OSC will be refreshing the software stack for Owens and Pitzer on May 19, 2020. This will be done in a system-wide downtime. During the software refresh, some default versions will be changed to be more up-to-date. Information about the new default versions, as well as all available versions of each software package will be included on the corresponding OSC software webpage. See https://www.osc.edu/supercomputing/software-list.
"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.
OSC is refreshing the software stack for Owens and Ruby on September 4, 2018. This will be done by a rolling reboot. During the software refresh, some default versions are updated to be more up-to-date. Information about the old and new default versions, as well as all available versions of each software package will be included on the corresponding OSC software webpage. See https://www.osc.edu/supercomputing/software-list.
"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.
OSC is refreshing the software stack for Oakley and Ruby on February 22, 2017 (during the scheduled downtime). During the software refresh, some default versions are updated to be more up-to-date and some older versions are removed. Information about the old and new default versions, as well as all available versions of each software package will be included on the corresponding OSC software webpage. See https://www.osc.edu/supercomputing/software-list.
Darshan is a lightweight "scalable HPC I/O characterization tool
The following versions of Darshan are available on OSC clusters:
Caffe is "
From their README:
PAPI provides the tool designer and application engineer with a consistent interface and methodology for use of the performance counter hardware found in most major microprocessors. PAPI enables software engineers to see, in near real time, the relation between software performance and processor events.
This software will be of interest only to HPC experts.
