Productivity from day one on supercomputers that leverage new technologies requires significant preparation. An institution that procures a novel system architecture often lacks sufficient institutional knowledge and skills to prepare for it. Thus, the "Center of Excellence" (CoE) concept has emerged to prepare for systems such as Summit and Sierra, currently the top two systems in the Top 500. This paper documents CoE experiences that prepared a workload of diverse applications and math libraries for a heterogeneous system. We describe our approach to this preparation, including our management and execution strategies, and detail our experiences with and reasons for using different programming approaches. Our early science and performance results show that the project enabled significant early seismic science with up to a l4X throughput increase over Cori. In addition to our successes, we discuss our challenges and failures so others may benefit from our experience.

The Carbon Capture Simulation Initiative (CCSI) project has developed and deployed scientific infrastructure called the CCSI Toolset. The CCSI Toolset provides state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. Carbon capture technologies have the potential to dramatically reduce the carbon emissions from power plants. The CCSI Toolset provides end users in industry with a comprehensive, integrated suite of leading-edge, scientifically validated models with simulation, uncertainty quantification, optimization, risk analysis and decision making support. The CCSI Toolset has at its core an integrated framework that enables execution of simulations and workflows including optimization and uncertainty parameter sweeps using a wide variety of computing platforms including desktops, clusters, Clouds, and HPC systems. The integration framework enables the running of a variety of commercial process simulation packages as well as custom simulators. Moreover, the framework enables scientists to run and manage thousands of concurrent simulations to perform optimizations and uncertainty quantification. Components of the CCSI Toolset are connected through the use of a data management system that stores data to a repository and enables the tracking of provenance for each simulation as well as its associated components. The data management system tracks all the configurations, models, simulations, and results created during the design of a carbon capture system and supports the design life-cycle as well as decision making. The primary contribution of this paper is thus the design and implementation of the integration framework within the CCSI Toolset, which provides both data management and simulation support for CCSI. This integration framework has been deployed and is in use by several groups of researchers and commercial entities.

Coupling separately developed codes offers an attractive method for increasing the accuracy and fidelity of the computational models. Examples include the earth sciences and fusion integrated modeling. This paper describes the Framework Application for Core-Edge Transport Simulations (FACETS).

Software is among the most complex human artifacts, and visualization is widely acknowledged as important to understanding software. In this paper, we consider the problem of understanding a software system's architecture through visualization. Whereas traditional visualizations use multiple stakeholder-specific views to present different kinds of task- specific information, we propose an additional visualization technique that unifies the presentation of various kinds of architecture-level information, thereby allowing a variety of stakeholders to quickly see and communicate current development, quality, and costs of a software system. For future empirical evaluation of multi-aspect, single-view architectural visualizations, we have implemented our idea in an existing visualization tool, Vizz3D. Our implementation includes techniques, such as the use of a city metaphor, that reduce visual complexity in order to support single-view visualizations of large-scale programs.

Babel is a high-performance, n-way language interoperability tool for the HPC community that now includes support for distributed computing via remote method invocation (RMI). We describe the design and implementation of Babel RMI, including its specification in our scientific interface definition language (SIDL), modifications to Babel's code generators, and support for third-party wire protocols. Babel RMI's programming model consistency, functional capabilities, and runtime performance are compared in context with COM, CORBA, grid/Web services, and Java RMI, Babel RMI's current features and performance uniquely recommend it for "short-haul" distributed computing within a machine room or single cluster. We describe the experience of some early adopters who use Babel RMI to couple and coordinate multiple MPI jobs on a single cluster to perform multiscale material science calculations.

Abstract The Common Component Architecture (CCA) is a component model for high‐performance computing, developed by a grass‐roots effort of computational scientists. Although the CCA is usable with CORBA‐like distributed‐object components, its main purpose is to set forth a component model for high‐performance, parallel computing. Traditional component models are not well suited for performance and massive parallelism. We outline the design pattern for the CCA component model, discuss our strategy for language interoperability, describe the development tools we provide, and walk through an illustrative example using these tools. Performance and scalability, which are distinguishing features of CCA components, affect choices throughout design and implementation. Copyright © 2005 John Wiley & Sons, Ltd.