Hopsworks provides a FTI (feature/training/inference) pipeline architecture for ML systems. Each part of the pipeline is defined in a Hopsworks job which corresponds to a Jupyter notebook, a python script or a jar. The production pipelines are then orchestrated with Airflow which is bundled in Hopsworks. Hopsworks provides several python environments that can be used and customized for each part of the FTI pipeline, for example switching between using PyTorch or TensorFlow in the training pipeline. You can train models on as many GPUs as are installed in a Hopsworks cluster and easily share them among users. You can also run Spark, Spark Streaming, or Flink programs on Hopsworks. JupyterLab is also bundled which can be used to run Python and Spark interactively.
0 commit comments