Search results
Results from the WOW.Com Content Network
CUDA operates on a heterogeneous programming model which is used to run host device application programs. It has an execution model that is similar to OpenCL. In this model, we start executing an application on the host device which is usually a CPU core. The device is a throughput oriented device, i.e., a GPU core which performs parallel ...
The Nvidia CUDA Compiler (NVCC) translates code written in CUDA, a C++-like language, into PTX instructions (an assembly language represented as American Standard Code for Information Interchange text), and the graphics driver contains a compiler which translates PTX instructions into executable binary code, [2] which can run on the processing ...
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.
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 ...
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.
Components of a GPU. A graphics processing unit (GPU) is a specialized electronic circuit initially designed for digital image processing and to accelerate computer graphics, being present either as a discrete video card or embedded on motherboards, mobile phones, personal computers, workstations, and game consoles.
Due to a trend of increasing power of mobile GPUs, general-purpose programming became available also on the mobile devices running major mobile operating systems. Google Android 4.2 enabled running RenderScript code on the mobile device GPU. [25]
Modern GPU designs are mainly based on the SIMD (Single Instruction Multiple Data) computation paradigm. [2] [3] This type of GPU devices is so-called general-purpose GPUs (GPGPUs). GPGPUs are able to perform an operation on multiple independent data concurrently with their vector or SIMD functional units.