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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Distributed Louvain Algorithm for Graph Community Detection

In most real-world networks, the nodes/vertices tend to be organized into tightly-knit modules known as communities or clusters, such that nodes within a community are more likely to be “related” to one another than they are to the rest of the network. The goodness of partitioning into communities is typically measured using a well known measure called modularity. However, modularity optimization is an NP-complete problem. In 2008, Blondel, et al. introduced a multi-phase, iterative heuristic for modularity optimization, called the Louvain method. Owing to its speed and ability to yield high quality communities, the Louvain method continues to be one of the most widely used tools for serial community detection. In this paper, we present the design of a distributed memory implementation of the Louvain algorithm for parallel community detection. Our approach begins with an arbitrarily partitioned distributed graph input, and employs several heuristics to speedup the computation of the different steps of the Louvain algorithm. We evaluate our implementation and its different variants using real-world networks from various application domains (including internet, biology, social networks). Our MPI+OpenMP implementation yields about 7x speedup (on 4K processes) for soc-friendster network (1.8B edges) over a state-of-the-art shared-memory multicore implementation (on 64 threads), without compromising output quality. Furthermore, our distributed implementation was able to process a larger graph (uk-2007; 3.3B edges) in 32 seconds on 1K cores (64 nodes) of NERSC Cori, when the state-of-the-art shared-memory implementation failed to run due to insufficient memory on a single Cori node containing 128 GB.

High performance computing, graph algorithms, Dist↗
DOE OSTI2023

Julia as a unifying end-to-end workflow language on the Frontier exascale system

We evaluate Julia as a single language and ecosystem paradigm powered by LLVM to develop workflow components for high-performance computing. We run a Gray-Scott, 2-variable diffusion-reaction application using a memory-bound, 7-point stencil kernel on Frontier, the US Department of Energy’s first exascale supercomputer. We evaluate the performance, scaling, and trade-offs of (i) the computational kernel on AMD’s MI250x GPUs, (ii) weak scaling up to 4,096 MPI processes/GPUs or 512 nodes, (iii) parallel I/O writes using the ADIOS2 library bindings, and (iv) Jupyter Notebooks for interactive analysis. Results suggest that although Julia generates a reasonable LLVM-IR, a nearly 50% performance difference exists vs. native AMD HIP stencil codes when running on the GPUs. As expected, we observed near-zero overhead when using MPI and parallel I/O bindings for system-wide installed implementations. Consequently, Julia emerges as a compelling high-performance and high-productivity workflow composition language, as measured on the fastest supercomputer in the world.

Godoy, William↗
DOE OSTI2023

4P (Plastic Parallel Pathways Platform) [SWR 23-84]

The Plastic Parallel Pathways Platform (4P) combines life cycle assessment, agent-based modeling within a dynamic material flow analysis structure to compute the environmental impacts of different recycling options under various behavioral interventions.

Walzberg, Julien↗
DOE OSTI2024

Scaling the SciDAC QuantOm Workflow

As part of the Scientific Discovery through Advanced Computing (SciDAC) program, the Quantum Chromodynamics Nuclear Tomography (QuantOM) project aims to analyze data from Deep Inelastic Scattering (DIS) experiments conducted at Jefferson Lab and the upcoming Electron Ion Collider. The DIS data analysis is performed on an event-level by combining the input from theoretical and experimental nuclear physics into a single, composable workflow. The optimization itself (I.e. fitting the experimental data with theoretical predictions) is carried out by a machine / deep learning algorithm. The size of the acquired DIS data as well as the complexity of the workflow itself require that the analysis is performed across multiple GPUs on high performance computing systems, such as Polaris at Argonne National Laboratory. This presentation discusses the novelties and challenges that came along with parallelizing this workflow. Recent results are compared to common distributed training techniques.

Lersch, Daniel↗
DOE OSTI2019

D-Wave for High Energy Physics

aWe analyze different problems in high-energy physics where quantum computing, and namely quantum annealers, may be able to provide an edge in coming years: 1) The training of Restricted Boltzmann Machines (RBM) is a natural problem for quantum annealers. We explore RBM trained on a D-Wave machine for classification of galaxy morphologies, including a discussion of how to obtain a Boltzmann distribution from the annealer. 2) For this study, we cast the problem of explaining and predicting the production of particles in high energy collisions (color recombination) as an optimization problem and employ classical and quantum computing techniques to find solutions. In particular, we present a quadratic unconstrained binary optimization (QUBO) formulation for quantum annealers. In parallel to these efforts, we also present the cross-platform XACC package for quantum compilation and execution.

Caldeira, J.↗
DOE OSTI2023

Neutron Absorber Plate Characterization Plan for Criticality Experiments Design

After being used in nuclear installations, depleted fuel can still be highly reactive and must be handled securely to prevent any radiological or criticality concerns. In particular, spent fuel from use in nuclear power reactors must be stored and transported in specifically designed containers using neutron absorber materials to prevent criticality. Various neutron absorber material types exist and are manufactured by various entities, as thoroughly described in the Handbook of Neutron Absorber Materials for Spent Nuclear Fuel Storage and Transportation Applications written by EPRI. Presently, one of the most modern and most widely used types of neutron absorber material contains particles of boron carbide, or B 4 C, embedded in aluminum matrix: Boralcan, manufactured by Rio Tinto. It is very important for the community to know as much as possible about such neutron absorber materials. Therefore, in the recent years, a US Department of Energy National Nuclear Security Administration–Nuclear Criticality Safety Program funded project initiated design of an experiment that places Boralcan neutron-absorbing plates in an established critical assembly using low-enriched uranium fuel at the Sandia Pulsed Reactor Facility/Critical Experiments (SPRF/CX) apparatus at Sandia National Laboratories. The goal of the experiment is to produce high-quality benchmark data to submit to the International Criticality Safety Benchmark Evaluation Project (ICSBEP), for use in validating calculational tools and nuclear data by criticality safety analysts. The project, named IER-554, is currently in its final design stage, following a successful preliminary design. In the work documented in the design study, ten critical configurations using Boralcan neutron absorber plates were designed, and the experiment was proven to be feasible, with a predicted low k eff uncertainty around 100 pcm. An overview of the modeled cutout of the critical assembly with a Boralcan plate is shown in Figure 1, representing one of the configurations planned for the critical experiments. Before the plates are inserted in the critical assembly, it is necessary to know more about their composition and uniformity. This summary focuses on the plate characterization plans. Each plate will undergo (1) neutron transmission measurements at different locations to determine the 10 B areal density and (2) an in-depth x-ray computed tomography (XCT) examination to obtain the exact Sizes and distribution of the B4C powder particles inside the plates. In parallel, plate modeling studies are performed with a goal to determine the validity of the currently used approximation of modeling the neutron absorber plates as a homogeneous mixture of Aluminum 1100 alloy and B4C— instead of explicitly modeling the B4C particles. By using the experimental 10 B areal density measurements, and the exact size and location of the B4C particles obtained by XCT, a plate model can theoretically be built that reproduces the plate with extremely high fidelity. The results of this modeling study could increase the confidence of the criticality safety community in its modeling methods when using this type of neutron absorber material, and the industry could use these validations to change the boron loading credit limits from the U.S. Nuclear Regulatory Commission standard review plan for dry cask storage of spent nuclear fuel. The modeling calculations are performed with SCALE 6.3.0 using the KENO V.a sequence for criticality calculations with the ENDF/B-VIII.0 continuous-energy cross section library.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Computational and Experimental Benchmarking for Transient Fuel Testing

In 2018 the Transient Reactor Test (TREAT) Facility was restarted. This now-operational facility brings back world-class transient fuel testing capabilities to the U.S. Among a number of parallel efforts prior to the TREAT Facility’s restart a Department of Energy (DoE) Integrated Research Project (IRP) was funded for the purpose of benchmarking the TREAT with several goals in mind: To produce a comprehensive evaluation of existing TREAT Facility neutronics data using the next generation reactor core neutronics codes in accordance with established guidelines per the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhEP). To perform a benchmark using ready-use computational fluid dynamics tools against that of a historically collected sodium loop experiment collected in the TREAT. To design, develop and test a new experimental thermal hydraulic system of a representative TREAT Facility water flow loop. And benchmark the data collected against that produced via RELAP5-3D and TRACE. To develop a comprehensive instrumentation plan for the TREAT Facility by benchmarking performing of advanced in-pile instruments in the Massachusetts Institute of Technology Research Reactor (MITR) and the TREAT. The integrated team brought together collaborating members from three universities including Oregon State University (OSU), the University of Michigan (UM), and Massachusetts Institute of Technology (MIT); three national laboratories, Idaho National Laboratory, Argonne National Laboratory (ANL), and Oak Ridge National Laboratory (ORNL); and two industry partners, TerraPower (TP) and Harris Thermal Transfer Products (HTTP). A brief summary of accomplishments resulting from this IRP includes two filed patents, more than 40 conference papers, two published benchmark reports through IRPhEP, a new representative thermal hydraulic test facility alike the in-pile PWR water flow loop for TREAT and the first advanced instruments tested within the TREAT core upon its restart. The papers presented herein were developed and provide a summary of the significant technical accomplishments which align with the four project’s objectives. The collaborators has significant support from countless parties including the operational and technical staff at TREAT to ensure that their outcomes most impactfully aligned with program needs. Lastly the collaborators would like to acknowledge the fiscal support of the DoE’s Office of Nuclear Energy under work package identification number NU-15-OR-OSU- 0701-01. This report contains selected papers from the Computational and Experimental Benchmarking for Transient Fuel Testing Integrated Research Project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Scaled ILU Smoothers for Navier-Stokes Pressure Projection

Incomplete LU (ILU) smoothers are effective in the algebraic multigrid (AMG) V-cycle for reducing high-frequency components of the error. However, the requisite direct triangular solves are comparatively slow on GPUs. Previous work has demonstrated the advantages of Jacobi iteration as an alternative to direct solution of these systems. Depending on the threshold and fill-level parameters chosen, the factors can be highly nonnormal and Jacobi is unlikely to converge in a low number of iterations. We demonstrate that row scaling can reduce the departure from normality, allowing us to replace the inherently sequential solve with a rapidly converging Richardson iteration. There are several advantages beyond the lower compute time. Scaling is performed locally for a diagonal block of the global matrix because it is applied directly to the factor. Further, an ILUT Schur complement smoother maintains a constant GMRES iteration count as the number of MPI ranks increases, and thus parallel strong-scaling is improved. Our algorithms have been incorporated into hypre, and we demonstrate improved time to solution for linear systems arising in the Nalu-Wind and PeleLM pressure solvers. For large problem sizes, GMRES+AMG executes at least five times faster when using iterative triangular solves compared with direct solves on massively parallel GPUs.

algebraic multigrid↗
DOE OSTI2018

NUMA-Aware Thread Scheduling for Big Data Transfers over Terabits Network Infrastructure

The evergrowing trend of big data has led scientists to share and transfer the simulation and analytical data across the geodistributed research and computing facilities. However, the existing data transfer frameworks used for data sharing lack the capability to adopt the attributes of the underlying parallel file systems (PFS). LADS (Layout-Aware Data Scheduling) is an end-to-end data transfer tool optimized for terabit network using a layout-aware data scheduling via PFS. However, it does not consider the NUMA (Nonuniform Memory Access) architecture. In this paper, we propose a NUMA-aware thread and resource scheduling for optimized data transfer in terabit network. First, we propose distributed RMA buffers to reduce memory controller contention in CPU sockets and then schedule the threads based on CPU socket and NUMA nodes inside CPU socket to reduce memory access latency. We design and implement the proposed resource and thread scheduling in the existing LADS framework. Experimental results showed from 21.7% to 44% improvement with memory-level optimizations in the LADS framework as compared to the baseline without any optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Characterization and Optimization of the Fitting of Quantum Correlation Functions

This case study presents a characterization and optimization of an application code for extracting parton distribution functions from high energy electron-proton scattering data. Profiling this application code reveals that the phase-space density computation accounts for 93% of the overall execution time for a single iteration on a single core. When executing multiple iterations in parallel on a multicore system, the application spends 78% of its overall execution time idling due to load imbalance. We address these issues by first transforming the application code from Python to C++ and then tackling the application load imbalance via a hybrid scheduling strategy that combines dynamic and static scheduling. These techniques result in a 62% reduction in CPU idle time and a 2.46x speedup in overall execution time per node. In addition, the typically enabled power-management mechanisms in supercomputers (e.g., AMD Turbo Core, Intel Turbo Boost, and RAPL) can significantly impact intra-node scalability when more than 50% of the CPU cores are used. This finding underscores the importance of understanding system interactions with power management, as they can adversely impact application performance, and highlights the necessity of intra-node scaling tests to identify performance degradation that inter-node scaling tests might otherwise overlook.

Chuang, Pi-Yueh [Virginia Tech,Dept. of Computer S↗
DOE OSTI2024

3.0 - MOOSE: Enabling massively parallel multiphysics simulations

The development of MOOSE has kept accelerating since the last release, with over 2,100 pull requests merged over the last 30 months that involved nearly fifty contributors across close to a dozen institutions internationally. The growth in MOOSE's capabilities and downstream applications is reflected in the growth of the community. User support provided on the GitHub discussions forum has steadily increased to nearly 50 daily interactions. New simulation projects, notably to model advanced nuclear reactor and fusion devices, are driving a significant expansion of the capabilities. This paper reports on these developments, with several major released features, new physics modules, and key improvements to the user experience and simulation workflow.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Efficient Probabilistic Computing with Stochastic Perovskite Nickelates

Probabilistic computing has emerged as a viable approach to solve hard optimization problems. Devices with inherent stochasticity can greatly simplify their implementation in electronic hardware. In this report we demonstrate intrinsic stochastic resistance switching controlled via electric fields in perovskite nickelates doped with hydrogen. The ability of hydrogen ions to reside in various metastable configurations in the lattice leads to a distribution of transport gaps. With experimentally characterized p-bits, a shared-synapse p-bit architecture demonstrates highly parallelized and energy-efficient solutions to optimization problems such as integer factorization and Boolean satisfiability. The results introduce perovskite nickelates as scalable potential candidates for probabilistic computing and showcase the potential of light-element dopants in next-generation correlated semiconductors.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Performance on HPC Platforms Is Possible Without C++

Computing at large scales has become extremely challenging due to increasing heterogeneity in both hardware and software. More and more scientific workflows must tackle a range of scales and use machine learning and AI intertwined with more traditional numerical modeling methods, placing more demands on computational platforms. These constraints indicate a need to fundamentally rethink the way computational science is done and the tools that are needed to enable these complex workflows. The current set of C++-based solutions may not suffice, and relying exclusively upon C++ may not be the best option, especially because several newer languages and boutique solutions offer more robust design features to tackle the challenges of heterogeneity. In June 2023, we held a mini symposium that explored the use of newer languages and heterogeneity solutions that are not tied to C++ and that offer options beyond template metaprogramming and Parallel. For for performance and portability. In conclusion, we describe some of the presentations and discussion from the mini symposium in this article.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Near-continuum, hypersonic oxygen flow over a double cone simulated by direct simulation Monte Carlo informed from quantum chemistry

A large-scale, fully resolved direct simulation Monte Carlo (DSMC) computation of a non-equilibrium, reactive flow of pure oxygen over a double cone is presented. Under the simulated near-continuum conditions, the computational demands are shown to be significant because of the wide range of length scales that must be resolved. Therefore, robust grid adaption capabilities and efficient parallelization of the Stochastic PArallel Rarefied-gas Time-accurate Analyzer (SPARTA) code that is utilized in this work are essential. The thermochemical and transport collision models were selected for efficiency and simplicity. First-principles data, obtained from the highly accurate direct molecular simulation method, were used to inform the collision models’ parameters. Importantly, because SPARTA implements molecular collision models using collision-specific energies, the resulting macroscopic relaxation rates were evaluated a posteriori via zero-dimensional heat bath simulations. The comparisons of surface properties, namely heat flux and pressure, show very close agreement with previous computational fluid dynamics (CFD) results. Differences with the measurements were found to be similar to the CFD simulations. The unresolved discrepancy with the measurements could be due to inconsistent free stream conditions with the actual experimental data or missing physical phenomena altogether, for example atomic and molecular oxygen electronically excited states, three-dimensional effects, or more complex gas–surface interactions. As shown in this work, the advantages of obtaining a DSMC particle solution for these flows reside in the method's ability to be directly informed from first principles and to seamlessly describe internal energy non-equilibrium for all modes. With the advent of exascale computing and beyond, particle methods will be an increasingly important tool to verify the validity of physical assumptions in reduced-order models via fully resolved, experimental-scale simulations, down to the level of molecular-level distributions.

Mechanics↗
DOE OSTI2024

Virtual Time III, Part 3: Throttling and Message Cancellation

This is Part 3 of a trio of papers that unify in a natural way the two historically distinct parallel discrete event synchronization paradigms, optimistic and conservative, combining the best properties of both into a single framework called Unified Virtual Time (UVT). In this part, we survey the synchronization effects that can be achieved by restricting to corner cases the relationships permitted among the control variables, GVT, CVT, TVT, and LVT, which were defined in Part 1. Here we also survey various throttling policies from the literature and describe how they can be implemented in UVT by controlling the value of TVT, including policies that can take advantage of rollback in addition to LP blocking. A significant result is a new category of efficient and higher precision throttling algorithms for optimistic execution that are based on optimistic lookahead, defined in a way that is symmetric to what we now call the conservative lookahead information that is traditionally used for conservative synchronization. Finally, we present a novel algorithm allowing the choice between lazy and aggressive cancellation to be made on a message-by-message basis using either external logic expressed in the model code, or policy code internal to the simulator, or a mixture of both.

throttling↗