GPU computing

GPU computing

The use of GPU and CPU to do compute-intensive assignments faster than conventional CPUs

GPU computing is the use of graphics processing units (GPU) and central processing units (CPU) to perform scientific calculations, engineering computation, and the processing of large volumes of data. GPUs have massive-parallel architecture. By using GPUs, the completion of computationally intensive assignments that benefit from parallel computation is faster compared with conventional central processing units (CPUs).

GPU computing is recognized for having enormous potential in other fields such as medical imaging. Due to the increased clock speeds now present in modern GPUs coupled with optimized parallel architectures, computer scientists and researchers have begun using GPU computing for some high performance computing (HPC) that was traditionally performed by a CPU utilizing specialized chips known as general-purpose computing on graphics processing units (GPGPU).

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GPU Computing

John D. Owens, Mike Houston, David Luebke, Simon Green, John E. Stone and James C. Phillips

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By Ryan Morrison For Mailonline
March 16, 2020
Mail Online
The 'Fold@Home' technology involves users downloading an app for their PC hat runs in the background, letting it use any processing power they're not using.
Bob O'Donnell
October 22, 2019
TechSpot
The concept of putting more computing power closer to where applications are occurring, commonly referred as "edge computing", has been talked about for a long time. After all, it makes logical sense to put resources nearer to where they're actually...
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