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HPC-ED is working to improve discovery and sharing of CyberTraining resources through the combination of the HPC-ED CyberTraining Catalog, an effective and flexible interface, thoughtful metadata design, and active community participation. HPC-ED encourages authors to share training resource information while retaining ownership and allows organizations to enrich their local portals with shared materials. By basing the architecture on an established, flexible framework, HPC-ED can provide a range of solutions people and organizations can employ for sharing and discovering materials. In this paper we describe the initial pilot phase of the project, where we prototyped the HPC-ED catalog, established an initial metadata set, provided documentation, and began using the system to share and discover materials. We gathered community feedback through a variety of means, and are now planning an implementation phase based on evolving our architecture and tools to meet community needs and feedback through improved interfaces and tools designed to address a range of preferences. 

The needs of cyberinfrastructure (CI) Users are different from those of CI Contributors. Typically, much of the training in advanced CI addresses developer topics such as MPI, OpenMP, CUDA and application profiling, leaving a gap in training for these users. To remedy this situation, we developed a new program: COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure (COMPLECS). COMPLECS focuses exclusively on helping CI Users acquire the skills and knowledge they need to efficiently accomplish their compute- and data-intensive research, covering topics such as parallel computing concepts, data management, batch computing, cybersecurity, HPC hardware overview, and high throughput computing. 

To improve the sharing and discovery of CyberTraining materi- als, the HPC-ED Pilot project team is building a platform for the community to better share and find training materials through a federated catalog. The platform, currently in early test mode, is fo- cused on a flexible platform, informative metadata, and community participation. By creating a framework for identifying, sharing, and including content broadly, HPC-ED will: allow providers of training materials to reach new groups of learners; extend the breadth and depth of training materials; and enable local sites to add or extend local portals. 

Throughout the cyberinfrastructure community there are a large range of resources available to train faculty and young scholars about successful utilization of computational resources for research. The challenge that the community faces is that training materi- als abound, but they can be difficult to find, and often have little information about the quality or relevance of offerings. Building on existing software technology, we propose to build a way for the community to better share and find training and education materials through a federated training repository. In this scenario, organizations and authors retain physical and legal ownership of their materials by sharing only catalog information, organizations can refine local portals to use the best and most appropriate ma- terials from both local and remote sources, and learners can take advantage of materials that are reviewed and described more clearly. In this paper, we introduce the HPC ED pilot project, a federated training repository that is designed to allow resource providers, campus portals, schools, and other institutions to both incorporate training from multiple sources into their own familiar interfaces and to publish their local training materials. 

The General Curvilinear Coastal Ocean Model (GCCOM) is a 3D curvilinear, structured-mesh, non-hydrostatic, large-eddy simulation model that is capable of running oceanic simulations. GCCOM is an inherently computationally expensive model: it uses an elliptic solver for the dynamic pressure; meter-scale simulations requiring memory footprints on the order of 10 12 cells and terabytes of output data. As a solution for parallel optimization, the Fortran-interfaced Portable–Extensible Toolkit for Scientific Computation (PETSc) library was chosen as a framework to help reduce the complexity of managing the 3D geometry, to improve parallel algorithm design, and to provide a parallelized linear system solver and preconditioner. GCCOM discretizations are based on an Arakawa-C staggered grid, and PETSc DMDA (Data Management for Distributed Arrays) objects were used to provide communication and domain ownership management of the resultant multi-dimensional arrays, while the fully curvilinear Laplacian system for pressure is solved by the PETSc linear solver routines. In this paper, the framework design and architecture are described in detail, and results are presented that demonstrate the multiscale capabilities of the model and the parallel framework to 240 cores over domains of order 10 7 total cells per variable, and the correctness and performance of the multiphysics aspects of the model for a baseline experiment stratified seamount.