Specifications include, but are not limited to: Oauth2 authentication, via a web portal. Personalized jupyter notebook and unix-based development environment Nearly instant on-demand instantiation of elastic Apache Spark and OpenMPI clusters compute resources. Integration with github or other public git repositories Support for developing three open source week-long bootcamps for python, numerical and statistical methods, and machine learning. Support for about 25 users for 1 year including compute and storage. Each user has an elastic quota for storage and compute resources. Access to large publicly available scientific data sets in a cloud-storage interface. Runnable examples of a high-performance hydrodynamics code on a cloud-based MPI instance and Apache Spark on a larger astronomical data set.
