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General-purpose computing on graphics processing units (GPGPU, or less often GPGP) is the use of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU).
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.
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.
A like for like comparison between desktop CPUs and GPGPUs is problematic because of algorithmic & structural differences. For example, a 2.66 GHz Intel Core 2 Duo can perform a maximum of 25 GFLOPs (25 billion single-precision floating-point operations per second) if optimally using SSE and streaming memory access so the prefetcher works perfectly.
GPU scheduler GPU memory management in-kernel Remote Desktop Linux Linux framebuffer (fbdev) / Direct Rendering Manager: Kernel Mode Setting: VGA Switcheroo [76] DRM sched [77] DMA-BUF: No Windows NT kernel Dxgkrnl.sys VidPN Manager in Dxgkrnl.sys [78]? VidSch in Dxgkrnl [79] VidMm in Dxgkrnl.sys, Dxgmms1.sys, and Dxgmms2.sys [80] RdpDD.sys ...
The Compute pipeline is a type of graphics pipeline used for dispatching and executing compute shaders. Compute pipelines are run through compute command lists, which are restricted to recording only copy and compute commands. Compute shaders are used for general-purpose algorithms and computations, and are run through parallel processors on
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
A cryptographic accelerator card allows cryptographic operations to be performed at a faster rate.. Hardware acceleration is the use of computer hardware designed to perform specific functions more efficiently when compared to software running on a general-purpose central processing unit (CPU).