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Germann, Timothy C.

Publications and source records attributed to Germann, Timothy C..

At least 19 records

ECP libraries and tools: An overview

The Exascale Computing Project (ECP) Software Technology and Co-Design teams addressed the growing complexities in high-performance computing (HPC) by developing scalable software libraries and tools that leverage exascale system capabilities. As we enter the exascale era, the need for reusable, optimized software solutions that can handle the unique challenges posed by these systems becomes increasingly important. The primary challenges the ECP teams faced were to create software libraries and tools that are performant on exascale architectures and portable and usable across diverse hardware platforms. Efforts addressed issues related to concurrent execution, memory management, and the integration of heterogeneous computing resources, such as GPUs from multiple vendors. The ECP’s strategy involved a structured development process encompassing the creation, optimization, and deployment of software in collaboration with industry, academia, and national laboratories. The project was organized into several technical areas: co-design of domain-specific suites with target applications, programming models and runtimes, development tools, mathematical libraries, data and visualization tools, and software ecosystem and delivery mechanisms. ECP has successfully developed a large portfolio of software libraries and tools that demonstrate significant improvements in performance and scalability on exascale systems. These products have been integrated into the Department of Energy’s computing facilities, supporting various scientific applications and ensuring robust performance across different hardware setups. ECP advancements in software development for exascale computing highlight the importance of a collaborative and adaptive approach to handling next-generation HPC systems complexities. The lessons learned emphasize the need for continuous engagement with end-users and vendors, and the importance of maintaining a balance between innovation and practical implementation. Future efforts will focus on ensuring scalability, keeping pace with rapid hardware advancements, and further enhancing the interoperability and usability of the software ecosystem. In conclusion, subsequent articles in this special issue provide in-depth discussions and case studies into specific library and tool efforts.

97 MATHEMATICS AND COMPUTING↗

High pressure suppression of plasticity due to an overabundance of shear embryo formation

Abstract High pressure shear band formation is a critical phenomenon in energetic materials due to its influence on both mechanical strength and mechanochemical activation. While shear banding is known to occur in a variety of these materials, the governing dynamics of the mechanisms are not well defined for molecular crystals. We conduct molecular dynamics simulations of shock wave induced shear band formation in the energetic material 1,3,5-trinitroperhydro-1,3,5-triazine (RDX) to assess shear band nucleation processes. We find, that at high pressures, the initial formation sites for shear bands, “embryos”, form in excess and rapidly lower deviatoric stresses prior to shear band formation and growth. This results in the suppression of plastic deformation. A local cluster analysis is used to quantify and contrast this mechanism with a more typical shear banding seen at lower pressures. These results demonstrate a mechanism that is reversible in nature and that supersedes shear band formation at increased pressures. We anticipate that these results will have a broad impact on the modeling and development of high-strain rate application materials such as those for high explosives and hypersonic systems.

36 MATERIALS SCIENCE↗

Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure

Disease surveillance systems allow public health agencies to respond to emerging diseases before they become widespread. Developing such systems requires identifying optimal ways to monitor in the context of an epidemic outbreak; this problem is known as sensor selection. Contact networks represent the dynamics of interaction in a population and are used to model how a disease spreads in a population and to explore strategies of sensor selection. We evaluated five sensor selection strategies on their ability to provide an early warning of a COVID-like outbreak in synthetic contact networks encapsulated in four network scenarios. Three of these scenarios assessed different aspects of community structure. The fourth scenario employed a contact network representing the population and interactions of 6.8 million people in New York City, constructed from an agent-based simulation using census and transportation data. This scenario exemplifies how sensor selection strategies may perform in a real-world, urban context. Our findings suggest that the choice of the optimal strategy depends heavily on the community structure of the network. Strategies that select highly connected nodes or maximize network coverage are the optimal surveillance strategy for outbreak detection in many network community structures. However, a naive implementation of these strategies may fail to provide an early warning at all—including in the New York City scenario. Moreover, these methods are impractical for real-world use as they require knowledge of the underlying contact network. Instead, a selection strategy that starts with a set of random nodes and then performs a random walk through a chain of neighbors reliably provides early warnings without requiring prior knowledge of the network. We find this method, called “random chain”, to be the most pragmatic for implementation in a real-world disease surveillance context.

60 APPLIED LIFE SCIENCES↗

Pore‐Scale Modeling of Carbon Dioxide and Hydrogen Transport During Geologic Gas Storage

Abstract Geologic storage of CO 2 and H 2 are climate‐positive techniques for meeting the energy transition. While similar formations could be considered for both gases, the flow dynamics could differ due to differences in their thermophysical properties. We conduct a rigorous pore‐scale study of water/CO 2 and water/H 2 systems at relevant reservoir conditions in a Bentheimer rock sample using the lattice Boltzmann method to quantify the effects of capillary, viscous, inertial, and wetting forces during gas invasion. At similar conditions, H 2 invasion is weaker compared to CO 2 due to unfavorable viscosity ratios. Increasing flow rate, however, increases the breakthrough saturation for both gas systems in the range of capillary numbers studied. At isolated conditions of flow rate, viscosity ratio, and wettability, local inertial effects are found to be critical and show consistent increase in the invaded gas saturation. The effect of inertial forces persits for both gases across all field conditions tested.

58 GEOSCIENCES↗

Cost effectiveness of preemptive school closures to mitigate pandemic influenza outbreaks of differing severity in the United States

Background: Nonpharmaceutical interventions (NPIs) may be considered as part of national pandemic preparedness as a first line defense against influenza pandemics. Preemptive school closures (PSCs) are an NPI reserved for severe pandemics and are highly effective in slowing influenza spread but have unintended consequences. Methods: We used results of simulated PSC impacts for a 1957-like pandemic (i.e., an influenza pandemic with a high case fatality rate) to estimate population health impacts and quantify PSC costs at the national level using three geographical scales, four closure durations, and three dismissal decision criteria (i.e., the number of cases detected to trigger closures). At the Chicago regional level, we also used results from simulated 1957-like, 1968-like, and 2009-like pandemics. Our net estimated economic impacts resulted from educational productivity costs plus loss of income associated with providing childcare during closures after netting out productivity gains from averted influenza illness based on the number of cases and deaths for each mitigation strategy. Results: For the 1957-like, national-level model, estimated net PSC costs and averted cases ranged from $\$7.5$ billion (2016 USD) averting 14.5 million cases for two-week, community-level closures to $\$97$ billion averting 47 million cases for 12-week, county-level closures. We found that 2-week school-by-school PSCs had the lowest cost per discounted life-year gained compared to county-wide or school district–wide closures for both the national and Chicago regional-level analyses of all pandemics. The feasibility of spatiotemporally precise triggering is questionable for most locales. Theoretically, this would be an attractive early option to allow more time to assess transmissibility and severity of a novel influenza virus. However, we also found that county-wide PSCs of longer durations (8 to 12 weeks) could avert the most cases (31–47 million) and deaths (105,000–156,000); however, the net cost would be considerably greater ($\$88$-$\$103$ billion net of averted illness costs) for the national-level, 1957-like analysis. Conclusions: We found that the net costs per death averted ($\$180,000$-$\$4.2$ million) for the national-level, 1957-like scenarios were generally less than the range of values recommended for regulatory impact analyses ($\$4.6$ to 15.0 million). This suggests that the economic benefits of national-level PSC strategies could exceed the costs of these interventions during future pandemics with highly transmissible strains with high case fatality rates. In contrast, the PSC outcomes for regional models of the 1968-like and 2009-like pandemics were less likely to be cost effective; more targeted and shorter duration closures would be recommended for these pandemics.

60 APPLIED LIFE SCIENCES↗

Predictive scale-bridging simulations through active learning

Throughout computational science, there is a growing need to utilize the continual improvements in raw computational horsepower to achieve greater physical fidelity through scale-bridging over brute-force increases in the number of mesh elements. For instance, quantitative predictions of transport in nanoporous media, critical to hydrocarbon extraction from tight shale formations, are impossible without accounting for molecular-level interactions. Similarly, inertial confinement fusion simulations rely on numerical diffusion to simulate molecular effects such as non-local transport and mixing without truly accounting for molecular interactions. With these two disparate applications in mind, we develop a novel capability which uses an active learning approach to optimize the use of local fine-scale simulations for informing coarse-scale hydrodynamics. Our approach addresses three challenges: forecasting continuum coarse-scale trajectory to speculatively execute new fine-scale molecular dynamics calculations, dynamically updating coarse-scale from fine-scale calculations, and quantifying uncertainty in neural network models.

97 MATHEMATICS AND COMPUTING↗

Application Results on Early Exascale Hardware

This Exascale Computing Project (ECP) milestone report summarizes the status of 27 of the 31 ECP Applications Development (AD) subprojects at the end of FY21. In November and December of 2021, a comprehensive assessment of AD projects was conducted by the ECP leadership along with external subject matter experts (SMEs). (NNSA application projects are reviewed separately using the ASC milestone process.) The AD review committee—consisting of the AD lead, AD deputy, Level 3 (L3), and at least one external project SME—was tasked with evaluating each project’s progress relative to ECP project goals specified in the FY21 timeline. Key areas of focus were code maturity and performance on pre-exascale systems, an in-depth analysis of final key performance parameter (KPP) verification contracts, and future R&D priorities in the final year of ECP and beyond. As such, this report contains not only an accurate snapshot of each subproject’s current status but also represents a broad account of successes and challenges in porting large scientific applications to DOE’s next-generation high-performance computing architectures – the Frontier and Aurora systems.

97 MATHEMATICS AND COMPUTING↗

Crack nucleation at forging flaws studied by non-local peridynamics simulations

We present a computational study and framework that allows us to study and understand the crack nucleation process from forging flaws. Forging flaws may be present in large steel rotor components commonly used for rotating power generation equipment including gas turbines, electrical generators, and steam turbines. The service life of these components is often limited by crack nucleation and subsequent growth from such forging flaws, which frequently exhibit themselves as non-metallic oxide inclusions. The fatigue crack growth process can be described by established engineering fracture mechanics methods. However, the initial crack nucleation process from a forging flaw is challenging for traditional engineering methods to quantify as it depends on the details of the flaw, including flaw morphology. We adopt the peridynamics method to describe and study this crack nucleation process. For a specific industrial gas turbine rotor steel, we present how we integrate and fit commonly known base material property data such as elastic properties, yield strength, and S-N curves, as well as fatigue crack growth data into a peridynamic model. The obtained model is then utilized in a series of high-performance two-dimensional peridynamic simulations to study the crack nucleation process from forging flaws for ambient and elevated temperatures in a rectangular simulation cell specimen. The simulations reveal an initial local nucleation at multiple small oxide inclusions followed by micro-crack propagation, arrest, coalescence, and eventual emergence of a dominant micro-crack that governs the crack nucleation process. The dependence on temperature and density of oxide inclusions of both the details of the microscopic processes and cycles to crack nucleation is also observed. The results are compared with fatigue experiments performed with specimens containing forging flaws of the same rotor steel.

97 MATHEMATICS AND COMPUTING↗

Crack nucleation from non-metallic inclusions in aluminum alloys described by peridynamics simulations

Conventional engineering methods oftentimes have challenges in the quantification of crack nucleation processes from manufacturing defects that are relevant for engineering component lifing. In this work, we present peridynamic simulation framework for the description of the crack nucleation process from cluster of non-metallic inclusions in aluminum alloys. Our non-local simulation framework characterizes crack nucleation process as multiple micro-crack nucleation events from individual inclusions, and eventually one micro-crack dominates. We define individual stages of the crack nucleation process, i.e., nucleation, micro-crack, technical, and crack initiation, that allow a quantification and meta model development of both the individual stages and the entire crack nucleation process.

36 MATERIALS SCIENCE↗

Performance Portability in the Exascale Computing Project: Exploration Through a Panel Series

Performance portability is a critical issue for the Exascale Computing Project (ECP) because of nontrivial architectural differences between machines available today and those expected at exascale. Many ECP project teams are working toward performance portability, and would expect to benefit from sharing lessons learned, identifying gaps, and discovering opportunities for partnerships. To facilitate this communication, the IDEAS-ECP project partnered with the three focus areas of ECP (application development, software technology, and hardware and integration), and Department of Energy computing facilities, to lead a series of panel discussions on performance portability. The panels were organized around broadly common themes of algorithmic and data locality challenges. In this article, we describe the panel series, its objectives, and perspectives from the various areas of the project. Finally, we also discuss use cases that are distinctive, as well as conclusions drawn from the collective experience of the participants.

97 MATHEMATICS AND COMPUTING↗

A survey of software implementations used by application codes in the Exascale Computing Project

The US Department of Energy Office of Science and the National Nuclear Security Administration initiated the Exascale Computing Project (ECP) in 2016 to prepare mission-relevant applications and scientific software for the delivery of the exascale computers starting in 2023. The ECP currently supports 24 efforts directed at specific applications and six supporting co-design projects. These 24 application projects contain 62 application codes that are implemented in three high-level languages—C, C++, and Fortran—and use 22 combinations of graphical processing unit programming models. The most common implementation language is C++, which is used in 53 different application codes. The most common programming models across ECP applications are CUDA and Kokkos, which are employed in 15 and 14 applications, respectively. This article provides a survey of the programming languages and models used in the ECP applications codebase that will be used to achieve performance on the future exascale hardware platforms.

97 MATHEMATICS AND COMPUTING↗

Map Applications to Target Exascale Architecture with Machine-Specific Performance Analysis, Including Challenges and Projections

This Exascale Computing Project (ECP) milestone report summarizes the status of all 30 ECP Applications Development (AD) subprojects at the end of FY20. In October and November of 2020, a comprehensive assessment of AD projects was conducted by the ECP leadership. Reviews occurred virtually between October 27, 2020 and November 12, 2020. The review committee—consisting of the AD lead, deputy, and L3—was tasked with evaluating each subproject’s progress in porting their codes to early exascale architectures considered precursors to the planned exascale machines. This includes characterizing which modules have been ported to multi-accelerator nodes, initial performance analyses, the status of software integration, and a current vision of successes, obstacles, and next steps. As such, this report contains not only an accurate snapshot of each subproject’s current status but also represents an unprecedentedly broad account of experiences in porting large scientific applications to next-generation high-performance computing architectures.

97 MATHEMATICS AND COMPUTING↗

School dismissal as a pandemic influenza response: When, where and for how long?

We used individual-based computer simulation models at community, regional and national levels to evaluate the likely impact of coordinated pre-emptive school dismissal policies during an influenza pandemic. Such policies involve three key decisions: when, over what geographical scale, and how long to keep schools closed. Our evaluation includes uncertainty and sensitivity analyses, as well as model output uncertainties arising from variability in serial intervals and presumed modifications of social contacts during school dismissal periods. During the period before vaccines become widely available, school dismissals are particularly effective in delaying the epidemic peak, typically by 4–6 days for each additional week of dismissal. Assuming the surveillance is able to correctly and promptly diagnose at least 5–10% of symptomatic individuals within the jurisdiction, dismissals at the city or county level yield the greatest reduction in disease incidence for a given dismissal duration for all but the most severe pandemic scenarios considered here. Broader (multi-county) dismissals should be considered for the most severe and fast-spreading (1918-like) pandemics, in which multi-month closures may be necessary to delay the epidemic peak sufficiently to allow for vaccines to be implemented.

59 BASIC BIOLOGICAL SCIENCES↗