Romeo presents at GTU Europe in Munich about implementing parallelization in the various deep learning frameworks on Apache Spark.

In this video:

Romeo presents at GPU Technology Conference, and talks about deep learning and applying it to IoT sensor data, which is structured data and time-series data, and using any of the open source deep learning frameworks for analyzing the IoT data.

After giving a brief introduction to deep learning and LSTM networks (read his tutorial for more details), Romeo discusses 4 ways of doing parallelization and introduces the deep learning frameworks for Apache Spark and how to turn on GPU and achieve parallelization:

He finally discusses different messaging protocols, including broadcasts, GRPC, and Open MPI, and finally IBM Spectrum MPI, giving IBM the fastest AI system because of connection between CPU and GPU.

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