The increase in processing capabilities has been a tremendous booster for usage of neural networks in day-to-day problems. GPU is a specialized processor designed to perform graphical operations (for example, gaming, 3D animation, and so on). They perform mathematically intensive tasks and are additional to the CPU. The CPU performs the operational tasks of the computer, while the GPU is used to perform heavy workload processing.
The neural network architecture needs heavy mathematical computational capabilities and GPU is the preferred candidate here. The vectorized dot matrix product between the weights and inputs at every neuron can be run in parallel through GPUs. The advancements in GPUs is popularizing neural networks. The applications of DL in image processing, computer vision, bioinformatics, and weather modeling are benefiting through GPUs.
