Management and Deployment of Scientific Applications with SIMULOCEAN Science Gateway

SIMULOCEAN is a web-based scientific application and visualization framework for the management and deployment of software serving the coastal modeling community. The framework helps to collect observational data, schedule modeling codes for execution, manage data transfer, and visualize both observational and numerical results. With all the information collected, SIMULOCEAN can also provide direct validation and verification for models, and generate high quality technical reports. As part of the SIMULOCEAN framework, we developed the Coastal Model Repository (CMR) which is targeting cloud and cloud-like architectures to enable quick deployment of coastal models and their working environments. CMR will serve as a community repository for precompiled open source models that are widely used by coastal researchers. While source code for various executables and libraries will be available, CMR will also introduce distribution of containerized coastal models, which can run on any cloud-like architecture directly, and with negligible system overhead. The idea of containerization of cloud-ready applications is not new, but it has become a viable solution given the rapid development of kernel-level virtualization technologies. One such technology, Docker, is an open platform allowing developers to build, ship, and run distributed applications in self-contained environments. Docker enables executable applications to be quickly assembled from components then run by a user without the need to rebuild or satisfy any external dependencies. As a result, a Docker-enabled app can be reliably executed in a known operating system environment on any system that supports Docker containers. With the help of CMR, a coastal researcher can start running state-of-the-art models on the latest cloud-ready computing systems in minutes. The SIMULOCEAN science gateway can take advantage of CMR to quickly deploy coastal models on academic and commercial cloud platforms, in addition to traditional HPC systems. This work is supported by NSF Award CCF-1539567 and in part by HPC computing resources at LSU. We acknowledge the assistance and support of the CSDMS Integration Facility and XSEDE Extended Collaborative Support Service (ECSS) program.