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A typical central processing unit, or a CPU, is a versatile device, capable of handling many different tasks with limited parallelcan bem using tens of CPU cores. A graphical digesting unit, or even a GPU, was created with a specific goal in mind — to render graphics as quickly as possible, which means doing a large amount of floating point computations with huge parallelwill bem making use of a large number of tiny GPU cores. That is why, because of a deliberately large amount of specialized and Multi Gpu Server sophisticated optimizations, GPUs have a tendency to run faster than traditional CPUs for particular tasks like Matrix multiplication that is clearly a base task for Deep Learning or 3D Rendering.

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Why are GPUs faster than CPUs anyway?

A typical central processing unit, or a CPU, is a versatile device, capable of handling many different tasks with limited parallelcan bem using tens of CPU cores. A graphical digesting unit, or perhaps a GPU, was created with a specific goal in mind — to render graphics as quickly as possible, which means doing a large amount of floating point computations with huge parallelwill bem utilizing a large number of tiny GPU cores. This is why, because of a deliberately large amount of specialized and sophisticated optimizations, nvidia ai gpu GPUs have a tendency to run faster than traditional CPUs for particular tasks like Matrix multiplication that is a base task for Deep Learning or 3D Rendering.

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