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SkyScale’s high performance computing appliances adds tremendous compute power for many machine learning applications with the Worlds Fastest Compute Engines based on NVIDIA Tesla P100 GPU accelerators
Deep Learning is solving important scientific, enterprise, and consumer problems that seemed beyond our reach just a few years back. Deep learning is a branch of machine learning that attempts to train computers to identify patterns and objects, in the same way humans do. This technology is already used in speech recognition, photo searches on Google+ and video recommendations on YouTube.
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 way less time than before. More GPUs means more computational power so if a system has multiple GPUs, it can compute data much faster than a system with only CPUs, or a system with a CPU and a single GPU. Every major deep learning framework is optimized for NVIDIA GPUs, enabling data scientists and researchers to leverage artificial intelligence for their work. SkyScale’s platforms are well suited for applications such as deep learning and image recognition with each node containing up to 16 Tesla P100 GPU accelerators.
KEY FEATURES OF THE TESLA P100 FOR DEEP LEARNING TRAINING
Caffe, TensorFlow, and CNTK are up to 3x faster with Tesla P100 compared to K80
100% of the top deep learning frameworks are GPU-accelerated
Up to 21.2 TFLOPS of native half precision floating point
Up to 16 GB of memory capacity with up to 732 GB/s memory bandwidth
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