Fujitsu Creates Highly Parallel Deep Learning Software For GPU Networks

Fujitsu announced that it has developed a new deep learning technology that can significantly increase the efficiency of deep learning on highly parallel GPU-based systems. The Problem With Deep Learning On Multiple GPUs Over the past few years, there has been an explosion of interest in deep learning as a better way to train machines to do certain tasks. Because of this, GPUs, which are well suited for processing many pieces of similar data simultaneously, have also become the centerpiece technology for deep learning development. However, even with GPUs, it still takes too much time to create a new algorithm with deep learning out of large amounts of data. One of the issues is that deep learning and other GPU-related operations don’t scale that well over multiple GPUs. The conventional…


Link to Full Article: Fujitsu Creates Highly Parallel Deep Learning Software For GPU Networks