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Historically, CPUs have used hardware-managed caches, but the earlier GPUs only provided software-managed local memories. However, as GPUs are being increasingly used for general-purpose applications, state-of-the-art GPUs are being designed with hardware-managed multi-level caches which have helped the GPUs to move towards mainstream computing.
In 2006, Nvidia's GPU had a 4x performance advantage over other CPUs. In 2018 the Nvidia GPU was 20 times faster than a comparable CPU node: the GPUs were 1.7x faster each year. Moore's law would predict a doubling every two years, however Nvidia's GPU performance was more than tripled every two years, fulfilling Huang's law. [5]
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.
A GPU cluster is a computer cluster in which each node is equipped with a graphics processing unit (GPU). By harnessing the computational power of modern GPUs via general-purpose computing on graphics processing units (GPGPU), very fast calculations can be performed with a GPU cluster. Titan, the first supercomputer to use GPUs
ROCm is free, libre and open-source software (except the GPU firmware blobs [4]), and it is distributed under various licenses. ROCm initially stood for Radeon Open Compute platfor m ; however, due to Open Compute being a registered trademark, ROCm is no longer an acronym — it is simply AMD's open-source stack designed for GPU compute.
API multi-GPU instead allows the API to intelligently split the workload among two or more completely different GPUs. [41] For example, integrated GPUs included on the CPU can be used in conjunction with a high-end dedicated GPU for a slight performance boost. On March 7, 2018, Vulkan 1.1 was released by the Khronos Group. [42]
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The SIMT execution model has been implemented on several GPUs and is relevant for general-purpose computing on graphics processing units (GPGPU), e.g. some supercomputers combine CPUs with GPUs. The processors, say a number p of them, seem to execute many more than p tasks.