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GPU621/To Be Announced

4 bytes added, 21:13, 22 November 2020
Difference of CPU and GPU for parallel applications (Yunseon)
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.  
 
 
'''CPU(Central processing unit)'''
CPU  can work on a variety of different calculations, and it usually has less than 100 cores (8-24) which can also do parallel computing using its instruction pipelines and also cores. Each core is strong and processing power is significant. For this reason, the CPU core can execute a big instruction set, but not too many at a time. Compare to GPUs, CPUs are usually smarter and have large and wide instructions that manage every input and output of a computer.
 
 
'''What is the difference? '''
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