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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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At least 73 records · Page 4

High Performance Computing Management: A Sustainable System Software Approach

The demand for high performance computing (HPC) resources continues to grow, driven by the increasing complexity of modeling and simulation, artificial intelligence (AI), and machine learning (ML) workloads [Porter]. The growing energy consumption demand of these HPC systems is a significant concern, both in terms of operational costs and environmental impact. AI hardware accelerators are expected to reach 1.5% of the world’s power consumption by 2029 [Shah].

97 - MATHEMATICS AND COMPUTING↗

Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software (Extended Analysis)

Tensor decomposition models play an increasingly important role in modern data science applications. One problem of particular interest is fitting a low-rank Canonical Polyadic (CP) tensor decomposition model when the tensor has sparse structure and the tensor elements are nonnegative count data. SparTen is a high-performance C++ library which computes a low-rank decomposition using different solvers: a first-order quasi-Newton or a second-order damped Newton method, along with the appropriate choice of runtime parameters. Since default parameters in SparTen are tuned to experimental results in prior published work on a single real-world dataset conducted using MATLAB implementations of these methods, it remains unclear if the parameter defaults in SparTen are appropriate for general tensor data. Furthermore, it is unknown how sensitive algorithm convergence is to changes in the input parameter values. This report addresses these unresolved issues with large-scale experimentation on three benchmark tensor data sets. Experiments were conducted on several different CPU architectures and replicated with many initial states to establish generalized profiles of algorithm convergence behavior.

97 MATHEMATICS AND COMPUTING↗

Performance portable ice-sheet modeling with MALI

High-resolution simulations of polar ice sheets play a crucial role in the ongoing effort to develop more accurate and reliable Earth system models for probabilistic sea-level projections. These simulations often require a massive amount of memory and computation from large supercomputing clusters to provide sufficient accuracy and resolution; therefore, it has become essential to ensure performance on these platforms. Many of today’s supercomputers contain a diverse set of computing architectures and require specific programming interfaces in order to obtain optimal efficiency. In an effort to avoid architecture-specific programming and maintain productivity across platforms, the ice-sheet modeling code known as MPAS-Albany Land Ice (MALI) uses high-level abstractions to integrate Trilinos libraries and the Kokkos programming model for performance portable code across a variety of different architectures. In this article, we analyze the performance portable features of MALI via a performance analysis on current CPU-based and GPU-based supercomputers. The analysis highlights not only the performance portable improvements made in finite element assembly and multigrid preconditioning within MALI with speedups between 1.26 and 1.82x across CPU and GPU architectures but also identifies the need to further improve performance in software coupling and preconditioning on GPUs. We perform a weak scalability study and show that simulations on GPU-based machines perform 1.24–1.92x faster when utilizing the GPUs. The best performance is found in finite element assembly, which achieved a speedup of up to 8.65x and a weak scaling efficiency of 82.6% with GPUs. We additionally describe an automated performance testing framework developed for this code base using a changepoint detection method. The framework is used to make actionable decisions about performance within MALI. We provide several concrete examples of scenarios in which the framework has identified performance regressions, improvements, and algorithm differences over the course of 2 years of development.

54 ENVIRONMENTAL SCIENCES↗

Then and Now: Improving Software Portability, Productivity, and 100× Performance

The US Exascale Computing Project (ECP) has succeeded in preparing applications to run efficiently on the first reported Exascale supercomputers in the world. To achieve this, it modernized the whole leadership software stack, from libraries to simulation codes. In this article, we contrast selected leadership software before and after ECP. We discuss how sustainable research software development for leadership computing can embrace the conversation with the hardware vendors, the leadership computing facilities, the software community, and the domain scientists who are the application developers and integrators of software products. We elaborate on how software needs to take portability as a central design principle and to benefit from interdependent teams; we also demonstrate how moving to programming languages with high momentum, like modern C++, can help improve the sustainability, interoperability, and performance of research software. Finally, we showcase how cross-institutional efforts can enable algorithm advances that are beyond incremental performance optimization.

97 MATHEMATICS AND COMPUTING↗

ExaCA v2.0: A versatile, scalable, and performance portable cellular automata application for additive manufacturing solidification

The previously established ExaCA software for performance portable alloy grain structure simulation has been updated to better represent the solidification behavior during complex alloy processing conditions, such as those encountered during metal additive manufacturing (AM), and for improved performance and scalability. Here, an extension to the time–temperature history input data format and the core ExaCA algorithm to include an arbitrary number of melting and solidification events yielded improved prediction of texture for various melt pool geometries, expanding the range of AM-relevant conditions that can be accurately simulated. Improved heat transport process simulation coupling, including the creation of large raster datasets from single track time–temperature history data and in-memory coupling with the new, performance portable finite difference code Finch, were also demonstrated in example studies on the effect of multilayer AM microstructure predictions on hatch spacing and cell size, respectively. Additional new features are detailed and demonstrated, including the ability to perform simulations using various interfacial response function forms, execute simulations on state-of-the-art hardware, improved usability through post-processing versatility, and improved strong and weak scaling performance. The performance, physics, and versatility improvements demonstrated here will further enable large-scale studies on AM process–microstructure relationships that were not previously possible. Furthermore, the usability improvements and ability to run coupled AM process–microstructure simulations using the Finch-ExaCA workflow will facilitate broader use of this open-source software by the computational materials community.

36 MATERIALS SCIENCE↗

Automated tracking of prefabricated components for areal-time evaluator to optimize and automateinstallation

Trade associations for prefabricated construction estimate that about 50% of prefabricated wall projects have alignment problems that lead to defects and rework. Additionally, component installation times average between 30 and 60 minutes per component. To address these issues, a real-time evaluator (RTE) system was introduced to decrease cost and automate prefabricated component installation by reducing the installation time, decreasing rework, and enhancing energy performance through higher installation quality. The RTE uses commonly available hardware and software to perform autonomous tracking to measure the real-time location and orientation of components as they are crane-lifted and installed. The hardware, software, and algorithms that allow the autonomous tracking of components are detailed. An algorithm to automate the initial search for a component with three attached retroreflectors is proposed. Algorithms to automate the measurement of component position and orientation are also proposed. Simple lab-scale proof-of-concept experiments were conducted to assess the algorithms for automation of component searching, measurement of real-time movement, and measurement of component orientation. With additional development, the system can be used as a tool to generate the commands for autonomous crane operation or single-task construction robots.

Hayes, Nolan↗

Toward performance-portable PETSc for GPU-based exascale systems

The Portable Extensible Toolkit for Scientific computation (PETSc) library delivers scalable solvers for nonlinear time-dependent differential and algebraic equations and for numerical optimization. The PETSc design for performance portability addresses fundamental GPU accelerator challenges and stresses flexibility and extensibility by separating the programming model used by the application from that used by the library, and it enables application developers to use their preferred programming model, such as Kokkos, RAJA, SYCL, HIP, CUDA, or OpenCL, on upcoming exascale systems. Furthermore, a blueprint for using GPUs from PETSc-based codes is provided, and case studies emphasize the flexibility and high performance achieved on current GPU-based systems.

97 MATHEMATICS AND COMPUTING↗

Defining a compact dry cooler design to reduce LCOE contribution in a CSP facility

Concentrating solar power (CSP), when coupled with a supercritical carbon dioxide (sCO 2 ) power cycle and sensible heat storage, presents a renewable and clean alternative for utility-scale power generation. However, in order to be competitive in the current and future markets, CSP facilities must limit their levelized cost of electricity (LCOE) by minimizing capital costs and reducing operating costs over the lifetime of the plant. Targeting this goal, this study investigates the LCOE impact of the power cycle pre-cooler. This study considers a compact dry cooler with micro-channel technology on the CO 2 side and formed fin geometry on the air side, using directly-coupled centrifugal fans and a transition duct to improve air distribution across the fins as well as protect the fins from contaminants which may cause blockage, soiling, fouling, and damage. In an effort to better understand the dry cooler impact on LCOE, a sensitivity study was conducted using various combinations of end-to-end approach temperatures, air-side pressure drop values, CO 2 -side pressure drop values, fan types, cooler turndown control schemes, cooler module sizes, and design-point ambient temperatures. Furthemore, off-design cycle performance data was calculated for each dry cooler design using NPSS simulation software; cycle performance data were then input to System Advisor Model (SAM) along with the associated capital costs for LCOE prediction of a 100 MW system over a 30 year plant lifetime. Results of this study show the LCOE is most sensitive to air-side performance, followed by heat transfer effectiveness and capital cost. It was found that a power cycle with a mid- to high-performance dry cooler will produce the most competitive power-production costs. Designing at the extreme ends for approach temperature (or effectiveness), design-point ambient temperature, and compactness (footprint) produce higher LCOE values; mid-range values for these parameters balance performance, operating costs, and associated capital cost to optimize LCOE.

14 SOLAR ENERGY↗

Uncertainty Analysis and Software Verification

Uncertainty analyses are an important part of calibrations and testing. They allow researchers insight on how to reduce and mitigate errors in testing. Each device used in testing introduces error in a system, as well as other sources such as environmental conditions, electronics, analog to digital, and random errors. Each source is carefully examined to identify how much error it introduces to a system. These sources are then combined using various methods of uncertainty calculations. To verify and validate software, a manual calculation is required to ensure the software is performing as intended. Using Excel to verify the calculations, we can identify discrepancies within the software. The root of the sum of the squares uncertainty (RSS) is used to find the combined uncertainty of a device at one and two standard deviations of the mean. Calibrations on accelerometers are performed using a vibration system along with a back-toback reference accelerometer. The vibration system takes a reference point at 100Hz frequency at 10g amplitude. The sensitivities are collected at each dialed in frequency. The sensitivity of the device represents the electrical output of the UUT (mV, pC, etc.) per unit of acceleration (g). The full history of sensitivities of selected accelerometers are used to find the averaged, standard deviation, and uncertainty of the device at each frequency tested. The uncertainty calculations from excel and the software are then compared.

97 MATHEMATICS AND COMPUTING↗

M-Star ® Software Test and Verification

Savannah River Mission Completion (SRMC) currently manages the risk for retained hydrogen in the Defense Waste Processing Facility (DWPF) vessels by implementing a Retained Hydrogen Program. The current program relies on Sludge Batch (SB) 8 Gas Chromatograph data and on conservative assumptions concerning gas release and retention to determine allowable vessel Quiescent time (Q-time). The authors identified M-Star ® CFD as a software that could simulate processes such as fluid flow, heat transfer, species transport, chemical reactions, particle transport, and retained hydrogen gas release. Preliminary simulation results suggest that more realistic assumptions on gas retention and release may be feasible for the DWPF retained hydrogen program. Because of the desire to use the M-Star ® software to perform analyses that support nuclear safety, SRMC has requested Savannah River National Laboratory (SRNL) to upgrade the software classification level of M-Star ® CFD from level D to level A to perform analyses that support nuclear safety.

08 HYDROGEN↗

ORNL Package Testing Program Software Quality Assurance Plan

The Oak Ridge National Laboratory (ORNL) Package Testing Program (PTP) uses commercial off-the-shelf (COTS) software in performing data collection of thermal test results for package designs that contain radioactive materials. Specifically, this software is used to collect temperature data from the furnace, packages, and ambient air to prepare and execute the thermal test specified in 10 CFR 71.73, “Thermal Test.” This software quality assurance (SQA) plan sets forth the guidelines, standards, and procedures that shall be used to provide SQA for PTP software applications. This is a living document that will be maintained for the lifecycle of the PTP program. The SQA plan follows the requirements set forth in ORNL Standards Based Management System (SBMS): Information Technology; Subject Area: Software Quality Assurance. When applicable to the requirements as described in ORNL SBMS, Software Quality Assurance, the software shall be listed in the ORNL Software Registration System (SRS). Exemptions to this SBMS are COTS and firmware that are not modified; spreadsheet applications and personal productivity tools that do not have a utility or safety application, research applications, legacy software, system software, vendor-supplied software used to interface with the vendor’s services, software used within the organization to facilitate processing or management of information, and software developed for applications not specific to the US Department of Energy (DOE).

97 MATHEMATICS AND COMPUTING↗