How does deep learning 4J work??
Training with Deeplearning4j occurs in a cluster. Neural nets are trained in parallel via iterative reduce, which works on Hadoop -YARN and on Spark. Deeplearning4j also integrates with CUDA kernels to conduct pure GPU operations, and works with distributed GPUs.
What is Eclipse Deeplearning4j??
Eclipse Deeplearning4j is a suite of tools for running deep learning on the JVM. It's the only framework that allows you to train models from java while interoperating with the python ecosystem through a mix of python execution via our cpython bindings, model import support, and interop of other runtimes such as tensorflow-java and onnxruntime.
What programming language is Deeplearning4j written in??
Deeplearning4j is written in Java and is compatible with any JVM language, such as Scala, Clojure, or Kotlin. The underlying computations are written in C, C++, and Cuda. Keras will serve as the Python API.
Is Deeplearning4j as fast as Caffe??
Deeplearning4j is as fast as Caffe for non-trivial image recognition tasks using multiple GPUs. For programmers unfamiliar with HPC on the JVM, there are several parameters that must be adjusted to optimize neural network training time.