• Initial multi-GPU support viable for standalone and Spark.

  • Refactored the Spark API significantly

  • Added CuDNN wrapper

  • Performance improvements for ND4J

  • Introducing DataVec: Lots of new functionality for transforming, preprocessing, cleaning data. (This replaces Canova)

  • New DataSetIterators for feeding neural nets with existing data: ExistingDataSetIterator, Floats(Double)DataSetIterator, IteratorDataSetIterator

  • New learning algorithms for word2vec and paravec: CBOW and PV-DM respectively

  • New native ops for better performance: DropOut, DropOutInverted, CompareAndSet, ReplaceNaNs

  • Shadow asynchronous datasets prefetch enabled by default for both MultiLayerNetwork and ComputationGraph

  • Better memory handling with JVM GC and CUDA backend, resulting in significantly lower memory footprint

Last updated