The goal of this project is to provide scientists and engineers with a generalized, hardware-independent programming and runtime environment that takes advantage of the wide range of scalable, high-performance, highly heterogeneous hardware systems available, while masking the details of each from the programmer. This environment will further provide an integrated inverse modeling tool to perform guided parameter space and uncertainty analysis as well as model optimization. Such inverse modeling is critical to identify general patterns in order to develop new scientific theories that characterize complexity and thus capture the essence of complex natural and engineered systems.
In addition to improving our understanding of complexity in natural and built systems (primary CDI theme), the proposed environment will aid in visualizing and extracting knowledge from data (secondary CDI theme) for which inverse methods (e.g., deconvolutions, regressions, parameter space/uncertainty analysis, model optimization) are indispensable. Reaching these goals is only possible, however, when combining the highest-performing heterogeneous hardware solutions that can execute many thousands of simulations with a high-level programming and inverse modeling environment that effectively hides the heterogeneous hardware complexities. Several general computing classes are identified, with example applications from science and engineering, that are likely to benefit from such heterogeneous hardware implementations. Such implementations would then open up new, transformational opportunities in scientific and engineering computing, increasing the likelihood of discovery of new theories regarding multi-scale interactions, emergent behavior, pattern formation, and self-organization in complex, feedback-prone systems.Several fundamental scientific and engineering computing categories with example applications from seismology, volcanology, hydrodynamics, and rock magnetics have been identified as targets of opportunity for this type of heterogeneous computing.
