SEARCH · Engineering Papers

Results for “BFS”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

7 records

All sources NASA NTRS DOE OSTI

DOE OSTI2026

CORE-BFS: Communication-Optimized REctangular-partitioned BFS Achieving 160.845 TeraTEPS on Frontier Supercomputer

Distributed Breadth-First Search (BFS) is fundamental to many large-scale graph applications, but its performance on parallel systems is often limited by high communication overhead. This paper presents CORE-BFS, an extremely scalable GPU-based BFS implementation that introduces a unique rectangular 2D partitioning-based design for Frontier supercomputer. To further improve performance, we propose four key optimizations: (1) Rectangular 2D-partition specific data formats that use two compressed row and one compressed column status array bitmaps combined with a Double Compressed Sparse Row (DCSR) format per partition, reducing memory footprint and inter-rank traffic; (2) Adaptive frontier & communication strategy that unifies top-down and bottom-up traversal on the rectangular layout, uses lazy synchronization in top-down levels, and switches variants based on frontier size to minimize communication overhead; (3) Frontier-split degree-aware update that maps frontier vertices to thread-centric, wavefront-centric, and block-centric kernels based on their degree to improve GPU utilization and memory coalescing; (4) Row-reduction pipeline that overlaps bottom-up adjacency list processing with row-wise bitmap reduction to hide inter-rank latency. Together, these techniques increase parallelism while reducing memory and communication overhead. On the Graph500 benchmark, CORE - BFS scales up to 9,248 Frontier nodes with scale-42 graphs and reaches 160.845 TTEPS, delivering a 5.42 × speedup over our previous Frontier implementation.

Yang, Haoshen [Rutgers University]↗

DOE OSTI2025

AmeriFlux US-BFS Robert J. Bernard Biological Field Station

This is the AmeriFlux version of the carbon flux data for the site US-BFS Robert J. Bernard Biological Field Station. Site Description - The Bernard Field Station (BFS), an 86-acre academic resource of the Claremont University Consortium, is situated within the campus of The Claremont Colleges in Claremont, CA. Its principal habitats comprise coastal sage scrub, Riversidian alluvial fan scrub, live oak forest, and grassland. The eddy covariance tower is located in the 'neck' of the field station, home to a protected area of Coastal Sage Scrub, dominated by Artemisia californica. BFS is within walking distance of Harvey Mudd College, serving as an invaluable outdoor laboratory resource for the students. With extensive flora and fauna, including over 170 species of birds, 27 species of mammals, and more than 700 species of insects, it embodies a significant ecological haven in the region that is otherwise Southern California suburbs.

Kavassalis, Sarah [Harvey Mudd College]↗

DOE OSTI2024

Establish the basis for Breadth-First Search on Frontier System: XBFS on AMD GPUs

Graphics Processing Units (GPUs) offer significant potential for accelerating various computational tasks, including Breadth-First Search (BFS). Numerous efforts have been made to deploy BFS on GPUs effectively. To address the dynamic nature of BFS, XBFS, the state-of-the-art work, employs an adaptive strategy that leverages different optimized frontier queue generation designs, accommodating the varying characteristics of levels in BFS. While XBFS demonstrates excellent performance on NVIDIA Quadro P6000 GPUs, it faces challenges when deployed on AMD GPUs. In this work, we present our efforts to implement XBFS’s adaptive approach on Frontier, the most powerful supercomputer system, by porting XBFS to AMD MI250X GPUs. Through targeted optimizations tailored to the unique features of AMD GPUs, our implementation achieves an average performance of 43 Giga-Traversed Edges Per Second (GTEPS) per Graphics Compute Dies (GCD). Based on these results, we observe potential for surpassing the performance of the official Frontier results from the Graph500 benchmark released in June 2024.

Yang, Haoshen↗

DOE OSTI2025

Deep Neural Network Assisted Distributed Strain and Temperature Fiber Sensor System for Natural Gas Pipeline Monitoring

Natural gas pipeline integrity monitoring is crucial to detect potential leaks, find structural issues, and prevent environmental damage. This article presents a system of natural gas pipeline monitoring that uses a specialized double Brillouin peak sensing fiber along with the Brillouin optical time domain analysis (BOTDAs) technique. The calibrated sensing fiber coefficients for strain and temperature are 41.8 kHz/ με and 0.9 MHz/°C for peak 1; and 47.2 kHz/ με , and 1.11 MHz/°C for peak 2, respectively. Initially, lab tests were performed by installing a short section of double Brillouin peak fiber (DBPF) on a 1-in steel pipe under pressure up to 1000 per square inch (psi) at elevated temperatures. Simultaneous distributed measurements of temperature and pressure-induced hoop strain were successfully measured. Considering the long processing speed to extract Brillouin frequency shift (BFS), we employ a novel probabilistic deep neural network (PDNN) framework for rapid BFS prediction. Additionally, using the Finite Element Method, the effects of the pipeline pressure on hoop strain were modeled and compared to the experimental hoop strain under the same set of pipeline conditions. Finally, an actual 4-in outer diameter steel natural gas pipeline was used for pilot-scale tests, where hoop strain was measured at various pressure levels. Leaks were simulated to demonstrate accurate pipeline integrity monitoring. At an internal pipe pressure of 1000 psi, hoop strain of approximately 300 με was observed, and the sensitivity was calculated as 0.28 με /psi. The results of this pilot-scale study demonstrated that the system is capable of performing distributed monitoring sufficient to detect pipeline pressure and the presence of leaks to ensure the safe operation of gas pipelines in the field.

03 NATURAL GAS↗

DOE OSTI2025

Prediction of Silicon Content in a Blast Furnace via Machine Learning: A Comprehensive Processing and Modeling Pipeline

Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.

Chemistry↗

DOE OSTI2025

Radiation Accidents and Malicious Events – Scenarios and Scope of the Work of ICRP Task Group 120

The International Commission on Radiological Protection (ICRP) Task Group 120 (TG120) is developing ICRP recommendations for radiological protection for a wide range of radiation accidents and malicious events, complementing those given in ICRP Publication 146 (2020) for large nuclear accidents. The scope includes accidents involving criticalities, operating faults, and fires and explosions in nuclear facilities, inadvertent damage to sealed radiation sources, as well as malicious events, such as sabotage of nuclear facilities or materials, use of radiological dispersal devices, the contamination of food and drinking water supplies, and the deployment of nuclear weapons. A template has been designed to collate relevant information on a wide range of case studies and hypothetical malicious scenarios to ensure that the recommendations developed are broadly applicable and comprehensive. For all scenarios, a graded approach to protection is being taken, accepting that specific guidance may be required for some distinctive aspects, for example, protection during times of armed conflict. This paper provides an overview of the scenarios and scope of the work of TG120, including some of the radiological and non-radiological impacts of radiation emergencies, along the response and recovery timeline.

ICRP↗

DOE OSTI2025

The Systems of Radiological Protection for Ionizing and Non-Ionizing Radiation

This paper summarizes the presentations and panel discussion held at Plenary Session 1 of the 16th IRPA International Congress/69th Health Physics Society Annual Meeting, in Orlando, FL, in July 2024. Plenary Session 1 discussed the basics of the systems of radiological protection (RP) for ionizing radiation (IR) and non-ionizing radiation (NIR) and included five presentations and a panel discussion. Rodney Croft, Chair of the International Commission on Non-Ionizing Radiation Protection (ICNIRP), delivered the first presentation. Croft introduced the System of RP for NIR and provided an overview of ICNIRP’s coverage and current areas of work. Werner Rühm, Chair of the International Commission on Radiological Protection (ICRP), delivered the second presentation. He gave an overview of the System of RP for IR and covered the key principles of justification, optimization, and dose limitation, including the current plans of ICRP toward the envisaged revision of the System of RP. The third speaker, Sigurður Magnús Magnússon, from the International Radiation Protection Association (IRPA), provided the perspective of the RP professionals on the development of the Systems of RP for IR and NIR. Emilie van Deventer, from the World Health Organization (WHO), presented WHO’s views of both Systems of RP and discussed the relevant current activities of WHO with regard to IR and NIR. Kathryn Higley, President of the National Council on Radiation Protection and Measurements (NCRP), delivered the final presentation. Higley outlined the history of NCRP, the differences between ICRP and NCRP, and discussed the role of the NCRP in the System of RP, including NCRP’s role to analyze mechanisms of interaction of NIR with biological systems, including humans. The session concluded with a fruitful panel discussion, where the audience had the opportunity to ask the five invited speakers questions.

61 RADIATION PROTECTION AND DOSIMETRY↗