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At least 1,315 records · Page 73

Integrating Energy-Efficient Computing with Computational Research to Accelerate Energy Technology

NREL's computational sciences center hosts the largest high performance computing (HPC) capabilities dedicated to energy research while functioning as a living laboratory for energy-efficient computing. NREL's HPC capabilities support the research needs of the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In ten years of operation, HPC use in EERE-sponsored research has grown by a factor of 30, including work in electricity generation, energy efficiency, transportation, and energy system modeling. This paper analyzes this research portfolio, providing examples of individual use cases. The paper documents NREL's history of operating one of the world's most energy-efficient data centers while examining pathways to reduce economic and environmental impact beyond reduction of Power Usage Efficiency (PUE). This paper concludes by examining the unique opportunities created for accelerating improvements in data center efficiency created by combining an HPC system dedicated to energy research and a research program in energy-efficient computing.

97 MATHEMATICS AND COMPUTING↗

PyFaults: A Python Toolkit for Stacking Fault Screening

PyFaults is an open-source Python library designed to model stacking fault disorder in crystalline materials and qualitatively assess the characteristic selective broadening effects in powder X-ray diffraction (PXRD). Here, the main capabilities of PyFaults are presented, including unit cell and supercell model construction, PXRD pattern calculation, assessment against experimental PXRD, and methods for rapid screening of candidate models within a set of possible stacking vectors and fault occurrence probabilities. This program aims to serve as a computationally inexpensive tool for identifying and screening potential stacking fault models in materials with planar disorder. Three diverse case studies, involving GaN, Li2MnO3 and Li3YCl6, are presented to illustrate the program functionality across a range of structure types and stacking fault modalities.

MATHEMATICS AND COMPUTING↗

Magnetizability and rotational g tensors for density fitted local second-order Møller-Plesset perturbation theory using gauge-including atomic orbitals

In this paper, we present theory and implementation of an efficient program for calculating magnetizabilities and rotational g tensors of closed-shell molecules at the level of local second-order Møller-Plesset perturbation theory (MP2) using London orbitals. Density fitting is employed to factorize the electron repulsion integrals with ordinary Gaussians as fitting functions. The presented program for the calculation of magnetizabilities and rotational g tensors is based on a previous implementation of NMR shielding tensors reported by S. Loibl and M. Schütz [J. Chem. Phys. 137, 084107 (2012)]. Extensive test calculations show (i) that the errors introduced by density fitting are negligible, and (ii) that the errors of the local approximation are still rather small, although larger than for nuclear magnetic resonance (NMR) shielding tensors. Electron correlation effects for magnetizabilities are tiny for most of the molecules considered here. MP2 appears to overestimate the correlation contribution of magnetizabilities such that it does not constitute an improvement over Hartree-Fock (when comparing to higher-order methods like CCSD(T)). For rotational g tensors the situation is different and MP2 provides a significant improvement in accuracy over Hartree-Fock. The computational performance of the new program was tested for two extended systems, the larger comprising about 2200 basis functions. It turns out that a magnetizability (or rotational g tensor) calculation takes about 1.5 times longer than a corresponding NMR shielding tensor calculation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

S4PST: Sustainability for Programming Systems and Tools: May Workshop Report

The US Department of Energy (DOE) Exascale Computing Project (ECP) has fostered and strengthened the use of modern software engineering practices for developing applications and libraries, and this effort has resulted in the coordinated and interoperable E4S1 and xSDK2 ecosystems. Although this approach is cost-effective, it relies on robust programming systems and tools (PST) as the underlying foundation for our HPC software. At present, our primary PST stack consists of traditional high-performance computing (HPC) languages, namely Fortran, C, C++, and the popular Python language for data analysis and AI workflows. These languages support various programming frameworks and run-time abstractions that enable parallelism and concurrency across multiple node architectures and thousands of nodes through a variety of interconnect systems. However, to accommodate users’ diverse needs, certain aspects of the HPC ecosystem are delegated to vendor-specific or third-party implementations that extend beyond a particular scientific domain. This broader scope results in a multitude of specifications and variations, which leads to a complex orchestration of many-ecosystems. Unfortunately, this complexity in the ecosystem imposes additional overhead costs on consumers during the latter stages of the development cycle. In addition to the software ecosystem challenge, the upcoming conclusion of the ECP by December 2023 has raised significant concerns within the HPC programming systems community, from both the economic and social perspectives. The ECP has implemented a management structure for software development and funding decisions across all ECP participants by following a conventional hierarchical and centralized approach. However, this structure has prompted certain considerations within the community, particularly in anticipation of the Software Sustainability initiative by the DOE’s Advanced Scientific Computing Research Program (ASCR). For the success of this new initiative, it is of utmost importance to secure consistent funding and foster close engagement with researchers and core developers of existing programming-system products. This collaboration is vital to maintaining the critical capabilities of the current software during the transition phase while proactively adapting to future technology and workforce trends. The community recognizes the significance of adapting to emerging trends and is aware of the inherent fragility of the HPC software ecosystem, particularly in relation to programming systems that cater to all users. The ability to adapt and evolve is essential to staying relevant and effectively addressing these technical, economic, and social challenges. The S4PST team, which represents one of the six ASCR Software Sustainability seedling projects, is dedicated to tackling these challenges through community-based approaches that go beyond the scope of the DOE. This involves collaboration between national laboratories with academia, non-DOE institutions, hardware and system vendors, and international partners. By fostering these partnerships, we aim to create a robust and sustainable HPC software ecosystem that can effectively meet the needs of the community. This new community effort, driven by the eight DOE labs, will take on the responsibility of guiding funding decisions for programming-systems development and maintenance with transparency and consistency across all decisions. Additionally, the team will offer common technical services to the programming systems community, irrespective of their funding situations, and facilitate community-wide incubation to proactively nurture the software ecosystem. By actively engaging with stakeholders and employing a collaborative approach, we can collectively shape the future of programming systems and ensure a robust and thriving HPC software landscape. On May 11–12, 2023, the S4PST team conducted its inaugural kick-off workshop at the Innovative Computing Laboratory (ICL) in the University of Tennessee, Knoxville, hosted by Hartwig Anzt. The workshop encompassed various sessions dedicated to presentations and discussions, with the aim of comprehending the team members’ perspectives on the vision of software sustainability. Additionally, the workshop aimed to identify the technical, economic, and social requirements for sustaining the programming-systems community in the field of HPC. This report provides a summary of the S4PST effort by highlighting five major thrust areas discussed during the workshop: (i) community, (ii) technical support, (iii) training and diversity, (iv) verification, validation and correctness, and (v) emerging technologies. It also encompasses an overview of the presentations and discussions held throughout the event, our views and potential synergies with other seedling efforts, along with the outcomes and key takeaways from our initial discussions.

97 MATHEMATICS AND COMPUTING↗

Improvement of the prediction of surface ozone concentration over conterminous U.S. by a computationally efficient second-order Rosenbrock solver in CAM4-Chem

The global chemistry-climate model (CAM4-Chem) overestimates the surface ozone concentration over the conterminous U.S. (CONUS). Reasons for this positive bias include emission, meteorology, chemical mechanism, and solver. In this study, we explore the last possibility by examining the sensitivity to the numerical methods for solving the chemistry equations. A second-order Rosenbrock (ROS-2) solver is implemented in CAM4-Chem to examine its influence on the surface ozone concentration and the computational performance of the chemistry program. Results show that under the same time step size (1800 s), statistically significant reduction of positive bias is achieved by the ROS-2 solver. The improvement is as large as 5.2 ppb in Eastern U.S. during summer season. The ROS-2 solver is shown to reduce the positive bias in Europe and Asia as well, indicating the lower surface ozone concentration over the CONUS predicted by the ROS-2 solver is not a trade-off consequence with increasing the ozone concentration at other global regions. In addition, by refining the time step size to 180 s, the first-order implicit solver does not provide statistically significant improvement of surface ozone concentration. It reveals that the better prediction from the ROS-2 solver is not only due to its accuracy but also due to its suitability for stiff chemistry equations. As an added benefit, the computation cost of the ROS-2 solver is almost half of first-order implicit solver. The improved computational efficiency of the ROS-2 solver is due to the reuse of the Jacobian matrix and lower upper (LU) factorization during its multistage calculation.

54 ENVIRONMENTAL SCIENCES↗

Accuracies of the synthesized monochromatic CT numbers and effective atomic numbers obtained with a rapid kVp switching dual energy CT scanner

Purpose: This study was performed to investigate the accuracies of the synthesized monochromatic images and effective atomic number maps obtained with the new GE Discovery CT750 HD CT scanner. Methods: A Gammex-RMI model 467 tissue characterization phantom and the CT number linearity section of a Phantom Laboratory Catphan 600 phantom were scanned using the dual energy (DE) feature on the GE CT750 HD scanner. Synthesized monochromatic images at various energies between 40 and 120 keV and effective atomic number (Z{sub eff}) maps were generated. Regions of interest were placed within these images/maps to measure the average monochromatic CT numbers and average Z{sub eff} of the materials within these phantoms. The true Z{sub eff} values were either supplied by the phantom manufacturer or computed using Mayneord's equation. The linear attenuation coefficients for the true CT numbers were computed using the NIST XCOM program with the input of manufacturer supplied elemental compositions and densities. The effects of small variations in the assumed true densities of the materials were also investigated. Finally, the effect of body size on the accuracies of the synthesized monochromatic CT numbers was investigated using a custom lumbar section phantom with and without an external fat-mimicking ring. Results: Other than the Z{sub eff} of the simulated lung inserts in the tissue characterization phantom, which could not be measured by DECT, the Z{sub eff} values of all of the other materials in the tissue characterization and Catphan phantoms were accurate to 15%. The accuracies of the synthesized monochromatic CT numbers of the materials in both phantoms varied with energy and material. For the 40-120 keV range, RMS errors between the measured and true CT numbers in the Catphan are 8-25 HU when the true CT numbers were computed using the nominal plastic densities. These RMS errors improve to 3-12 HU for assumed true densities within the nominal density {+-}0.02 g/cc range. The RMS errors between the measured and true CT numbers of the tissue mimicking materials in the tissue characterization phantom over the 40-120 keV range varied from about 6 HU-248 HU and did not improve as dramatically with small changes in assumed true density. Conclusions: Initial tests indicate that the Z{sub eff} values computed with DECT on this scanner are reasonably accurate; however, the synthesized monochromatic CT numbers can be very inaccurate, especially for dense tissue mimicking materials at low energies. Furthermore, the synthesized monochromatic CT numbers of materials still depend on the amount of the surrounding tissues especially at low keV, demonstrating that the numbers are not truly monochromatic. Further research is needed to develop DE methods that produce more accurate synthesized monochromatic CT numbers.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SU-E-T-49: A Multi-Institutional Study of Independent Dose Verification for IMRT

Purpose: AAPM TG114 does not cover the independent verification for IMRT. We conducted a study of independent dose verification for IMRT in seven institutes to show the feasibility. Methods: 384 IMRT plans in the sites of prostate and head and neck (HN) were collected from the institutes, where the planning was performed using Eclipse and Pinnacle3 with the two techniques of step and shoot (S&S) and sliding window (SW). All of the institutes used a same independent dose verification software program (Simple MU Analysis: SMU, Triangle Product, Ishikawa, JP), which is Clarkson-based and CT images were used to compute radiological path length. An ion-chamber measurement in a water-equivalent slab phantom was performed to compare the doses computed using the TPS and an independent dose verification program. Additionally, the agreement in dose computed in patient CT images between using the TPS and using the SMU was assessed. The dose of the composite beams in the plan was evaluated. Results: The agreement between the measurement and the SMU were −2.3±1.9 % and −5.6±3.6 % for prostate and HN sites, respectively. The agreement between the TPSs and the SMU were −2.1±1.9 % and −3.0±3.7 for prostate and HN sites, respectively. There was a negative systematic difference with similar standard deviation and the difference was larger in the HN site. The S&S technique showed a statistically significant difference between the SW. Because the Clarkson-based method in the independent program underestimated (cannot consider) the dose under the MLC. Conclusion: The accuracy would be improved when the Clarkson-based algorithm should be modified for IMRT and the tolerance level would be within 5%.

60 APPLIED LIFE SCIENCES↗

Hydropower Biological Evaluation Toolset (HBET) Version 3.0: User Guide

The Hydropower Biological Evaluation Tools (HBET) software package, developed by Pacific Northwest National Laboratory (PNNL), is designed to assemble, organize, and process data collected by Sensor Fish and live fish. HBET enable users to characterize the hydraulic conditions of hydropower structures and estimate fish injury and mortality rates from various stressors. Future updates of the software may support other technologies, such as bead tracking in physical models and computational fluid dynamics. The HBET program can be customized to analyze different hydraulic applications, including turbines, spillways, weirs, pumped storage, and other user-defined functions, and therefore, help researchers, turbine designers, hydropower operators, and regulators better evaluate hydropower structures regarding their environmental sustainability and cost-effectiveness. Added content to the user guide about the new feature for predicting absolute injury rates.

13 HYDRO ENERGY↗

Three Dimensional Simulations of Multiphase Flows Using a Lattice Boltzmann Method Suitable for High Density Ratios - 12126

Multiphase flows involving gas and liquid phases can be observed in engineering operations at various Department of Energy sites, such as mixing of slurries using pulsed-air mixers and hydrogen gas generation in liquid waste tanks etc. The dynamics of the gas phase in the liquid domain play an important role in the mixing effectiveness of the pulsed-air mixers or in the level of gas pressure build-up in waste tanks. To understand such effects, computational fluid dynamics methods (CFD) can be utilized by developing a three-dimensional computerized multiphase flow model that can predict accurately the behavior of gas motion inside liquid-filled tanks by solving the governing mathematical equations that represent the physics of the phenomena. In this paper, such a CFD method, lattice Boltzmann method (LBM), is presented that can model multiphase flows accurately and efficiently. LBM is favored over traditional Navier-Stokes based computational models since interfacial forces are handled more effectively in LBM. The LBM is easier to program, more efficient to solve on parallel computers, and has the ability to capture the interface between different fluid phases intrinsically. The LBM used in this paper can solve for the incompressible and viscous flow field in three dimensions, while at the same time, solve the Cahn-Hillard equation to track the position of the gas-liquid interface specifically when the density and viscosity ratios between the two fluids are high. This feature is of primary importance since the previous LBM models proposed for multiphase flows become unstable when the density ratio is larger than 10. The ability to provide stable and accurate simulations at large density ratios becomes important when the simulation case involves fluids such as air and water with a density ratio around 1000 that are common to many engineering problems. In order to demonstrate the capability of the 3D LBM method at high density ratios, a static bubble simulation is conducted to solve for the pressure difference between the inside and outside of a gas bubble in a liquid domain. Once the results show that the method is in agreement with the Laplace law, buoyant bubble simulations are conducted. The initial results obtained for bubble shape during the rising process was found to be in agreement with the theoretical expectations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Chapter 6: Abuse Response of Batteries Subjected to Mechanical Impact

Electrochemical and thermal models to simulate nominal performance and abuse response of lithium-ion cells and batteries have been reported widely in the literature. Studies on mechanical failure of cell components and how such events interact with the electrochemical and thermal response are relatively less common. This chapter outlines a framework developed under the Computer Aided Engineering for Batteries program to couple failure modes resulting from external mechanical loading to the onset and propagation of electrochemical and thermal events that follow. Starting with a scalable approach to implement failure criteria based on thermal, mechanical, and electrochemical thresholds, we highlight the practical importance of these models using case studies at the cell and module level. The chapter also highlights a few gaps in our understanding of the comprehensive response of batteries subjected to mechanical crash events, the stochastic nature of some of these failure events, and our approach to build safety maps that help improve robustness of battery design by capturing the sensitivity of some key design parameters to heat generation rates under different mitigation strategies.

abuse simulations↗

An update on modeling land-ice/ocean interactions in CESM

This talk is an update on ongoing land-ice/ocean coupling work within the Community Earth System Model (CESM). The coupling method is designed to allow simulation of a fully dynamic ice/ocean interface, while requiring minimal modification to the existing ocean model (the Parallel Ocean Program, POP). The method makes use of an immersed boundary method (IBM) to represent the geometry of the ice-ocean interface without requiring that the computational grid be modified in time. We show many of the remaining development challenges that need to be addressed in order to perform global, century long climate runs with fully coupled ocean and ice sheet models. These challenges include moving to a new grid where the computational pole is no longer at the true south pole and several changes to the coupler (the software tool used to communicate between model components) to allow the boundary between land and ocean to vary in time. We discuss benefits for ice/ocean coupling that would be gained from longer-term ocean model development to allow for natural salt fluxes (which conserve both water and salt mass, rather than water volume).

58 GEOSCIENCES↗

Complementary Study of Radiative Heat Transfer and Flow Physics from Moderate-scale Hydrocarbon Pool Fire Simulations

As part of the Advanced Simulation and Computing Verification and Validation (ASCVV) program, a 0.3-m diameter hydrocarbon pool fire with multiple fuels was modeled and simulated. In the study described in this report, systematic examination was performed on the radiation model used in a series of coupled Fuego/Nalu simulations. A calibration study was done with a medium-scale methanol pool fire and the effect of calibration traced throughout the radiation model. This analysis provided a more detailed understanding of the effect of radiation model parameters on each other and on other quantities in the simulations. Heptane simulation results were also examined using this approach and possible areas for further improvement of the models were identified. The effect of soot on radiative losses was examined by comparing heptane and methanol results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Development of a one-stop beam verification system using electronic portal imaging devices for routine quality assurance

In this study, a computer-based system for routine quality assurance (QA) of a linear accelerator (linac) was developed by using the dosimetric properties of an amorphous silicon electronic portal imaging device (EPID). An acrylic template phantom was designed such that it could be placed on the EPID and be aligned with the light field of the collimator. After irradiation, portal images obtained from the EPID were transferred in DICOM format to a computer and analyzed using a program we developed. The symmetry, flatness, field size, and congruence of the light and radiation fields of the photon beams from the linac were verified simultaneously. To validate the QA system, the ion chamber and film (X-Omat V2; Kodak, New York, NY) measurements were compared with the EPID measurements obtained in this study. The EPID measurements agreed with the film measurements. Parameters for beams with energies of 6 MV and 15 MV were obtained daily for 1 month using this system. It was found that our QA tool using EPID could substitute for the film test, which is a time-consuming method for routine QA assessment.

61 RADIATION PROTECTION AND DOSIMETRY↗

A Verified Optimizer for Quantum Circuits

We present VOQC, the first verified optimizer for quantum circuits, written using the Coq proof assistant. Quantum circuits are expressed as programs in a simple, low-level language called SQIR, a small quantum intermediate representation, which is deeply embedded in Coq. Optimizations and other transformations are expressed as Coq functions, which are proved correct with respect to a semantics of SQIR programs. SQIR programs denote complex-valued matrices, as is standard in quantum computation, but we treat matrices symbolically to reason about programs that use an arbitrary number of quantum bits. SQIR’s careful design and our provided automation make it possible to write and verify a broad range of optimizations in VOQC, including full-circuit transformations from cutting-edge optimizers.

97 MATHEMATICS AND COMPUTING↗

NVL-C: Static Analysis Techniques for Efficient, Correct Programming of Non-Volatile Main Memory Systems

Computer architecture experts expect that non-volatile memory (NVM) hierarchies will play a more significant role in future systems including mobile, enterprise, and HPC architectures. With this expectation in mind, we present NVL-C: a novel programming system that facilitates the efficient and correct programming of NVM main memory systems. The NVL-C programming abstraction extends C with a small set of intuitive language features that target NVM main memory, and can be combined directly with traditional C memory model features for DRAM. We have designed these new features to enable compiler analyses and run-time checks that can improve performance and guard against a number of subtle programming errors, which, when left uncorrected, can corrupt NVM-stored data. Moreover, to enable recovery of data across application or system failures, these NVL-C features include a flexible directive for specifying NVM transactions. So that our implementation might be extended to other compiler front ends and languages, the majority of our compiler analyses are implemented in an extended version of LLVM's intermediate representation (LLVM IR). We evaluate NVL-C on a number of applications to show its flexibility, performance, and correctness.

Denny, Joel↗

An Early Quantum Computing Proposal

The D-Wave 2X is the third generation of quantum processing created by D-Wave. NASA (with Google and USRA) and Lockheed Martin (with USC), both own D-Wave systems. Los Alamos National Laboratory (LANL) purchased a D-Wave 2X in November 2015. The D-Wave 2X processor contains (nominally) 1152 quantum bits (or qubits) and is designed to specifically perform quantum annealing, which is a well-known method for finding a global minimum of an optimization problem. This methodology is based on direct execution of a quantum evolution in experimental quantum hardware. While this can be a powerful method for solving particular kinds of problems, it also means that the D-Wave 2X processor is not a general computing processor and cannot be programmed to perform a wide variety of tasks. It is a highly specialized processor, well beyond what NNSA currently thinks of as an “advanced architecture.”A D-Wave is best described as a quantum optimizer. That is, it uses quantum superposition to find the lowest energy state of a system by repeated doses of power and settling stages. The D-Wave produces multiple solutions to any suitably formulated problem, one of which is the lowest energy state solution (global minimum). Mapping problems onto the D-Wave requires defining an objective function to be minimized and then encoding that function in the Hamiltonian of the D-Wave system. The quantum annealing method is then used to find the lowest energy configuration of the Hamiltonian using the current D-Wave Two, two-level, quantum processor. This is not always an easy thing to do, and the D-Wave Two has significant limitations that restrict problem sizes that can be run and algorithmic choices that can be made. Furthermore, as more people are exploring this technology, it has become clear that it is very difficult to come up with general approaches to optimization that can both utilize the D-Wave and that can do better than highly developed algorithms on conventional computers for specific applications. These are all fundamental challenges that must be overcome for the D-Wave, or similar, quantum computing technology to be broadly applicable.

97 MATHEMATICS AND COMPUTING↗

SciPy 1.0: fundamental algorithms for scientific computing in Python

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

97 MATHEMATICS AND COMPUTING↗