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Using RapidMiner H2O operators with existing H2O local server
I have noticed the previous discussion on using CUDA and GPUs with RM so this is a related query. I can run GPU based Tensorflow, Keras and MXNet from the RM Python interface and I can access local H2O server from R and Python. However, using the existing RM H2O operators seems like a very attractive option. So, I wonder if it is possible to configure RM client to connect to an existing H2O server rather than start a new H2O cluster each time an H2O operator is run (per session). In this way, you could link RM client with the H2O server supporting GPUs. Would it be possible without installing the Hadoop, Spark, etc.
I am using an educational license of RapidMiner Studio.