Enhanced deep learning doubles GPU memory accuracy

The technology reduces the volume of internal GPU memory used by over 40%. Fujitsu has introduced a new technology that it says will streamline the internal memory of GPUs, resulting in heightened machine learning accuracy. Recent years have seen a focus on technologies that use GPUs for high-speed machine learning to support the huge volume of calculations necessary for deep learning processing. But to make use of a GPU’s high-speed calculation ability, the data to be used in a series of calculations needs to be stored in the GPU’s internal memory, which, in turn, creates an issue where the scale of the neural network that could be built is limited by memory capacity. Fujitsu Laboratories has been working on a technology to improve memory efficiency, implementing and evaluating it in…


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