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Table 1: Computational Usage estimates for our proposed Yellowstone research based on our codes measured performance on Yellowstone during ASD period . Some additional disk space and CPU hours (small compared to the total numbers) may be needed for visualization;.
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Table 1: Computational Usage estimates for our proposed Yellowstone research based on our codes measured performance on Yellowstone during ASD period. Some additional disk space and CPU hours (small compared to the total numbers) may be needed for visualization;
Figure 1: Conceptual workflow for adjoint tomography, exemplified by an inversion for Europe.
Figure 2: (left) AWP-ODC Performance on Intel Sandy Bridge Based Gordon, IBM iDataPlex Carver, Cray XT5 Jaguar, and Yellowstone. (Right) SPECFEM3D Performance on DOE INCITE and XSEDE Systems
Figure 3: (a) Map of topography and major faults (thick black lines) of southern California. (b) The optimal perturbation results of the southern California tomographic inversion including iteration CVM-S4.21 performed on Yellowstone. In perturbation maps, the red regions represent velocity reduction areas and the blue regions represent velocity increase areas.
Figure 4: Illustration showing how a fractal model of small-scale heterogeneities is added into a 3D velocity model. The vertical section (left) and surface slice (right) of Vs velocity model including a fractal model with H=0.0 and =5%.
Figure 5: AWP-ODC forward earthquake simulations showing impact of small scale, near surface heterogeneities in 3D velocity model. Image (left) shows instantaneous peak velocities when small scale heterogeneities are present in 3D CVM, while image (right) shows equivalent simulation without such modifications. These images (and animation) were developed collaboratively by NCAR and SCEC researchers.