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The Gordon Bell-winning AWP-ODC application continues to push the boundaries of earthquake simulation by leveraging the enhanced performance of MVAPICH on both CPU and GPU based architectures. This presentation highlights the recent improvements to the code and its application to broadband deterministic 3D wave propagation simulations of earthquake ground motions, incorporating high-resolution surface topography and detailed underground structures. The results of these simulations provide critical insights into the potential impacts of major earthquakes, contributing to more effective disaster preparedness and mitigation strategies. Additionally, the presentation will address the scientific and technical challenges encountered during the process and discuss the implications for future large-scale seismic studies on Exascale computing systems. 

The ShakeOut simulations of a M7.8 earthquake on the southern San Andreas fault (2008) studies predicted unexpectedly large ground motions throughout Southern California due to waveguide e#ects from interconnected sedimentary basins in 3D velocity model. Here, we re-examine the ground motion predictions from the ShakeOut scenario using the most recent updates on the velocity models and the realistic surface topography from the Digital Elevation Model. The exceptional scalability and performance of the AWP-ODC due to the most recent advancements allows for examination of plenty earth models including the irregular surface topography at low computational cost. 

We have ported and verified the topography version of AWP-ODC, with discontinuous mesh feature enabled, to HIP so that it runs on AMD MI250X GPUs. 103.3% parallel efficiency was benchmarked on Frontier between 8 and 4,096 nodes or up to 32,768 GCDs. Frontier is a two exaflop/s computing system based on the AMD Radeon Instinct GPUs and EPYC CPUs, a Leadership Computing Facility at Oak Ridge National Laboratory (ORNL). This HIP topography code has been used in the production runs on Frontier, a primary computing engine currently utilizing the 2024 SCEC INCITE allocation, a 700K node-hours supercomputing time award. Furthermore, we implemented ROCm-Aware GPU direct support in the topo code, and demonstrated 14% additional reduction in time-to-solution up to 4,096 nodes. The AWP-ODC-Topo code is also tuned on TACC Vista, an Arm-based NVIDIA GH200 Grace Hopper Superchip, with excellent performance demonstrated. This poster will demonstrate the studies of weak scaling and the performance characteristics on GPUs. We discuss the efforts of verifying the ROCm-Aware development, and utilizing high-performance MVAPICH libraries with the on-the-fly compression on modern GPU clusters. 

Artificial intelligence (AI) tools and technologies are increasingly prevalent in society. Many teens interact with AI devices on a daily basis but often have a limited understanding of how AI works, as well as how it impacts society more broadly. It is critical to develop youths’ understanding of AI, cultivate ethical awareness, and support diverse youth in pursuing computer science to help ensure future development of more equitable AI technologies. Here, we share our experiences developing and remotely facilitating an interdisciplinary AI ethics program for secondary students designed to increase teens’ awareness and understanding of AI and its societal impacts. Students discussed stories with embedded ethical dilemmas, engaged with AI media and simulations, and created digital products to express their stance on an AI ethics issue. Across four iterations in formal and informal settings, we found students to be engaged in AI stories and invested in learning about AI and its societal impacts. Short stories were effective in raising awareness, focusing discussion and supporting students in developing a more nuanced understanding of AI ethics issues, such as fairness, bias and privacy. 

Introduction: Spheroids show great promise in being a better model for testing treatments for cancer in vitro when compared to monolayer cells. Single photon imaging of spheroids is limited by depth. Due to this reason, two photon imaging is necessary to obtain a full image of the spheroid. We developed a software that can evaluate the cellular metabolism of a spheroid by calculating the Redox Index (NADH divided by FAD). We tried to validate this software by treating the spheroids with an ATP antagonist.