High Performance Computing GPU Accelerators in Deep Learning
by staff from High-Performance Computing News Analysis | insideHPC on (#QB92)
Training the neural networks used in deep learning is an ideal task for GPUs because GPUs can perform many calculations at once (parallel calculations), meaning the training will take much less time than it used to take. More GPUs means more computational power so if a system has multiple GPUs, it can compute data much faster than a system with CPUs only, or a system with a CPU and a single GPU. One Stop System's High Density Compute Accelerator is the densest GPU expansion system to date.
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