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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Algorithmic and GPU enhancements for molecular dynamics in Cabana and LAMMPS

The focus of this milestone was to implement and test new algorithms and optimizations for improved GPU performance by molecular dynamics (MD) and related particle codes. The work was done in the CoPA Cabana library, the CabanaMD mini-app which uses Cabana to implement and benchmark prototypical MD models, and the LAMMPS MD code which is used by the ECP EXAALT project as well as for materials modeling generally. Efforts included (a) implementation of new or optimized algorithms for fundamental MD kernels like neighbor-list building and FFTs which are also widely used in other particle methods, (b) performance testing of data structure layouts for both simple pairwise and computationally intense neural network potentials, (c) optimizations aimed at improving GPU performance for models with small atom counts, and (d) optimizations specific to the SNAP interatomic potential due to its importance for the EXAALT project.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Analysis of Tank 38H (HTF-38-22-31, -32) and Tank 43H (HTF-43-22-33, -34) Samples for Support of the Enrichment Control and Corrosion Control Programs

SRNL analyzed samples from Tank 38H and Tank 43H to support ECP and CCP. The results indicate the concentrations of most soluble species in the Tank 38H surface sample increased from the previous surface sample. The Tank 38H sub-surface sample shows changes in concentration for soluble species in the solution with some increasing and some decreasing. The current Tank 38H sub-surface sample contains less sludge solids than the previous sample based on visual appearance. The small differences in the concentrations of major components between the Tank 38H surface and sub-surface samples indicate only minimal stratification of solution species within the tank.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Simulating Atmospheric Boundary Layer Turbulence with Nek5000/RS

We present large-eddy-simulation (LES) modeling approaches for the simulation of atmospheric boundary layer turbulence that are of direct relevance to wind energy production. In this report, we study a GABLS benchmark problem using high-order spectral element code Nek5000/RS, which is supported under the DOE’s Exascale Computing Project (ECP) Center for Efficient Exascale Discretizations (CEED) project, targeting application simulations on various acceleration-device based exascale computing platforms [1, 2]. We demonstrate our newly developed subgrid-scale (SGS) models based on high-pass filter (HPF), mean-field eddy viscosity (MFEV), and Smagorinsky (SMG) with no-slip and traction boundary conditions, provided with low-order statistics, convergence and turbulent structure analysis. The model fidelity and scaling performance of Nek5000/RS on DOE’s leadership computing platforms in comparison to those of AMR-Wind, a block-structured second-order finite-volume code with adaptive-mesh-refinement capabilities, are discussed in [3].

17 WIND ENERGY↗
DOE OSTI2022

Nek5000/RS Performance on Advanced GPU Architectures

We demonstrate NekRS performance results on various advanced GPU architectures. NekRS is a GPU-accelerated version of Nek5000 that is targeting high performance on forthcoming exascale platforms. It is being developed in DOE’s Center of Efficient Exascale Discretizations (CEED), which is one of the co-design centers under the Exascale Computing Project (ECP). In this report, we consider Frontier, Crusher, Spock, Polaris, Perlmutter, ThetaGPU and Summit. Simulations are performed using ExaSMR’s 17x17 rod-bundle geometries with different problem sizes. The report focuses on strong scaling performance and analysis. Many of the results shown in this report are the outcome from participation in the ALCF GPU Hackathon on Polaris, which was held on 7/19/22, and 7/26–7/28/22. Members of the Nek5000/RS team included Misun Min, Yu-Hsiang Lan, Paul Fischer and Thilina Rathnayake. Mentors were Kris Rowe (ALCF) and Peng Wang (NVIDIA). Also presented in this report are results on Frontier, which were obtained in collaboration with John Holmen at OLCF.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Analysis of Tank 38H (HTF-38-22-91, -92) and Tank 43H (HTF-43-22-93, -94) Samples for Support of the Enrichment Control and Corrosion Control Programs

SRNL analyzed samples from Tank 38H and Tank 43H to support ECP and CCP. The results indicate the concentrations of most soluble species in the Tank 38H surface sample increased slightly from the previous surface sample. The Tank 38H sub-surface sample shows changes in concentration for soluble species in the solution with some increasing and some decreasing. The current Tank 38H sub-surface sample contains more sludge solids than the previous sample based on visual appearance. The small differences in the concentrations of major components between the Tank 38H surface and sub-surface samples indicate only minimal stratification of solution species within the tank. The Tank 43H surface and sub-surface samples are similar in composition to the previous samples. The similar solution compositions measured in the Tank 43H surface and sub-surface samples indicate a minimal stratification within the tank. The total uranium and plutonium in the current Tank 38H surface sample remains similar to the previous analysis. The Tank 38H sub-surface sample shows an increase in uranium and plutonium concentrations compared to the previous sample likely because of an increase in sludge solids in the current sample. The total uranium concentration in the two Tank 43H samples is essentially unchanged from previous sample results. The plutonium concentration in the Tank 43H surface sample is similar to the previous sample results while the plutonium in the Tank 43H sub-surface sample increased relative to the previous analysis. The sum of the major cations versus the sum of the major anions shows a difference of <10% for both samples from Tank 38H and for both samples from Tank 43H providing an indication of good data quality for the non-radioactive analytes in the samples. The silicon concentrations measured in the Tank 38H sub-surface sample increased compared with the previous sample results likely due to the presence of more sludge solids in the current sample. The Tank 38H surface sample silicon concentrations is similar to the previous sample results. The Tank 43H surface and sub-surface sample silicon concentrations both increased compared to the previous sample results. The samples analyzed from Tanks 38H and 43H show silicon concentrations ranging from 61.5 to 97.3 mg/L.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Milestone Report: Co-Scheduling Applications on Current and Future Architectures

This report evaluates the viability and performance of co-scheduling scientific applications and workloads between CPUs and GPUs on current and future hardware architectures. This study was performed by collecting hardware independent and memory performance characteristics of 6 ECP mini-applications through Byfl and NSight Systems, by measuring the applications’ co-scheduled performance on current node architectures, and by gathering memory bandwidth utilization data with Intel Advisor and nvprof to begin reasoning about the feasibility of co-scheduling applications on future APU architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Extending PETSc's Composable Hierarchical Solvers (Final Technical Report)

This report documents research activities conducted at CU Boulder as part of Extending PETSc’s Composable Hierarchical Solvers, which has been part of a collaboration with Argonne National Laboratory (separate award). Our work has focused on performance-portable end-to-end GPU solvers demonstrated via exemplary applications in nonlinear fluid and structural mechanics. We describe advances in algorithmic composition and analysis in the context of these applications, but the implementations are fully documented and decoupled, and in use by other projects. We believe the vertical integration achieved through collaboration with ECP’s CEED and the PSAAP center at CU was necessary to take risks with data structures and algorithms.

42 ENGINEERING↗
DOE OSTI2023

Analysis of Tank 38h (HTF-38-23-19, -20) and Tank 43H (HTF-43-23-21, -22) Samples for Support of the Enrichment Control and Corrosion Control Programs

SRNL analyzed samples from Tank 38H and Tank 43H to support ECP and CCP. The results indicate the concentrations of most soluble species in the Tank 38H surface sample decreased significantly from the previous surface sample. The Tank 38H sub-surface sample shows changes in concentration for soluble species in the solution with some increasing and some decreasing. The current Thank 38H sub-surface sample contains visible sludge solids similar to the previous sample, i.e., less than 1%, based on visual appearance. The significant differences in the concentrations of major components between the Tank 38H surface and sub-surface samples indicate significant stratification of solution species between these two locations within the tank. Savannah River Mission Completion personnel indicate that ~ 150,000 gallons of Tank 22 supernate were received in Tank 38H since its last analysis during which time the 2H evaporator was not operated, so the observed stratification is expected. The Tank 43H surface and sub-surface samples are similar in composition to the previous samples. The similar solution compositions measured in the Tank 43H surface and sub-surface samples indicate a minimal stratification within the tank. The total uranium and plutonium in the current Tank 38H surface sample remains similar to the previous analysis. The Tank 38H sub-surface sample shows an increase in uranium and plutonium concentrations compared to the previous sample likely because of an increase in sludge solids in the current sample. The total uranium concentration in the Tank 43H surface sample is similar to the previous sample results while the plutonium in the Tank 43H sub-surface sample increased relative to the previous analysis. The sum of the major cations versus the sum of the major anions shows a difference of <10% for both samples from Tank 38H sub-surface sample (174 mg/L) increased compared with the previous sample. The Tank 38H surface sample silicon concentrations (27.5 mg/L) is one-half of the previous sample results. The Tank 43H surface sample silicon concentrations compared to the previous sample results indicate Si in the concentration range of 60 to 83 mg/L. Thus, these current samples analyzed from Tanks 38H and 43H show overall silicon concentrations ranging from 27.5 to 174 mg/L.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Advanced Research Directions on AI for Science, Energy, and Security: Report on Summer 2022 Workshops

Over the past decade, fundamental changes in artificial intelligence (AI)—from foundational to applied—have delivered dramatic insights across a wide breadth of U.S. Department of Energy (DOE) mission space. AI is helping to augment and improve scientific and engineering workflows (e.g., for control, design, and dramatic performance gains through surrogate models) in national security, the Office of Science, and DOE’s applied energy programs. The progress and potential for AI in DOE science was captured in the 2020 “AI for Science” report from the DOE laboratory community in collaboration with academia and industry. Specific scientific areas ready to further leverage the power of AI ranged from the scale and performance of computational models to data analysis to creating new classes of observations using computer vision. Since that report, the scale and scope of scientific AI have accelerated, revealing new, emergent properties that yield insights that go beyond enabling opportunities to being potentially transformative in the way that scientific problems are posed and solved. Thus, under the guidance of both the Office of Science (SC) and the National Nuclear Security Administration (NNSA), the DOE national laboratories organized a series of workshops in 2022 to gather input on new and rapidly emerging opportunities and challenges of scientific AI. This 2023 report is a synthesis of those workshops. The scientific community believes AI can have a foundational impact on a broad range of DOE missions, including science, energy, and national security. Further, DOE has unique capabilities that enable the community to drive progress in scientific use of AI, building on long-standing DOE strengths and investments in computation, data, and communications infrastructure, spanning the Energy Sciences Network (ESnet), the Exascale Computing Project (ECP), and integrative programs such as the NNSA Office of Defense Programs Advanced Simulation and Computing (ASC) and the SC Scientific Discovery through Advanced Computing (SciDAC) programs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

2.3.3.01- xSDK-Batched Final Report for Subcontract Partner KIT

The xSDK batched effort as focus effort of the ECP project xSDK focused on the development, deployment, and dissemination of batched functionality in the US Exascale Computing Project. Over a duration of almost three years, KIT as subcontract to LLNL provided technology development, functionality deployment, integration support, and consulting on batched iterative solvers and batched preconditioners. This final report accumulates the quarterly progress reports and most significant contributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

2.3.3.01- xSDK-Multiprecision Final Report for Subcontract Partner KIT

The xSDK Multiprecision effort as focus effort of the ECP project xSDK focused on the development, deployment, and dissemination of mixed precision functionality in the US Exascale Computing Project. Over a duration of four years, KIT as subcontract to LLNL provided technology development, functionality deployment, integration support, and consulting on mixed precision functionality. The subcontract was modified several times over the project duration. All deliverables of the subcontract have been completed. This final report accumulates the quarterly progress reports and most significant contributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Analysis of Tank 38H (HTF-38-23-95, -96) and Tank 43H (HTF-43-23-93, -94) Samples for Support of the Enrichment Control and Corrosion Control Programs

Savannah River National Laboratory analyzed samples from Tank 38H and Tank 43H to support Enrichment Control Program (ECP) and Corrosion Control Program (CCP). The results indicate the concentrations of most soluble species in the Tank 38H surface sample increased significantly from the previous Tank 38H surface sample. The current Tank 38H subsurface sample shows similar Na, free hydroxide, and anions versus the previous subsurface sample. However, the 38H subsurface sample shows higher concentrations of Al, Ca, Fe, Mn, and Si vs. the previous Tank 38H subsurface sample. The current Tank 38H subsurface sample contained visible sludge solids in excess of the previous sample based on visual appearance. Weight percent solids measurements indicate presence of 3.0 ± 0.1 wt.% insoluble solids in the Tank 38H subsurface sample. The significant differences in the concentrations of major components between the Tank 38H surface and subsurface samples indicate significant stratification of solution species between these two locations within the Tank 38H. Savannah River Mission Completion (SRMC) personnel indicated that there were no tank-to-tank transfers into Tank 38H since early January 2023 and the 2H (16H) Evaporator was shut down on 3/26/2023 and has not operated since that time. There have been many pumped non-waste transfers of water from the H-Area diversion box 7 (HDB-7) sump into Tank 38 since the 3/26/2023 date.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Batched Sparse Linear Algebra Phase 2 (Final Report)

The purpose of the work was to help LLNL develop a broadly applicable set of capabilities that focus on batched sparse linear functionality and its software implementation. The enablement occurred in a broader scope of the Exascale Computing Program (ECP) with an eye on the xSDK collection of applications and libraries. These served as the main dissemination targets and in the end benefitted from this project’s outcomes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

xSDK Multiprecision (Final Report)

The xSDK Multiprecision effort as focus effort of the ECP project xSDK focused on the development, deployment, and dissemination of mixed precision functionality in the US Exascale Computing Project. Over a duration of four years, KIT as subcontract to LLNL provided technology development, functionality deployment, integration support, and consulting on mixed precision functionality. The subcontract was modified several times over the project duration. All deliverables of the subcontract have been completed. This final report accumulates the quarterly progress reports and most significant contributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Ristra Project FY23 L2 Milestone Report, Rev.1: MRT #8541: Multiphysics Scaling on EAS-3

The findings of this report were used to close out the ATDM milestone MRT# 8541, which was designed to demonstrate readiness of ATDM multiphysics codes for mission-relevant work on ATS-4, El Capitan. To this end, the closure criteria were to run a 3D shaped charge problem at scale up to 50% of the El Capitan early-access system, RZVernal (AMD Trento CPUs and AMD MI-250X GPUs), demonstrate scalability, and document challenges with the software stack and environment. LANL’s approach to this milestone was to test our modular software capability by developing an entirely new code, Moya, built upon our FleCSI framework. The physics capability and the GPU infrastructure needed for the shaped charge problem on GPUs was added to Moya, and the required calculations were performed at scale. Moya showed good scaling without any fine-tuning of GPU kernels; there is still significant room for performance enhancements, especially for the Legion backend. Tied up in this L2 milestone was a closeout of KPP-3s for the ECP ST Projects at LANL; this material will be covered in a separate document.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Analysis of Tank 38H (HTF-38-24-53, -56) and Tank 43H (HTF-43-24-54, -55) Samples for Support of the Enrichment Control and Corrosion Control Programs

Savannah River National Laboratory analyzed samples from Tank 38H and Tank 43H to support the Enrichment Control Program (ECP) and Corrosion Control Program (CCP). The results indicate the concentrations of most soluble species in the Tank 38H surface sample increased from the previous Tank 38H surface sample. The current Tank 38H subsurface sample shows similar Na, free hydroxide, and anions in comparison to the previous subsurface sample. However, the 38H subsurface sample shows lower concentrations of Al, Ca, Fe, Mn, and Si in comparison to the previous Tank 38H subsurface sample. Measurement of the wt.% insoluble solids in the Tank 38H subsurface sample and associated uncertainty analysis indicates that the calculated average wt.% insoluble solids is 0.45 ± 0.75 wt.%. Significant differences in the concentrations of major components between the Tank 38H surface and subsurface samples indicate significant stratification of solution species between these two locations within Tank 38H.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Batched Sparse Linear Algebra Phase 2

The purpose of the work was to help LLNL develop a broadly applicable set of capabilities that focus on batched sparse linear functionality and its software implementation. The enablement occurred in a broader scope of the Exascale Computing Program (ECP) with an eye on the xSDK collection of applications and libraries. These served as the main dissemination targets and in the end benefitted from this project’s outcomes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Assessing Accelerator Library Integration in MOOSE

MOOSE is a general purpose open source multiphysics framework supporting native finite element and finite volume discretizations as well and wrapping other libraries providing arbitrary computational capabilities. Due to its generality, it has experienced significant success. However, with recent changes in the landscape of computer architectures, most notably the growth of GPU computing, MOOSE must assess new technologies or else risk alienating customers interested in the benefits these technologies can offer. In that vein we have assessed multiple accelerator libraries developed through the ECP project, including Kokkos, libCEED, and MFEM, and present our evaluation of these libraries as candidates for incorporation into the MOOSE framework.

97 MATHEMATICS AND COMPUTING↗