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GPU computing

GPU computing

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

All edits by  Joshua Holley 

Edits on 10 Mar, 2018
Joshua Holley"Fixed a few grammatical issues and clarified/expanded a few points"
Joshua Holley edited on 10 Mar, 2018
Edits made to:
Article (+280/-71 characters)

GPU computing is the use of graphics processing unitunits (GPU) and central processing unitunits (CPU) to perform scientific calculations, engineering computingcomputation, 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 offor having enormous potential in other fields such as medical imaging. ComputerDue to the increased clock speeds now present in modern GPUs coupled with optimized parallel architectures, computer scientists and researchers arehave nowbegun using GPU computing asfor some high performance computing (HPC) forthat generalwas purposestraditionally andperformed establishedby a CPU utilizing specialized chips known as general-purpose computing on graphics processing unitunits (GPGPU).

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