Overview

The Zeblok Notebooks allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

Zeblok notebooks are built on the top of the Nvidia CUDA Docker image. CUDA is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers can dramatically speed up computing applications by harnessing the power of GPUs.

The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime.

The CUDA container images on Docker Hub provide an easy-to-use distribution for CUDA supported platforms and architectures.

Zeblok notebooks supports CUDA 10.1 toolkit. and cuDNN version 1. The NVIDIA CUDA® Deep Neural Network library (cuDNN) is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers.

Deep learning researchers and framework developers worldwide rely on cuDNN for high-performance GPU acceleration. It allows them to focus on training neural networks and developing software applications rather than spending time on low-level GPU performance tuning. cuDNN accelerates widely used deep learning frameworks, including Caffe,Caffe2ChainerKeras,MATLABMxNetTensorFlow, and PyTorch. For access to NVIDIA optimized deep learning framework containers, that has cuDNN integrated into the frameworks, visit NVIDIA GPU CLOUD to learn more and get started.

 

Install external modules into the ZeblokNotebook

  1.  Let's say we wanted to use the module 'xgboost'. Observe that it is not installed currently.

  2. Mention it in Module.txt file inside zeblokNotebooks/zeblokScripts/ folder.

  3. Import the helper function from ZeblokInstaller and run it.

import sys
scripts_path='/home/jovyan/zeblokNotebooks/zeblokScripts'
if scripts_path not in sys.path: 
    sys.path.insert(0, scripts_path)
from ZeblokInstaller import install_modules
install_modules()

Available Notebooks

jupyter/minimal-notebook

Source on GitHub | Dockerfile commit history | Docker Hub image tags

jupyter/minimal-notebook adds command line tools useful when working in Jupyter applications.

jupyter/r-notebook

Source on GitHub | Dockerfile commit history | Docker Hub image tags

jupyter/r-notebook includes popular packages from the R ecosystem.

jupyter/scipy-notebook

Source on GitHub | Dockerfile commit history | Docker Hub image tags

jupyter/scipy-notebook includes popular packages from the scientific Python ecosystem.

jupyter/tensorflow-notebook

Source on GitHub | Dockerfile commit history | Docker Hub image tags

jupyter/tensorflow-notebook includes popular Python deep learning libraries.

  • Everything in jupyter/scipy-notebook and its ancestor images
  • tensorflow and keras machine learning libraries

jupyter/datascience-notebook

Source on GitHub | Dockerfile commit history | Docker Hub image tags

jupyter/datascience-notebook includes libraries for data analysis from the Julia, Python, and R communities.

  • Everything in the jupyter/scipy-notebook and jupyter/r-notebook images, and their ancestor images
  • The Julia compiler and base environment
  • IJulia to support Julia code in Jupyter notebooks
  • HDF5Gadfly, and RDatasets packages

jupyter/pyspark-notebook

Source on GitHub | Dockerfile commit history | Docker Hub image tags

jupyter/pyspark-notebook includes Python support for Apache Spark, optionally on Mesos.

  • Everything in jupyter/scipy-notebook and its ancestor images
  • Apache Spark with Hadoop binaries
  • Mesos client libraries

jupyter/all-spark-notebook

Source on GitHub | Dockerfile commit history | Docker Hub image tags

jupyter/all-spark-notebook includes Python, R, and Scala support for Apache Spark, optionally on Mesos.