Tarantella is an open-source, distributed Deep Learning
framework built on top of TensorFlow 2, providing
scalable Deep Neural Network training on CPU and GPU
Tarantella is easy-to-use, allows to re-use existing
TensorFlow 2/Keras models, and does not require any
knowledge of parallel computing.
Tarantella allows you to speed up your AI workflows by providing
scalable Deep Neural Network
training on multi-GPU and multi-no de
Tarantella comes with a simple, minimalistic API that abstracts away any parallel computing details. It provides a rich technical documentation and tutorials to quickly get started.
Tarantella supports the full Keras API of TensorFlow 2 and lets you easily integrate Tarantella in your existing workflows.
Tarantella takes automatic care of the distribution of data and computation in such a way that serial results are reproduced.
Tarantella is a community-driven,
open-source framework that builds
on top of TensorFlow 2.
Tarantella supports CPU and GPU
clusters, independently of the
hardware type and vendor.
To get you started quickly, download Tarantella from github, check out the installation guidelines, and
the tutorials and documentation.
If you want to contribute to Tarantella, have a look at feature requests, bug reports and the
Tarantella is developed at the Competence Center for High Performance Computing, which is part of the Fraunhofer
Institute for Industrial Mathematics ITWM. In close cooperation with industrial and academic partners,
the Competence Center for High Performance Computing develops solutions for the efficient use of increasingly
more complex processors and parallel computers. Our focus lies particularly in the fields of HPC tools, such as
parallel filesystems and scalable parallel programming, seismic and visualization, Deep Learning tools and
applications, as well as hardware-software co-design and Green by IT.