machine learning


"Horovod is a distributed training framework for TensorFlow, Keras, PyTorch, and MXNet. The goal of Horovod is to make distributed Deep Learning fast and easy to use. The primary motivation for this project is to make it easy to take a single-GPU TensorFlow program and successfully train it on many GPUs faster."

Quote from Horovod Github documentation


 PyTorch is an open source machine learning framework with GPU acceleration and deep neural networks that is based on the automatic differentiation in the Torch library of tensors.

Availability and Restrictions


OSC does not provide general access to PyTorch.  However, we are available to assist with the configuration of local individual/research-group installations on all our clusters.  If you have any questions, please contact OSC Help.


"Torch is a deep learning framework with wide support for machine learning algorithms. It's open-source, simple to use, and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C / CUDA implementation. Torch offers popular neural network and optimization libraries that are easy to use, yet provide maximum flexibility to build complex neural network topologies. It also runs up to 70% faster on the latest NVIDIA Pascal™ GPUs, so you can now train networks in hours, instead of days."


"TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture lets you deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code."

Quote from TensorFlow Github documentation