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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.
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Application of Benchmarked Kinetic Resistive Wall Mode Stability Codes to ITER, Including Additional Physics
Leading resistive wall mode (RWM) stability codes MARS-K [Y. Liu, et al., Phys. Plasmas 15, 112503 (2008)] and MISK [B. Hu, et al., Phys. Plasmas 12, 057301 (2005)] have been previously benchmarked. The benchmarking has now been extended to include additional physics, and used to project the stability of ITER in a realistic operating space. Due to ITER's relatively low plasma rotation and collisionality, collisions and non-resonance rotational effects were both found to have little impact on stability, and these non-resonance rotational effects also will not self-consistently affect the ITER RWM eigenfunction. Resonances between thermal ions and electrons and the expected level of ITER toroidal rotation were found to be important to stability, as were alpha particles, which are not in rotational resonance. MISK calculations show that without alpha particles, ITER is projected to be unstable to the RWM, but the expected level of alphas is calculated to provide a sufficient level of stability.
Quantum-Hardware Focused Application Performance Benchmarks (Final Technical Report)
Quantum computers promise to transform how we do scientific calculations. In this project, we benchmark different current quantum computers for solving chemistry problems and find ways to build noise-resilient implementations. We also use the characterization techniques developed to test ion trap quantum computers.
Scalable Application-Oriented Benchmarking of Quantum Computers
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Performance on Trinity (a Cray XC40) with Acceptance-Applications and Benchmarks.
Abstract not provided.
Performance on Trinity (a Cray XC40) with Acceptance-Applications and Benchmarks.
Abstract not provided.
Performance on Trinity (a Cray XC40) with Acceptance-Applications and Benchmarks.
Abstract not provided.
Performance on Trinity Phase 2 (a Cray XC40 utilizing Intel Xeon Phi processors) with Acceptance-Applications and Benchmarks.
Abstract not provided.
Performance on Trinity Phase 2 (a Cray XC40 utilizing Intel Xeon Phi processors) with Acceptance Applications and Benchmarks.
Abstract not provided.
Performance on Trinity Phase 2 (a Cray XC40 utilizing Intel Xeon Phi processors) with Acceptance Applications and Benchmarks.
Abstract not provided.
The ESIF-HPC-2 Benchmark Suite
We describe the development of the ESIF-HPC-2 benchmark suite, a collection of kernel and application benchmark codes for measuring computational and I/O performance from single nodes to full HPC systems that was used for acceptance testing in our recent HPC procurement. The configurations of the benchmarks used for our system is presented. We also describe a set of "dimensions" that can be used to classify benchmarks and assess coverage of a suite systematically. The collection is offered cost-free as a GitHub repository for general usage and further development.
The ESIF-HPC-2 Benchmark Suite: Preprint
We describe the development of the ESIF-HPC-2 benchmark suite, a collection of kernel and application benchmark codes for measuring computational and I/O performance from single nodes to full HPC systems that was used for acceptance testing in our recent HPC procurement. The configurations of the benchmarks used for our system is presented. We also describe a set of 'dimensions' that can be used to classify benchmarks and assess coverage of a suite systematically. The collection is offered cost-free as a GitHub repository for general usage and further development.
Uncertainty Quantification Techniques of SCALE/TSUNAMI
The Standardized Computer Analysis for Licensing Evaluation (SCALE) code system developed at Oak Ridge National Laboratory (ORNL) includes Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI). The TSUNAMI code suite can quantify the predicted change in system responses, such as k eff , reactivity differences, or ratios of fluxes or reaction rates, due to changes in the energy-dependent, nuclide-reaction-specific cross-section data. Where uncertainties in the neutron cross-section data are available, the sensitivity of the system to the cross-section data can be applied to propagate the uncertainties in the cross-section data to an uncertainty in the system response. Uncertainty quantification is useful for identifying potential sources of computational biases and highlighting parameters important to code validation. Traditional validation techniques often examine one or more average physical parameters to characterize a system and identify applicable benchmark experiments. However, with TSUNAMI correlation coefficients are developed by propagating the uncertainties in neutron cross-section data to uncertainties in the computed responses for experiments and safety applications through sensitivity coefficients. The bias in the experiments, as a function of their correlation coefficient with the intended application, is extrapolated to predict the bias and bias uncertainty in the application through trending analysis or generalized linear least squares techniques, often referred to as 'data adjustment.' Even with advanced tools to identify benchmark experiments, analysts occasionally find that the application models include some feature or material for which adequately similar benchmark experiments do not exist to support validation. For example, a criticality safety analyst may want to take credit for the presence of fission products in spent nuclear fuel. In such cases, analysts sometimes rely on 'expert judgment' to select an additional administrative margin to account for gap in the validation data or to conclude that the impact on the calculated bias and bias uncertainty is negligible. As a result of advances in computer programs and the evolution of cross-section covariance data, analysts can use the sensitivity and uncertainty analysis tools in the TSUNAMI codes to estimate the potential impact on the application-specific bias and bias uncertainty resulting from nuclides not represented in available benchmark experiments. This paper presents the application of methods described in a companion paper.
Synthetic Graph Generation for Data-Intensive HPC Benchmarking: Scalability, Analysis and Real-World Application
The benchmarking effort within the Extreme Scale Systems Center at Oak Ridge National Laboratory seeks to provide High Performance Computing benchmarks and test suites of interest to the DoD sponsor. The work described in this report is a part of the effort focusing on graph generation. A previously developed benchmark, SystemBurn, allows the emulation of a broad spectrum of application behavior profiles within a single framework. To complement this effort, similar capabilities are desired for graph-centric problems. This report described the in-depth analysis of the generated synthetic graphs' properties at a variety of scales using different generator implementations and examines their applicability to replicating real world datasets.
Data-driven analysis to understand GPU hardware resource usage of optimizations
With heterogeneous systems, the number of GPUs per chip increases to provide computational capabilities for solving science at a nanoscopic scale. However, low utilization for single GPUs defies the need to invest more money in expensive accelerators. Although related work develops optimizations to improve application performance, none studies how these optimizations impact hardware resource usage or average GPU utilization. Here, this paper takes a data-driven analysis approach in addressing this gap by (1) characterizing how hardware resource usage affects device utilization, execution time, or both, (2) presenting a multiobjective metric to identify important application-device interactions that can be optimized to improve device utilization and application performance jointly, (3) studying hardware resource usage behaviors of several optimizations for a benchmark application, and finally (4) identifying optimization opportunities for several scientific proxy applications based on their hardware resource usage behaviors. Furthermore, we demonstrate the applicability of our methodology by applying the identified optimizations to a proxy application, which improves the execution time, device utilization, and power consumption by up to 29.6%, 5.3% and 26.5% respectively.
Sensitivity Coefficients for Diffusion Coefficients and Other Reactor Physics Parameters using CE TSUNAMI-3D
The TSUNAMI (Tools for Sensitivity and Uncertainty Analysis Methodology Implementation) capabilities within the SCALE code system leverage sensitivity coefficients for many criticality safety applications, including quantifying the data-induced uncertainty in the eigenvalue of critical systems, quantifying computational biases, and selecting applicable benchmark experiments. TSUNAMI sensitivity and uncertainty analysis tools have traditionally been limited to criticality safety application spaces, but the introduction of Generalized Perturbation Theory (GPT) sensitivity methods by Jessee in 2009 and Perfetti in 2013 has extended the scope of SCALE adjoint-weighted sensitivity and uncertainty analysis to include reactor physics applications. The continuous-energy (CE) TSUNAMI-3D GPT sensitivity analysis methods were originally developed to calculate sensitivity coefficients for a limited number of reaction-rate responses using CE Monte Carlo methods. These tools were recently applied in an Oak Ridge National Laboratory (ORNL)-directed research and development project to improve the efficiency of {sup 252}Cf production in the High Flux Isotope Reactor (HFIR) by understanding the sensitivity of key heavy actinide capture-to- fission ratios to potential system design changes. This work further extends the applicability of the CE TSUNAMI- 3D GPT methods to reactor physics applications by enabling the calculation of sensitivity coefficients for an expanded set of reaction rate responses-including a first-ever capability for conducting sensitivity analysis of neutron diffusion coefficients.
Gaussian Process Optimization of Sensitivity-Based Similarity Metrics between New Nuclear Applications and New/Existing Benchmarks
Confidently designing safe, new nuclear criticality experiments requires expert judgement, which could take years of experience. Sensitivity/uncertainty (S/U) analysis can be utilized by less experienced individuals to conservatively estimate uncertainties in important parameters, such as k eff , in newly proposed nuclear applications. This type of analysis relies on matching new nuclear applications with existing benchmark experiments. The Whisper-1.1 software package included in MCNP6.2 ®1 contains more than 1,100 International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmarks. These benchmarks however rarely match new nuclear applications. The number of benchmarks available to match a given set of materials or geometric configurations varies significantly. Furthermore, recently performed benchmark experiments may not have had enough time to be properly documented and published. Benchmarks are vital for determining the accuracy of nuclear data and can assist nuclear physics and evaluators in improving nuclear data libraries. Exhaustively exploring the parameter space using simulations with software such as MCNP is too computationally expensive. In this work, Gaussian process optimization was implemented to reduce the number of simulations needed for optimization over multiple parameters. This optimization scheme was designed to selectively generate new benchmarks with high sensitivity-based similarity metrics to user-defined nuclear applications. Two benchmark models of spherically nested shells containing plutonium, uranium, tantalum, and water were used in the optimization to match an application containing plutonium plates, stacked in a tantalum reflector, surrounded by water.
Participation in and Assessment of the Third DNCSH Public Workshop
Advanced reactor development and deployment is introducing fuel forms, materials, and configurations that differ from those used in traditional light-water reactors (LWRs), including tristructural-isotropic (TRISO)-based fuels, moderators, high-temperature materials, and compact core designs. These attributes can fall outside the range of applicability of existing criticality safety validation bases and may require additional work in code validation and benchmark applicability.