KITWARE INC — Department of Energy SBIR Phase I: 29d

Description

The promise of fusion energy is enormous—an energy system whose fuel is obtained from simple ingredients such as seawater and lithium, and which yields zero carbon emissions to the atmosphere. However, realizing this vision requires undertaking one of the most challenging programs of scientific research and development that has ever been undertaken. Predictive simulation plays a crucial role in fusion energy research. Such simulations provide a theoretical framework for the creation and evaluation of fusion experiments, and point the way towards viable designs. However, two key problems must be overcome if simulation is to remain effective as problem size and complexity increases. First, large-scale computing is producing large amounts of data and consequently data transfer is now the major bottleneck in most simulation workflows. Second, the complexity of multi-physics analyses requires the capability to easily configure software systems into workflows that can handle complex, multi-physics workflows. Without properly addressing these challenges, the ability to perform successful fusion research will be greatly reduced. In the work proposed here we describe a method to address these challenges. We will use the Adaptable IO System (ADIOS) to support fast, scalable, and portable I/O and data transfer; and VTK-m a high-performance system to support a number of abstract simulation data models. Together the combined capabilities of ADIOS and VTK-m will enable scalable I/O and support interoperable simulation tools that can be readily integrated into efficient simulation workflows.