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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).
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.
The main features are about displaying information about the SoC, CPU, screen, battery, temperature, WI-FI and cellular network, Android properties, GPU details, other listings of devices (PCI, sensors etc.) and a listing of installed apps, codecs and system directories. A version for the Android Wear platform is also available. [8]
MSI Afterburner is a graphics card overclocking (OC) and monitoring utility that allows users to monitor and adjust various settings of their graphics card. [2] Developed by MSI (Micro-Star International) and previously Alexey Nicolaychuk, developer of RivaTuner, it is widely used for enhancing the performance of graphics cards, especially in gaming and high-performance tasks.
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.
Different software is used by different motherboards. There are also third-party programs that work on a variety of motherboards and allow wide customization of fan behavior depending on temperature readings from the motherboard, CPU, and GPU sensors, as well as allowing manual control. Two such programs are SpeedFan [11] and Argus Monitor. [12]
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.
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