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GPU621/To Be Announced

2 bytes removed, 21:14, 22 November 2020
Difference of CPU and GPU for parallel applications (Yunseon)
'''GPU(Graphics processing unit)'''
 
GPU is designed with thousands of processor cores running simultaneously and it enables massive parallelism where each of the cores is focused on making efficient calculations which are repetitive and highly-parallel computing tasks.  GPU was originally designed to create quick image rendering which is a specialized type of microprocessor. However, modern graphic processors are powerful enough to be used to accelerate calculations with a massive amount of data and others apart from image rendering.  GPUs can perform parallel operations on multiple sets of data, and able to complete more work at the same time compare to CPU by using Parallelism. Even with these abilities, GPU can never fully replace the CPU because cores are limited in processing power with the limited instruction set.  
'''What is the difference? '''
 
CPU can work on a variety of different calculations, while a GPU is best at focusing all the computing abilities on a specific task. Because the CPU is consisting of a few cores (up to 24) optimized for sequential serial processing. It is designed to maximize the performance of a single task within a job; however, it can do a variety of tasks.  On the other hand, GPU uses thousands of processor cores running simultaneously and it enables massive parallelism where each of the cores is focused on making efficient calculations which are repetitive and highly-paralleled architecture computing tasks.   
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