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At least 163 records · Page 9

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NASA NTRS2010

Development of a Benchmark Example for Delamination Fatigue Growth Prediction

The development of a benchmark example for cyclic delamination growth prediction is presented and demonstrated for a commercial code. The example is based on a finite element model of a Double Cantilever Beam (DCB) specimen, which is independent of the analysis software used and allows the assessment of the delamination growth prediction capabilities in commercial finite element codes. First, the benchmark result was created for the specimen. Second, starting from an initially straight front, the delamination was allowed to grow under cyclic loading in a finite element model of a commercial code. The number of cycles to delamination onset and the number of cycles during stable delamination growth for each growth increment were obtained from the analysis. In general, good agreement between the results obtained from the growth analysis and the benchmark results could be achieved by selecting the appropriate input parameters. Overall, the results are encouraging but further assessment for mixed-mode delamination is required

Krueger, Ronald↗

NASA NTRS2010

Development of a Benchmark Example for Delamination Fatigue Growth Prediction

Krueger, Ronald↗

NASA NTRS1984

Automated benchmark generation based upon a specification language

The problem of validating and verifying digital flight control system (DFCS) software is addressed in this paper. A new specification language DIVERS is proposed, and is the keystone of the approach. This language consists of keywords where each keyword represents an element in the block diagram of a DFCS. DIVERS has a dictionary which contains all the keywords a DFCS designer might need. Translator programs convert the system specifications into an executable, high-level language program. The features of translators are discussed and are elucidated by examples. This language is used to describe a typical flight software module.

Rajan, N.↗

DOE OSTI2024

Democratizing uncertainty quantification

Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In this paper, we introduce UM-Bridge (the UQ and Modeling Bridge), a high-level abstraction and software protocol that facilitates universal interoperability of UQ software with simulation codes. It breaks down the technical complexity of advanced UQ applications and enables separation of concerns between experts. UM-Bridge democratizes UQ by allowing effective interdisciplinary collaboration, accelerating the development of advanced UQ methods, and making it easy to perform UQ analyses from prototype to High Performance Computing (HPC) scale. In addition, we present a library of ready-to-run UQ benchmark problems, all easily accessible through UM-Bridge. These benchmarks support UQ methodology research, enabling reproducible performance comparisons. We demonstrate UM-Bridge with several scientific applications, harnessing HPC resources even using UQ codes not designed with HPC support.

Benchmarks↗

DOE OSTI2020

Characterizing Output Bottlenecks of a Production Supercomputer: Analysis and Implications

This article studies the I/O write behaviors of the Titan supercomputer and its Lustre parallel file stores under production load. The results can inform the design, deployment, and configuration of file systems along with the design of I/O software in the application, operating system, and adaptive I/O libraries.We propose a statistical benchmarking methodology to measure write performance across I/O configurations, hardware settings, and system conditions. Moreover, we introduce two relative measures to quantify the write-performance behaviors of hardware components under production load. In addition to designing experiments and benchmarking on Titan, we verify the experimental results on one real application and one real application I/O kernel, XGC and HACC IO, respectively. These two are representative and widely used to address the typical I/O behaviors of applications.In summary, we find that Titan’s I/O system is variable across the machine at fine time scales. This variability has two major implications. First, stragglers lessen the benefit of coupled I/O parallelism (striping). Peak median output bandwidths are obtained with parallel writes to many independent files, with no striping or write sharing of files across clients (compute nodes). I/O parallelism is most effective when the application—or its I/O libraries—distributes the I/O load so that each target stores files for multiple clients and each client writes files on multiple targets in a balanced way with minimal contention. Second, our results suggest that the potential benefit of dynamic adaptation is limited. In particular, it is not fruitful to attempt to identify “good locations” in the machine or in the file system: component performance is driven by transient load conditions and past performance is not a useful predictor of future performance. For example, we do not observe diurnal load patterns that are predictable.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1997

Parallel supercomputing with commodity components

We have implemented a parallel computer architecture based entirely upon commodity personal computer components. Using 16 Intel Pentium Pro microprocessors and switched fast ethernet as a communication fabric, we have obtained sustained performance on scientific applications in excess of one Gigaflop. During one production astrophysics treecode simulation, we performed 1.2 x 10(sup 15) floating point operations (1.2 Petaflops) over a three week period, with one phase of that simulation running continuously for two weeks without interruption. We report on a variety of disk, memory and network benchmarks. We also present results from the NAS parallel benchmark suite, which indicate that this architecture is competitive with current commercial architectures. In addition, we describe some software written to support efficient message passing, as well as a Linux device driver interface to the Pentium hardware performance monitoring registers.

Performance↗

NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

The development of the Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large complex systems engineering challenge being addressed in part by focusing on the specific subsystems handling of off-nominal mission and fault tolerance. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML), the Mission and Fault Management (M&FM) algorithms are crafted and vetted in specialized Integrated Development Teams composed of multiple development disciplines. NASA also has formed an M&FM team for addressing fault management early in the development lifecycle. This team has developed a dedicated Vehicle Management End-to-End Testbed (VMET) that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. The flexibility of VMET enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the algorithms utilizing actual subsystem models. The intent is to validate the algorithms and substantiate them with performance baselines for each of the vehicle subsystems in an independent platform exterior to flight software test processes. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test processes. Risk reduction is addressed by working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and detection and responses that can be tested in VMET and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM. The plan for VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Trevino, Luis↗

NASA NTRS1998

Automated Generation of Message-Passing Programs: An Evaluation of CAPTools using NAS Benchmarks

Scientists at NASA Ames Research Center have been developing computational aeroscience applications on highly parallel architectures over the past ten years. During the same time period, a steady transition of hardware and system software also occurred, forcing us to expand great efforts into migrating and receding our applications. As applications and machine architectures continue to become increasingly complex, the cost and time required for this process will become prohibitive. Various attempts to exploit software tools to assist and automate the parallelization process have not produced favorable results. In this paper, we evaluate an interactive parallelization tool, CAPTools, for parallelizing serial versions of the NAB Parallel Benchmarks. Finally, we compare the performance of the resulting CAPTools generated code to the hand-coded benchmarks on the Origin 2000 and IBM SP2. Based on these results, a discussion on the feasibility of automated parallelization of aerospace applications is presented along with suggestions for future work.

Hribar, Michelle R.↗

NASA NTRS1989

Robust performance of multiple tasks by a mobile robot

While there have been many successful mobile robot experiments, only a few papers have addressed issues pertaining to the range of applicability, or robustness, of robotic systems. The purpose of this paper is to report results of a series of benchmark experiments done to determine and quantify the robustness of an integrated hardware and software system of a mobile robot.

Beckerman, Martin↗

NASA NTRS2007

Feasibility of Turing-Style Tests for Autonomous Aerial Vehicle "Intelligence"

A new approach is suggested to define and evaluate key metrics as to autonomous aerial vehicle performance. This approach entails the conceptual definition of a "Turing Test" for UAVs. Such a "UAV Turing test" would be conducted by means of mission simulations and/or tailored flight demonstrations of vehicles under the guidance of their autonomous system software. These autonomous vehicle mission simulations and flight demonstrations would also have to be benchmarked against missions "flown" with pilots/human-operators in the loop. In turn, scoring criteria for such testing could be based upon both quantitative mission success metrics (unique to each mission) and by turning to analog "handling quality" metrics similar to the well-known Cooper-Harper pilot ratings used for manned aircraft. Autonomous aerial vehicles would be considered to have successfully passed this "UAV Turing Test" if the aggregate mission success metrics and handling qualities for the autonomous aerial vehicle matched or exceeded the equivalent metrics for missions conducted with pilots/human-operators in the loop. Alternatively, an independent, knowledgeable observer could provide the "UAV Turing Test" ratings of whether a vehicle is autonomous or "piloted." This observer ideally would, in the more sophisticated mission simulations, also have the enhanced capability of being able to override the scripted mission scenario and instigate failure modes and change of flight profile/plans. If a majority of mission tasks are rated as "piloted" by the observer, when in reality the vehicle/simulation is fully- or semi- autonomously controlled, then the vehicle/simulation "passes" the "UAV Turing Test." In this regards, this second "UAV Turing Test" approach is more consistent with Turing s original "imitation game" proposal. The overall feasibility, and important considerations and limitations, of such an approach for judging/evaluating autonomous aerial vehicle "intelligence" will be discussed from a theoretical perspective.

Young, Larry A.↗

NASA NTRS2017

Trade Study: Storing NASA HDF5/netCDF-4 Data in the Amazon Cloud and Retrieving Data Via Hyrax Server Data Server

This study explored three candidate architectures with different types of objects and access paths for serving NASA Earth Science HDF5 data via Hyrax running on Amazon Web Services (AWS). We studied the cost and performance for each architecture using several representative Use-Cases. The objectives of the study were: Conduct a trade study to identify one or more high performance integrated solutions for storing and retrieving NASA HDF5 and netCDF4 data in a cloud (web object store) environment. The target environment is Amazon Web Services (AWS) Simple Storage Service (S3). Conduct needed level of software development to properly evaluate solutions in the trade study and to obtain required benchmarking metrics for input into government decision of potential follow-on prototyping. Develop a cloud cost model for the preferred data storage solution (or solutions) that accounts for different granulation and aggregation schemes as well as cost and performance trades.We will describe the three architectures and the use cases along with performance results and recommendations for further work.

AWS cost↗

NASA NTRS2017

Task 28: Web Accessible APIs in the Cloud Trade Study

This study explored three candidate architectures for serving NASA Earth Science Hierarchical Data Format Version 5 (HDF5) data via Hyrax running on Amazon Web Services (AWS). We studied the cost and performance for each architecture using several representative Use-Cases. The objectives of the project are: Conduct a trade study to identify one or more high performance integrated solutions for storing and retrieving NASA HDF5 and Network Common Data Format Version 4 (netCDF4) data in a cloud (web object store) environment. The target environment is Amazon Web Services (AWS) Simple Storage Service (S3).Conduct needed level of software development to properly evaluate solutions in the trade study and to obtain required benchmarking metrics for input into government decision of potential follow-on prototyping. Develop a cloud cost model for the preferred data storage solution (or solutions) that accounts for different granulation and aggregation schemes as well as cost and performance trades.

cost model↗

NASA NTRSDate not supplied

Machine Learning Airport Surface Model

Future needs of the National Airspace System require decision support tools to adopt a service-oriented architecture in alignment with the FAA’s vision for an Info-Centric NAS. To achieve this, many existing systems will need to undergo a digital transformation from a monolithic decision support tool to a service-oriented architecture where individual services are exposed through well defined Application Programming Interfaces (APIs). To enable this transformation, NASA has developed the Digital Information Platform as a cloud based foundation for development of aviation services with a special focus towards Artificial Intelligence and Machine Learning (ML) services. This paper describes the work required for the transformation of NASA’s legacy surface management system to a real-time ML based decision support system deployed in the cloud. Details of the Machine Learning Operations (MLOps) infrastructure and best practices are described which enabled the end-toend lifecycle management of ML within an integrated software system. Validation results are provided from an operational field evaluation where performance was benchmarked against the legacy approach.

Jeremy Coupe↗

DOE OSTI2025

Packaging HEP Heterogeneous Mini-apps for Portable Benchmarking and Facility Evaluation on Modern HPCs

High Energy Physics (HEP) experiments are making increasing use of GPUs and GPU dominated High Performance Computer facilities. Both the software and hardware of these systems are rapidly evolving, creating challenges for experiments to make informed decisions as to where they wish to devote resources. In its first phase, the High Energy Physics Center for Computational Excellence (HEP-CCE) produced portable versions of a number of heterogeneous HEP mini-apps, such as p2r, FastCaloSim, Patatrack and the WireCell Toolkit, that exercise a broad range of GPU characteristics, enabling cross platform and facility benchmarking and evaluation. However, these miniapps still require a significant amount of manual intervention to deploy on a new facility. We present our work in developing turn-key deployments of these mini-apps, where by means of containerization and automated configuration and build techniques such as Spack, we are able to quickly test new hardware, software, environments and entire facilities with minimal user intervention, and then track performance metrics over time.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Packaging HEP Heterogeneous Mini-apps for Portable Benchmarking and Facility Evaluation on Modern HPCs

High Energy Physics (HEP) experiments are making increasing use of GPUs and GPU dominated High Performance Computer facilities. Both the software and hardware of these systems are rapidly evolving, creating challenges for experiments to make informed decisions as to where they wish to devote resources. In its first phase, the High Energy Physics Center for Computational Excellence (HEP-CCE) produced portable versions of a number of heterogeneous HEP mini-apps, such as \ptor, FastCaloSim, Patatrack and the WireCell Toolkit, that exercise a broad range of GPU characteristics, enabling cross platform and facility benchmarking and evaluation. However, these mini-apps still require a significant amount of manual intervention to deploy on a new facility. We present our work in developing turn-key deployments of these mini-apps, where by means of containerization and automated configuration and build techniques such as Spack, we are able to quickly test new hardware, software, environments and entire facilities with minimal user intervention, and then track performance metrics over time.

Atif, Mohammad [Brookhaven] (ORCID:000000026889770↗

DOE OSTI2023

Nuclear Criticality Safety Integral Experiment Covariance Determination

Integral benchmarks for criticality safety and nuclear data validation require expensive uncertainty quantification studies. Commonly, the uncertainty quantification ignores correlations between experiments that share components. Experiments such as the TEX (Thermal/Epithermal eXperiments) campaigns consist of many shared parts, such as fuel, which create a strong correlation in their uncertainties. While these correlations are known to exist, they are often not estimated due to the complexity of such calculations. This paper describes a software package that uses an intuitive method of determining the covariance for each of the experimental components, providing a correlation matrix for each family of parts across the multiple cases examined within a benchmark. The code uses the TEX-HEU campaign as a proof of concept, and we show that the correlations can be calculated with information commonly found in ICSBEP (International Criticality Safety Benchmark Evaluation Project) benchmarks. The estimated covariances are used in χ 2 trending studies to evaluate their impact on nuclear data validation. Without covariances, χ 2 per degree of freedom was calculated as 2.203 and with covariances it was 1.179. The difference shows that omitting covariance information may cause overly pessimistic bias quantifications. The covariance determination code can be easily integrated into current benchmark evaluations as well as reevaluating legacy benchmark uncertainties. Uncertainty correlation calculations should become the baseline for criticality safety integral experiment benchmarks and can now be easily calculated with the described software package.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Nuclear Criticality Safety Integral Experiment Covariance Determination

Integral benchmarks for criticality safety and nuclear data validation require expensive uncertainty quantification studies. Commonly, the uncertainty quantification ignores correlations between experiments that share components. Experiments such as the TEX (Thermal/Epithermal eXperiments) campaigns consist of many shared parts between experiments, such as fuel, which creates a strong correlation in their errors. While these correlations are known to exist, they are often not estimated due to the complexity of such calculations. This paper describes a software package that uses an intuitive method of determining the covariance for each of the experimental components, providing a correlation matrix for each family of parts across the multiple cases examined within a benchmark. The code uses the TEX-HEU campaign as a proof of concept, and we show that the correlations can be calculated with information commonly found in ICSBEP (International Criticality Safety Benchmark Evaluation Project) benchmarks. The estimated covariances are used in χ 2 trending studies to evaluate their impact on nuclear data validation. The covariance determination code can be easily integrated into current benchmark evaluations as well as reevaluating legacy benchmark uncertainties. Uncertainty correlation calculations should become the baseline for criticality safety integral experiment benchmarks and can now be easily calculated with the described software package.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Bragg Spot Finder (BSF): a new machine-learning-aided approach to deal with spot finding for rapidly filtering diffraction pattern images

Macromolecular crystallography contributes significantly to understanding diseases and, more importantly, how to treat them by providing atomic resolution 3D structures of proteins. This is achieved by collecting X-ray diffraction images of protein crystals from important biological pathways. Spotfinders are used to detect the presence of crystals with usable data, and the spots from such crystals are the primary data used to solve the relevant structures. Having fast and accurate spot finding is essential, but recent advances in synchrotron beamlines used to generate X-ray diffraction images have brought us to the limits of what the best existing spotfinders can do. This bottleneck must be removed so spotfinder software can keep pace with the X-ray beamline hardware improvements and be able to see the weak or diffuse spots required to solve the most challenging problems encountered when working with diffraction images. In this paper, we first present Bragg Spot Detection (BSD), a large benchmark Bragg spot image dataset that contains 304 images with more than 66 000 spots. We then discuss the open source extensible U-Net-based spotfinder Bragg Spot Finder (BSF), with image pre-processing, a U-Net segmentation backbone, and post-processing that includes artifact removal and watershed segmentation. Finally, we perform experiments on the BSD benchmark and obtain results that are (in terms of accuracy) comparable to or better than those obtained with two popular spotfinder software packages ( Dozor and DIALS ), demonstrating that this is an appropriate framework to support future extensions and improvements.

36 MATERIALS SCIENCE↗