JupyterHub-FIONA is a new computational resource hosted by the Berkeley Research Computing program that provides high-performance interactive computing with a pre-configured Jupyter environment.
UC Berkeley is currently hosting a node loaned by the Pacific Research Platform project, built with 28 Xeon cores, an NVIDIA K80 dual-GPU card, 256GB of RAM, roughly 5TB of SSD storage, and 80Gbps of network bandwidth (full specs below). It is configured with a JupyterHub instance for interactive usage, including the entire scientific python stack as well as CUDA support, Caffe, TensorFlow, direct support for spawning kernels on Comet (@SDSC), and other tools.
The purpose of this node is to support the development of better research computing environments that sit at the boundary between interactive usage and large-scale HPC resources. Jupyter is typically used by individual users on either personal machines or small-/medium-sized cloud/remote nodes. With this experiment, we are offering a system whose performance profile goes beyond that and is a gateway to HPC-scale resources, such as those provided by the Berkeley Research Computing program, by XSEDE resources (including Comet at SDSC), and the NERSC facilities at LBNL.
Access to this resource is free of charge. The full invitation to researchers is available here. Please review the full document before applying for access via a simple online intake form. Researchers are welcome to e-mail firstname.lastname@example.org with questions about the resource or application process (please use “JupyterHub Call for Proposals” as part of your subject line to help the BRC consultants quickly direct your message).
The server is running CentOS 7.2.1511, and its JupyterHub login is available at https://jhub-prp.berkeley.edu. Note that as of this writing, network connectivity is capped at 10Gbps. The hardware specifications for the system are as follows: