Boosting Deep Learning with the Intel Scalable System Framework
April 14, 2016 Rob Farber Training ‘complex multi-layer’ neural networks is referred to as deep-learning as these multi-layer neural architectures interpose many neural processing layers between the input data and the predicted output results – hence the use of the word deep in the deep-learning catchphrase. While the training procedure is computationally expensive, evaluating the resulting trained neural network is not, which explains why trained networks can be extremely valuable as they have the ability to very quickly perform complex, real-world pattern recognition tasks on a variety of low-power devices including security cameras, mobile phones, wearable technology. These architectures can also be implemented on FPGAs to process information quickly and economically in the data center on low-power devices, or as an alternative architecture on high-power FPGA devices. The Intel Xeon…
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Boosting Deep Learning with the Intel Scalable System Framework
