Tensorflow is an open-source framework for high-performance numerical computation. It is used for both research and production systems on a variety of platforms from mobile and edge devices, to desktops and clusters of servers. Its main use is Machine Learning and especially Deep Learning.
In this post, we will show you how you can use your MooseFS cluster with Tensorflow to train deep neural networks!
We are proud to make this announcement that our friends from the “Institute of Mathematical Machines and Mandala Robotics” secured the first and second positions in the “Autonomous Robots International Competition: ERL Emergency 2017” held recently at Piombino, Italy. Their robot uses MooseFS driven storage for 3D Scanning, 3D Mapping, and 3D Modelling.
The Robot needed to perform multiple high-level functions simultaneously like Modelling & Mapping its processor, managing its control station, performing AI-driven automatic object recognition to mention among a few, and this required robust parallel access to data which was supported by MooseFS.
Additionally, MooseFS allowed a significant amount of data to be processed in real-time. This feature facilitated Robot’s multiple 3D scans along with 360° video to cover the entire investigating area.
This is an excellent example to showcase one of the many benefits that MooseFS provides to its customers!