Yet, even when businesses capture the data ... flow volumes and potential choke points that are essential to know for system reliability. Seeing everything represented in a network graph is ...

neural networks, and deep learning in the larger context of data flow graphs. These graphs describe the computational network for models in a more complicated but more flexible, generalized ...

Deep flexibility. The major point in this area is that a data flow graph isn’t limited to representing neural networks. While there is a lot of support for neural networks in TensorFlow ...

In this example, we confine ourselves to a small network with no packet loss ... Figure C is a sample of how the text data file looks. The flow graph feature can provide a quick and easy to ...

What do we mean by “data flow graphs”? Well, that’s the really cool part. But before we can answer that, we’ll need to talk a bit about the structure for a simple neural network.

Their view is that dataflow architectures are the only way to efficiently train networks with high performance ... FPGA and manycore processor that tackles static scheduling of data flow graphs across ...