is a parallel computing platform and programming model that higher level languages can use to exploit parallelism. In CUDA, the kernel is executed with the aid of threads. The thread is an abstract entity that represents the execution of the kernel. A kernel is a function that compiles to run on a special device. Multi threaded ...
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 , it allows the allocation of one or more CUDA-enabled GPUs to a single application. Each GPU can be part of a cluster or running inside of a virtual machine. The ...
The memory protection is based on the fact that OS running on the CPU (see figure) exclusively controls both the MMU and the IOMMU. The devices are physically unable to circumvent or corrupt configured memory management tables. In virtualization, guest operating systems can use hardware that is not specifically made for virtualization. Higher ...
In computing, CUDA (Compute Unified Device Architecture) 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.
OptiX is a high-level, or "to-the-algorithm" API, meaning that it is designed to encapsulate the entire algorithm of which ray tracing is a part, not just the ray tracing itself. This is meant to allow the OptiX engine to execute the larger algorithm with great flexibility without application-side changes.
In 2008, BOINC's website announced that Nvidia had developed a language called CUDA that uses GPUs for scientific computing. With NVIDIA's assistance, several BOINC-based projects (e.g., MilkyWay@home. SETI@home) developed applications that run on NVIDIA GPUs using CUDA.
A BFG Physx card. PhysX is an open-source [1] realtime physics engine middleware SDK developed by Nvidia as part of the Nvidia GameWorks software suite.. Initially, video games supporting PhysX were meant to be accelerated by PhysX PPU (expansion cards designed by Ageia).