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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Level-2 Milestone 6007: Sierra Early Delivery System Deployed to Secret Restricted Network

This report documents the delivery and installation of Shark, a CORAL Sierra early delivery system deployed on the LLNL SRD network. Early ASC program users have run codes on the machine in support of application porting for the final Sierra system which will be deployed at LLNL in CY2018. In addition to the SRD resource, Shark, unclassified resources, Rzmanta and Ray, have been deployed on the LLNL Restricted Zone and Collaboration Zone networks in support of application readiness for the Sierra platform.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Collaborating CPU and GPU for large-scale high-order CFD simulations with complex grids on the TianHe-1A supercomputer

Programming and optimizing complex, real-world CFD codes on current many-core accelerated HPC systems is very challenging, especially when collaborating CPUs and accelerators to fully tap the potential of heterogeneous systems. In this paper, with a tri-level hybrid and heterogeneous programming model using MPI + OpenMP + CUDA, we port and optimize our high-order multi-block structured CFD software HOSTA on the GPU-accelerated TianHe-1A supercomputer. HOSTA adopts two self-developed high-order compact definite difference schemes WCNS and HDCS that can simulate flows with complex geometries. We present a dual-level parallelization scheme for efficient multi-block computation on GPUs and perform particular kernel optimizations for high-order CFD schemes. The GPU-only approach achieves a speedup of about 1.3 when comparing one Tesla M2050 GPU with two Xeon X5670 CPUs. To achieve a greater speedup, we collaborate CPU and GPU for HOSTA instead of using a naive GPU-only approach. We present a novel scheme to balance the loads between the store-poor GPU and the store-rich CPU. Taking CPU and GPU load balance into account, we improve the maximum simulation problem size per TianHe-1A node for HOSTA by 2.3×, meanwhile the collaborative approach can improve the performance by around 45% compared to the GPU-only approach. Further, to scale HOSTA on TianHe-1A, we propose a gather/scatter optimization to minimize PCI-e data transfer times for ghost and singularity data of 3D grid blocks, and overlap the collaborative computation and communication as far as possible using some advanced CUDA and MPI features. Scalability tests show that HOSTA can achieve a parallel efficiency of above 60% on 1024 TianHe-1A nodes. With our method, we have successfully simulated an EET high-lift airfoil configuration containing 800M cells and China's large civil airplane configuration containing 150M cells. To our best knowledge, those are the largest-scale CPU–GPU collaborative simulations that solve realistic CFD problems with both complex configurations and high-order schemes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Performance Analysis of PIConGPU: Particle-in-Cell on GPUs using NVIDIA’s NSight Systems and NSight Compute

PIConGPU, Particle In Cell on GPUs, is an open source simulations framework for plasma and laser-plasma physics used to develop advanced particle accelerators for radiation therapy of cancer, high energy physics and photon science. While PIConGPU has been optimized for at least 5 years to run well on NVIDIA GPU-based clusters, there has been limited exploration by the development team of potential scalability bottlenecks using recently updated and new tools including NVIDIA’s NVProf tool and the brand-new NVIDIA NSight Suite (Systems and Compute) tools. PIConGPU is a highly optimized application that runs production jobs at scale on a system Oak Ridge Leadership Facility’s (OLCF) Summit supercomputer (using the full machine at 4600 nodes; at 98% of GPU utilization on all ~28000 NVIDIA Volta GPUs). PIConGPU has been selected as one of the the eight applications for OLCF’s coveted Center for Accelerated Application Readiness (CAAR) program aimed at the facility’s Frontier supercomputer (OLCF’s first exascale system to launch in 2021), to partner with our vendors (primary vendors: AMD and Cray/HPE) ensuring that Frontier will be able to perform large-scale science when it opens to users in 2022. To this effect, performance engineers on the PIConGPU team wanted to dive deep into the application to understand at the finest granularity, which portions of the code could be further optimized to exploit the hardware on Summit at it’s maximum potential and also to elucidate which key kernels should be tracked and optimized for the CAAR effort to port this code to Frontier. Any bottlenecks that are observed via performance profiling on Summit are likely to also impact scalability on the Frontier-dev system and the Frontier Early Access (EA) system. Additionally, the engineers wanted to take a closer look at the newest NVIDIA profiling tools which allows us to identify the most useful features on these tools and will provide an opportunity to compare it to new AMD and Cray’s performance analysis tool releases and provide feedback to our vendor partners on what features are most important and mission critical for CAAR efforts. The primary goal of this report is to focus on the evaluation of PIConGPU’s most time-intensive kernels using NVProf and NSight Suite. Three kernels, Current Deposition (also known as Compute Current), Particle Push (Move and Mark), and Shift Particles are known to be some of the most time-consuming kernels in PIConGPU. The Current xi Deposition kernel and Particle Push kernel both set up the particle attributes for running any physics simulation with PIConGPU, so it is crucial to improve the performance of these two kernels. In this report, we measure single GPU metrics for the three kernels, offer high level takeaways from the conducted analysis, and compare the profiling data from NSight Compute to that of NVProf. This analysis was performed using a grid size of 240 x 272 x 224, and 10 time steps with the Mid-November Figure of Merit (FOM) run setup. The Traveling Wave Electron Acceleration (TWEAC) science case used in this run is a representative science case for PIConGPU. This execution can also be used for baseline analysis on AMD MI50/ MI60 systems. As of the time of writing, the PIConGPU application has limited use for features of NSight Systems, so this report will mainly focus on insights garnered from NSight Compute. For this analysis, we run the “full” metric set available in NSight Compute version 2020.1.2 and use NSight Systems version 2020.3.1 to generate the application timeline.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Implementation of Stochastic Polynomials Approach in the RAVEN Code

RAVEN, under the support of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, has been tasked to provide the necessary software and algorithms to enable the application of the conceptual framework developed by the Risk Informed Safety Margin Characterization (RISMC) [1] path. RISMC is one of the paths defined under the Light Water Reactor Sustainability (LWRS) DOE program.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Milestone Completion Report STCO04-1 AAPS: engagements with code teams, vendors, collaborators, developers

The Advanced Architecture and Portability Specialists team (AAPS) worked with a select set of LLNL application teams to develop and/or implement a portability strategy for next-generation architectures. The team also investigated new and updated programming models and helped develop programming abstractions targeting maintainability and performance portability. Significant progress was made on both fronts in FY17, resulting in multiple applications being significantly more prepared for the nextgeneration machines than before.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

GENESPACE R Package (GENESPACE) v1.0

In short, the GENESPACE pipeline conducts analysis of orthology networks, constrained within syntenic regions. Since analyses are limited to local tests conducted within syntenic blocks, GENESPACE is agnostic to ploidy, duplicated regions, inversions or other whole-genome chromosomal complexities that are common across many evolutionary lineages. This advantage allows for evolutionary tests in polyploids (e.g. switchgrass, manuscript in review), species with ancient, but retained whole-genome duplications (e.g. pecan, manuscript in prep), high levels of tandem array proliferation (e.g. eukalypts, manuscript in review) and many other factors that can confound comparative genomic analyses. The major advances of GENESPACE are three-fold: First, this is the first R package to integrate visualization and analysis of large-scale comparative genomics. R, which offers a high-level environment for graphical and statistical exploration of data, is often speed- and memory-limited and not used for computationally intensive tasks such as comparative genomics. The highly efficient C++ scripts used in GENESPACE (via data.table) permit a much faster and computationally lightweight implementation of comparative genomics than is currently available. Second, the pipeline itself is novel. To the best of our knowledge, no other program accomplishes synteny-constrained and ploidy-agnostic comparative genomics. Since nearly all plants and many animals have a history of whole-genome duplications, this is a major and necessary advance to the field. Third, GENESPACE offers high-level and intuitive multi-genome graphical outputs. The dotplots and 'riparian' plots produced herein, which are produced entirely through original R code, are publication-ready and easily customizable.

Schmutz, Jeremy↗
DOE OSTI2024

Common Electric Power Transmission System Model JSON Schema Specification

The Common Electric Power Transmission System Model (CTM) is an intuitive, extensible, language-agnostic, and error-resistant specification of electric power network components parameter names and units, and relation between components, intended for use by the research community developing new computational methods for power systems operations and simulation. Power system datasets following the CTM specification can be read as dictionaries and manipulated in that form in most programming languages (e.g., Python, Julia, C++). This standard data structure in CTM makes it easy to work in multiple power systems domains (e.g., economic operation, reliability assessment, electricity markets, stability assessment, etc.) without requiring conversions between use-case-specific file formats with information loss in the process. This repository specifies CTM as a JSON Schema, provides documentation, derivate (code-generated) implementations of CTM, and example data and usage of the schema for important use cases.

Aravena Solis, Ignacio↗
DOE OSTI2018

A Detailed Assessment of the Finite Element Analysis of Reinforced Concrete Structures Impacted by Large Missiles

This document consolidates the work performed by Sandia National Laboratories and the US Nuclear Regulatory Commission in participation of Program IRIS: “Improving the Robustness of the Assessment Methodologies for Structures Impacted by Missiles”. Three round-robin benchmark exercises on improving the robustness of the assessment of structures impacted by large missiles at medium to high velocities were organized by either the IAGE Subgroup on Ageing of Concrete Structures of the Organization for Economic Co-operation and Development Nuclear Energy Agency (NEA) or Électricité de France (EDF). The objectives of the exercises were to develop guidance for conducting impact analyses including issues related to computer codes, modeling approaches, and analysis techniques. The full project was comprised of three phases: Phase I, impact of walls; Phase II, impact of larger structures; and Phase III, transmission of shock and vibration to internal components.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

BUILD: Binary Understanding and Integration Logic for Dependencies (Final Report)

Increasingly diverse mission needs, the emergence of AI and cloud, and increasing hardware diversity are driving HPC software to be more complex. Modern codes are built from hundreds of small, complex components, and much of the software development process involves integrating these components rather than developing new components from scratch. The goal of the BUILD project was to ease the task of software integration for developers across LLNL’s programs. The project focused on (1) modeling software compatibility, (2) modeling ABI compatibility with binary analysis, (3) developing solver techniques to reason about compatibility, and (4) developing AI/ML models to fill gaps in our understanding of software compatibility. The project has developed several key technologies that help developers—by accelerating development workflows, removing the need for rebuilds, and enabling faster, automatic, and less error-prone code sharing. These technologies are used in LLNL codes and will be ready for the new El Capitan Exascale system in Livermore Computing. Many of these technologies have been hardened and integrated with LLNL’s Spack package manager, and they are already in use by production code teams. Results of BUILD have laid the groundwork for future advances in software integration—the ML and binary modification techniques developed in this project still need to be operationalized but have great potential to further speed up software integration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Hindsight logging for model training

In modern Machine Learning, model training is an iterative, experimental process that can consume enormous computation resources and developer time. To aid in that process, experienced model developers log and visualize program variables during training runs. Exhaustive logging of all variables is infeasible, so developers are left to choose between slowing down training via extensive conservative logging, or letting training run fast via minimalist optimistic logging that may omit key information. As a compromise, optimistic logging can be accompanied by program checkpoints; this allows developers to add log statements post-hoc, and "replay" desired log statements from checkpoint---a process we refer to as hindsight logging. Unfortunately, hindsight logging raises tricky problems in data management and software engineering. Done poorly, hindsight logging can waste resources and generate technical debt embodied in multiple variants of training code. In this paper, we present methodologies for efficient and effective logging practices for model training, with a focus on techniques for hindsight logging. Our goal is for experienced model developers to learn and adopt these practices. To make this easier, we provide an open-source suite of tools for Fast Low-Overhead Recovery (flor) that embodies our design across three tasks: (i) efficient background logging in Python, (ii) adaptive periodic checkpointing, and (iii) an instrumentation library that codifies hindsight logging for efficient and automatic record-replay of model-training. Model developers can use each flor tool separately as they see fit, or they can use flor in hands-free mode, entrusting it to instrument their code end-to-end for efficient record-replay. Our solutions leverage techniques from physiological transaction logs and recovery in database systems. Evaluations on modern ML benchmarks demonstrate that flor can produce fast checkpointing with small user-specifiable overheads (e.g. 7%), and still provide hindsight log replay times orders of magnitude faster than restarting training from scratch.

Computer Science↗
DOE OSTI2014

Herschel observations of extraordinary sources: Analysis of the HIFI 1.2 THz wide spectral survey toward orion KL. I. method

We present a comprehensive analysis of a broadband spectral line survey of the Orion Kleinmann-Low nebula (Orion KL), one of the most chemically rich regions in the Galaxy, using the HIFI instrument on board the Herschel Space Observatory. This survey spans a frequency range from 480 to 1907 GHz at a resolution of 1.1 MHz. These observations thus encompass the largest spectral coverage ever obtained toward this high-mass star-forming region in the submillimeter with high spectral resolution and include frequencies >1 THz, where the Earth's atmosphere prevents observations from the ground. In all, we detect emission from 39 molecules (79 isotopologues). Combining this data set with ground-based millimeter spectroscopy obtained with the IRAM 30 m telescope, we model the molecular emission from the millimeter to the far-IR using the XCLASS program, which assumes local thermodynamic equilibrium (LTE). Several molecules are also modeled with the MADEX non-LTE code. Because of the wide frequency coverage, our models are constrained by transitions over an unprecedented range in excitation energy. A reduced χ{sup 2} analysis indicates that models for most species reproduce the observed emission well. In particular, most complex organics are well fit by LTE implying gas densities are high (>10{sup 6} cm{sup –3}) and excitation temperatures and column densities are well constrained. Molecular abundances are computed using H{sub 2} column densities also derived from the HIFI survey. The distribution of rotation temperatures, T {sub rot}, for molecules detected toward the hot core is significantly wider than the compact ridge, plateau, and extended ridge T {sub rot} distributions, indicating the hot core has the most complex thermal structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

An Assessment of Fission Product Scrubbing in Sodium Pools Following a Core Damage Event in a Sodium Cooled Fast Reactor

The U.S. Nuclear Regulatory Commission has stated that mechanistic source term (MST) calculations are expected to be required as part of the advanced reactor licensing process. A recent study by Argonne National Laboratory has concluded that fission product scrubbing in sodium pools is an important aspect of an MST calculation for a sodium-cooled fast reactor (SFR). To model the phenomena associated with sodium pool scrubbing, a computational tool, developed as part of the Integral Fast Reactor (IFR) program, was utilized in an MST trial calculation. This tool was developed by applying classical theories of aerosol scrubbing to the decontamination of gases produced as a result of postulated fuel pin failures during an SFR accident scenario. The model currently considers aerosol capture by Brownian diffusion, inertial deposition, and gravitational sedimentation. The effects of sodium vapour condensation on aerosol scrubbing are also treated. This paper provides details of the individual scrubbing mechanisms utilized in the IFR code as well as results from a trial mechanistic source term assessment led by Argonne National Laboratory in 2016.

Fission Product Scrubbing↗
DOE OSTI2016

Software Dependability

The purpose of this paper is to provide a brief introduction of Software Dependability and a summary of lessons learned. The components of Software Dependability vary among standards, however there is agreement among the standards that reliability, availability and maintainability are some the main components of dependability. Safety is also a main component is safety systems. Although reliability and safety are similar there is an additional difference, safety can withstand some level of fault tolerance. For the purposes of this discussion Software Dependability includes reliability, availability, maintainability and safety. Software Dependability: Trustworthiness of a computer system such that reliance can be justifiably placed on the service it delivers. Reliability, availability, and maintainability are aspects of dependability. Reliability: The ability of a system or component to perform its required functions under stated conditions for a specified period of time. Availability: The degree to which a system or component is operational and accessible when required for use. Often expressed as a probability. Maintainability: Speed and ease with which a program can be corrected or changed. Safety: a measure of the length of time the software system can be expected to run before failing in such a way as to cause a system hazard. (author)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Application of the CFD CONV code to the analysis of LIVE L6 test

The thermo-physical behaviour of a corium pool in reactor pressure vessel of a pressurised water reactor is of principal importance for the prediction of core melt down accident development. This concerns, in general, the understanding of a severe accident with core melting, its course, major critical phases and timing, and the influence of these processes on the accident progression in terms of assessing the possibility to remove the released heat by external vessel cooling. The general objective of the LIVE program at KIT is to study phenomena resulting from core melting experimentally in large-scale 3D geometry with emphasis on the transient behaviour. The presented paper describes analysis and interpretation of the LIVE L6 experiment, in which the molten pool (non-eutectic melt KNO{sub 3}-NaNO{sub 3}) was separated by horizontal copper plate in order to develop the approach to the analysis of layering and focusing effects as the most challenging factors. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Finite Element Solver for Fission Dynamics

FELIX is a physics computer code used to model fission fragment mass distributions in a fully quantum-mechanical, microscopic framework that only relies on our current knowledge of nuclear forces. It is an implementation of the time-dependent generator coordinate method (TDGCM), which simulates the dynamics of a collective quantum wave-packet assuming the motion is adiabatic. In typical applications of the TDGCM, the nuclear collective wavepacket is obtained as a superposition of wavefunctions obtained by solving the Hartree-Fock-Bogoliubov equations of nuclear density functional theory (DFT). The program calculates at each time step the coefficients of that superposition.

Regnier, D.↗
DOE OSTI2017

2011.2 Revision of the Evaluated Nuclear Data Library (ENDL2011.2)

LLNL's Computational Nuclear Physics Group and Nuclear Theory and Modeling Group have col- laborated to create the 2011.2 revised release of the Evaluated Nuclear Data Library (ENDL2011.2). ENDL2011.2 is designed to support LLNL's current and future nuclear data needs and will be em- ployed in nuclear reactor, nuclear security and stockpile stewardship simulations with ASC codes. This database is currently the most complete nuclear database for Monte Carlo and deterministic transport of neutrons and charged particles. This library was assembled with strong support from the ASC PEM and Attribution programs, leveraged with support from Campaign 4 and the DOE/O ce of Science's US Nuclear Data Program. This document lists the revisions made in ENDL2011.2 compared with the data existing in the original ENDL2011.0 release and the ENDL2011.1-rc4 re- lease candidate of April 2015. These changes are made in parallel with some similar revisions for ENDL2009.2.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

NEAMS TH CRAB

The MOOSE framework is a library designed to make it straightforward for physicists and engineers to model partial differential equations using finite element and finite volume methods. Finite elements have been a part of the framework library since MOOSE's inception over a decade ago. Initial finite volume capability, however, was added only as recently as May of 2020. Since that time, significant work has been conducted to develop fluid modeling capability based on the finite volume method. Much of this work has taken place in MOOSE's navier_stokes module and in the NEAMS program's coarse mesh CFD code Pronghorn. We report here on development in MOOSE and Pronghorn of incompressible, porous incompressible, and weakly compressible finite volume simulation capabilities and their application to modeling of MSR and FHR advanced reactor concepts.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗