Wendelin Exanalytics Libre

WENDELIN combines Scikit Learn machine learning and NEO distributed storage for out-of-core data analytics in python

Table of Contents

Wendelin Architecture

Wendelin architecture is based on 5 layers:

  • Analytics layer: Wendelin leverages a wide variety of Numpy based analytics libraries such as scikit-learn, Pandas, NLTK, OpenCV-python, etc
  • Storage layer: Wendelin stores native python objects on NEO distributed storage and thus eliminates format conversion steps found in other NoSQL technologies.
  • Elasticity layer: Wendelin distributes data processing scripts on a cluster thanks to ERP5 active python object technology. Scripts are stored on NEO and can be modified in real time without any system restart.
  • Deployment layer: Wendelin deployment is automated thanks to SlapOS mesh computing operating system. Analytics libraries are optimized automatically by SlapOS based on the targert CPU.
  • Infrastructure Layer: Wendelin can be deployed on commodity hardware, private cloud or public cloud.

 

Key Features

  • Python based
  • Native code compiler for key algorithms
  • GPU compiler for key algorithms
  • Native storage of low level matrix data structure
  • Best machine learning algorithms
  • Wide scientific community thanks to Numpy
  • Support 30+ years of FORTRAN optimizations
  • Distributed multi-index
  • Orthogonal index/storage topology for high throughput and fast access

Wendelin architecture provides key features not found in other platforms.