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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 was created by Nvidia in 2006. [3]
This number is generally used as a maximum throughput number for the GPU and generally, a higher fill rate corresponds to a more powerful (and faster) GPU. Memory subsection. Bandwidth – Maximum theoretical bandwidth for the processor at factory clock with factory bus width. GHz = 10 9 Hz. Bus type – Type of memory bus or buses used.
Nvidia claims a 128 CUDA core SMM has 86% of the performance of a 192 CUDA core SMX. [9] Also, each Graphics Processing Cluster, or GPC, contains up to 4 SMX units in Kepler, and up to 5 SMM units in first generation Maxwell. [9] GM107 supports CUDA Compute Capability 5.0 compared to 3.5 on GK110/GK208 GPUs and 3.0 on GK10x GPUs. Dynamic ...
The computations are offloaded to the GPUs through either the low-level or the high-level API introduced with CUDA. CUDA is only available for Nvidia's graphics products. Nvidia OptiX is part of Nvidia GameWorks. OptiX is a high-level, or "to-the-algorithm" API, meaning that it is designed to encapsulate the entire algorithm of which ray ...
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.
Nvidia RTX (also known as Nvidia GeForce RTX under the GeForce brand) is a professional visual computing platform created by Nvidia, primarily used in workstations for designing complex large-scale models in architecture and product design, scientific visualization, energy exploration, and film and video production, as well as being used in mainstream PCs for gaming.
Model – The marketing name for the GPU assigned by AMD/ATI. Note that ATI trademarks have been replaced by AMD trademarks starting with the Radeon HD 6000 series for desktop and AMD FirePro series for professional graphics. Codename – The internal engineering codename for the GPU. Launch – Date of release for the GPU.
Before CUDA was published in 2007, GPGPU was "classical" and involved repurposing graphics primitives. A standard structure of such was: Load arrays into textures; Draw a quadrangle; Apply pixel shaders and textures to quadrangle; Read out pixel values in the quadrangle as array; More examples are available in part 4 of GPU Gems 2. [35]