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#Deeplearning4j images for cuda and hadoop.

Deeplearning4j development environment for hadoop and spark: Below are the folders for:

  1. deeplearning4j: This is a folder for building deeplearning4j from source.
  2. hadoop-docker: full blown hdfs and yarn bundled with cuda. Make sure to mount a /data directory as a volume to hdfs. (see the hdfs-site.xml)
  • note also that if you use a volume you need to format the name node before you start the container. If you define a volume define a new entry point with a mounted inithadoop.sh which will run the format for the container followed by the "real" entrypoint.
  1. spark: a functional spark 1.6.2 installation that can be used for spark slave and master bundled with cuda connecting to hadoop.
  2. compose: a sample spark/hadoop cluster, for running gpus in compose use: https://github.com/eywalker/nvidia-docker-compose
  3. streamsets: this is for an ETL gui integrated with hadoop and spark. Versions: Spark 1.6.2 Cuda 8 Cudnn 5.0 Hadoop 2.7.2 Openblas current master Hadoop and spark compiled with java 8 Spark/scala version: 2.11

#Downloading ##Dl4j (WARNING THIS IS an 8GB download)

docker pull skymindio-docker-dl4j-dev-environment.bintray.io/skymindio/dl4j-dev-environment:0.6.1-SNAPSHOT

##Spark

docker pull skymindio-docker-dl4j-spark.bintray.io/skymindio/dl4j-spark

##Hadoop

docker pull skymindio-docker-dl4j-hadoop.bintray.io/skymindio/dl4j-hadoop

##Streamsets

docker pull skymindio-docker-datacollecor.bintray.io/skymindio/datacollector

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