Adaptive Multidimensional Modeling with Applications in Scientific Computing
No abstract available
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
No abstract available
Explore the source record for details and available documents.
Abstract not provided
Abstract not provided.
Explore the source record for details and available documents.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Final report
Exascale computing systems are soon to emerge, which will pose great challenges on the huge gap between computing and I/O performance. Many large-scale scientific applications play an important role in our daily life. The huge amounts of data generated by such applications require highly parallel and efficient I/O management policies. In this paper, we adopt a mission-critical scientific application, GEOS-5, as a case to profile and analyze the communication and I/O issues that are preventing applications from fully utilizing the underlying parallel storage systems. Through in-detail architectural and experimental characterization, we observe that current legacy I/O schemes incur significant network communication overheads and are unable to fully parallelize the data access, thus degrading applications' I/O performance and scalability. To address these inefficiencies, we redesign its I/O framework along with a set of parallel I/O techniques to achieve high scalability and performance. Evaluation results on the NASA discover cluster show that our optimization of GEOS-5 with ADIOS has led to significant performance improvements compared to the original GEOS-5 implementation.
Cardiovascular implantable devices alter the biofluid dynamics and biochemistry of the blood in which they are placed. These perturbations can lead to thrombus formation which may or may not be desired, depending on the application. In this work, a computational model is developed that couples biofluid dynamics and biochemistry to predict the clotting response of blood to such devices. The model consists of 28 advection–diffusion–reaction partial differential equations to track proteins in the blood involved in clotting and utilizes boundary flux terms to model the initiation of the intrinsic clotting pathway at thrombogenic device surfaces. We use this model to simulate the transient clot growth within a 2D idealized bifurcation aneurysm filled with various distributions of bare metal coils with similar packing densities. The clot model predicts initial clot formation to occur in areas along coil surfaces where flow is minimal and where time-averaged shear rates are the smallest. Among the six coil-filled aneurysm cases simulated, maximum thrombus occlusion ranged between 80.8 and 92.2% of the post-treatment aneurysm volume and was achieved 325–450 s after treatment. Finally, with further refinement and validation, the computational clotting model will be a valuable engineering tool for evaluating and comparing the relative performance of cardiovascular implantable devices.
Application of optimal control to launch vehicle computer program
Control optimization, stabilization, and computer algorithms for space applications