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ROCm [3] is an Advanced Micro Devices (AMD) software stack for graphics processing unit (GPU) programming. ROCm spans several domains: general-purpose computing on graphics processing units (GPGPU), high performance computing (HPC), heterogeneous computing.
To be used efficiently, all computer software needs certain hardware components or other software resources to be present on a computer. [1] These prerequisites are known as (computer) system requirements and are often used as a guideline as opposed to an absolute rule. Most software defines two sets of system requirements: minimum and recommended.
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.
The intention is to facilitate language evolution and provide a more natural ability to leverage GPU compute capabilities, in line with hardware developments such as Unified Memory Architecture and Heterogeneous System Architecture. This allows closer cooperation between a CPU and GPU.
(system memory) 8:8:4 2 4 Up to 512 from system memory 6.4 12.8 DDR2 64 128 28.8 10.0 3.3 n/a n/a Unknown The block of decoding of HD-video PureVideo HD is disconnected GeForce 8200 mGPU [44] Unknown Unknown gt Unknown PureVideo 3 with VP3 GeForce 8300 mGPU [44] Unknown Unknown 1500 Up to 512 from system memory 36 Unknown GeForce ...
TechPowerUp GPU-Z (or just GPU-Z) is a lightweight utility designed to provide information about video cards and GPUs. [2] The program displays the specifications of Graphics Processing Unit (often shortened to GPU) and its memory; also displays temperature, core frequency, memory frequency, GPU load and fan speeds.
Alea GPU, [20] created by QuantAlea, [21] introduces native GPU computing capabilities for the Microsoft .NET languages F# [22] and C#. Alea GPU also provides a simplified GPU programming model based on GPU parallel-for and parallel aggregate using delegates and automatic memory management. [23]
A GART is used as a means of data exchange between the main memory and video memory through which buffers (i.e. paging/swapping) of textures, polygon meshes and other data are loaded, but can also be used to expand the amount of video memory available for systems with only integrated or shared graphics (i.e. no discrete or inbuilt graphics ...