Deep learning models are known to be computationally expensive and can take several days to train depending upon the size of data-set. To reduce the processing time the use of GPU and distributed computing using MapReduce can be seen these days. In this post I will show how to combine both of these processing paradigm. Once the learning algorithm is implemented using MapReduce it is possible to use the model on the Elastic Map Reduce(EMR) platform provided by Amazon Web Services (AWS). The code is available on Github.
I will use Mrjob’s MapReduce implementation in Python to implement a simple neural network.
Each mapper or individual machine is equipped with a GPU and uses Theano/Tensorflow for GPU multi-threading. Continue reading