The main difference between CPU and GPU architectures is that CPUs are designed to handle a wide range of tasks quickly (as measured by CPU clock speed), but the symmetries of those tasks are limited. A GPU is designed to render high-resolution images and video simultaneously.
Since GPUs can process multiple sets of data simultaneously, they are also commonly used for non-graphical tasks such as machine learning and scientific computation. Designed with thousands of processor cores running simultaneously, the GPU enables massive parallelism where each core is focused on performing efficient calculations.
Multi-core processors that have both a CPU and a GPU have been on the market for many years. In fact, almost every notebook, smartphone and tablet PC now has a multi-core processor with an integrated GPU and audio, networking and other features.
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Since GPUs can process multiple sets of data simultaneously, they are also commonly used for non-graphical tasks such as machine learning and scientific computation. Designed with thousands of processor cores running simultaneously, the GPU enables massive parallelism where each core is focused on performing efficient calculations.
Multi-core processors that have both a CPU and a GPU have been on the market for many years. In fact, almost every notebook, smartphone and tablet PC now has a multi-core processor with an integrated GPU and audio, networking and other features.