Performance of Distributed TensorFlow: A Multi-Node and Multi-GPU Configuration

This 20-page explores the performance of distributed TensorFlow in a multi-node and multi-GPU configuration, running on an Amazon EC2 cluster.

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    Why read this?

    The technical study includes performance results for two types of metrics:

    • Total number of images processed per second
    • Average total time of processing on a batch.

    In addition, the following values—derived from the metrics above—were measured:

    • Time normed to the number of computing nodes and workers
    • Speed of image processing (samples per second) normed to the number of computing nodes and workers

    The performance benchmark was carried out employing the Inception architecture as a neural network model and the Camelyon16 data as a training set.

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