1. UCERF3 Uniform California Earthquake Rupture Forecast (UCERF3) 14 Full-3D tomographic model CVM-S4.26 of S. California 2 CyberShake 14.2 seismic hazard model for LA region 3 Dynamic rupture model of fractal roughness on SAF Fig. 1. A wiring diagram for the SCEC computational pathways of earthquake system science (left) and large-scale calculations exemplifying each of the pathways (below). (1) Uniform California earthquake rupture forecast, UCERF3, run on TACC Stampede. (2) CyberShake ground motion prediction model 14.2, run on NCSA Blue Waters. (3) Dynamic rupture model including fractal fault roughness, run on XSEDE Kraken. (4) 3D velocity model for Southern California crust, CVM-S4.26, run on ALCF Mira. Model components include dynamic and kinematic fault rupture (DFR and KFR), anelastic wave propagation (AWP), nonlinear site response (NSR), and full-3D tomography (F3DT). Los Angeles SA-3s, 2% PoE in 50 years depth = 6 km

2. 1 2 2 3 4 CVM-S4.26BBP-1D Figure 2. Comparison of two seismic hazard models for the Los Angeles region from CyberShake Study 14.2, completed in early March, 2014. The left panel is based on an average 1D model, and the right panel is based on the F3DT-refined structure CVM-S4.26. The 3D model shows important amplitude differences from the 1D model, several of which are annotated on the right panel: (1) lower near-fault intensities due to 3D scattering; (2) much higher intensities in near-fault basins due to directivity-basin coupling; (3) higher intensities in the Los Angeles basins; and (4) lower intensities in hard-rock areas. The maps are computed for 3-s response spectra at an exceedance probability of 2% in 50 years. Both models include all fault ruptures in the Uniform California Earthquake Rupture Forecast, version 2 (UCERF2), and each comprises about 240 million seismograms.

3. Table 1. Measurements from four completed CyberShake hazard calculations showing continued improvements in each of three metrics. Core hours are counted as recommended by system operator at the time we used the system. Makespan is defined as wall-clock time to complete calculations, including all delays. Time to Solution is defined to include makespan plus setup and analysis time estimates. Measurements of our two earliest CyberShake studies are scaled up to the 1144 site scale used in 2013 and 2014.

4. Figure 3. Spatial distribution of the goodness-of-fit scores obtained from comparisons between three simulation sets and the signals recorded at 336 stations within the Los Angeles region.

5. Figure 4. Reduction in horizontal peak ground velocities (%) obtained for one nonlinear simulations of the ShakeOut scenario by Roten et al. (2014).

6. Figure 5: Topaware-assisted task placement on BW torus topology node allocation for AWP-ODC on 4,096 XE6 nodes showing continuous subnet in yellow slab along the fastest XZ plane, imagining the left most face wrap- around touching directly to the right-most face. (Visualization courtesy of NCSA BW staff O. Padron and G. Bauer).

7. Figure 6. Left: Scaling of SCEC HPC Applications. Weak scaling of AWP-ODC (sustained TFLOPS) on XK7, XE6 and HPS250. Right: Strong scaling of Hercules (wall clock time) on Kraken, Blue Waters and Mira. AWP-ODC is measured with 2.3 PFLOPS on XK7, and 653 TFLOPS on XE6. Benchmarks are based on variety of problem sizes.

8. Figure 7: Left, Wall clock time of Hercules on Kraken, Blue Waters and Mira; Right, Weak scaling of SORD on TACC Ranger, ANL Mira and Intrepid