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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 883 records · Page 49

Rapid Calculation of Max-Min Fair Rates for Multi-Commodity Flows in Fat-Tree Networks

Max-min fairness is often used in the performance modeling of interconnection networks. Existing methods to compute max-min fair rates for multi-commodity flows have high complexity and are computationally infeasible for large networks. In this paper, we show that by considering topological features, this problem can be solved efficiently for the fat-tree topology that is widely used in data centers and high performance compute clusters. Several efficient new algorithms are developed for this problem, including a parallel algorithm that can take advantage of multi-core and shared-memory architectures. Using these algorithms, we demonstrate that it is possible to find the max-min fair rate allocation for multi-commodity flows in fat-tree networks that support tens of thousands of nodes. We evaluate the run-time performance of the proposed algorithms and show improvement in orders of magnitude over the previously best known method. Finally, we further demonstrate a new application of max-min fair rate allocation that is only computationally feasible using our new algorithms.

97 MATHEMATICS AND COMPUTING↗

A Parallel Cut-Cell Algorithm for the Free-Boundary Grad--Shafranov Problem

A parallel cut-cell algorithm is described to solve the free-boundary problem of the Grad--Shafranov equation. The algorithm reformulates the free-boundary problem in an irregular bounded domain and its important aspects include a searching algorithm for the magnetic axis and separatrix, a surface integral along the irregular boundary to determine the boundary values, an approach to optimize the coil current based on a targeting plasma shape, Picard iterations with Aitken's acceleration for the resulting nonlinear problem, and a Cartesian grid embedded boundary method to handle the complex geometry. Here the algorithm is implemented in parallel using a standard domain-decomposition approach and a good parallel scaling is observed. Numerical results verify the accuracy and efficiency of the free-boundary Grad--Shafranov solver.

97 MATHEMATICS AND COMPUTING↗

Caffeine v0.1.0

Caffeine is the CoArray Fortran Framework of Efficient Interfaces to Network Environments. Caffeine aims to produce a parallel runtime library that will support Fortran compilers with a programming-model-agnostic application binary interface (ABI) to various lower-level communication libraries. The current version of Caffeine uses the GASNet-EX networking middleware, also developed at Berkeley Lab. On many combinations of applications and platforms, GASNet-EX outperforms the widely used Message Passing Interface (MPI). Through GASNet-EX's support for communicating between graphics processing units (GPU), GASNet-EX has features that specifically target the emerging, leading-edge exascale computing platforms.

Rouson, Damian↗

Three-dimensional induced polarization data inversion for complex resistivity

The conductive and capacitive material properties of the subsurface can be quantified through the frequency-dependent complex resistivity. However, the routine three-dimensional (3D) interpretation of voluminous induced polarization (IP) data sets still poses a challenge due to large computational demands and solution nonuniqueness. We have developed a flexible methodology for 3D (spectral) IP data inversion. Our inversion algorithm is adapted from a frequency-domain electromagnetic (EM) inversion method primarily developed for large-scale hydrocarbon and geothermal energy exploration purposes. The method has proven to be efficient by implementing the nonlinear conjugate gradient method with hierarchical parallelism and by using an optimal finite-difference forward modeling mesh design scheme. The method allows for a large range of survey scales, providing a tool for both exploration and environmental applications. We experimented with an image focusing technique to improve the poor depth resolution of surface data sets with small survey spreads. The algorithm's underlying forward modeling operator properly accounts for EM coupling effects; thus, traditionally used EM coupling correction procedures are not needed. The methodology was applied to both synthetic and field data. We tested the benefit of directly inverting EM coupling contaminated data using a synthetic large-scale exploration data set. Afterward, we further tested the monitoring capability of our method by inverting time-lapse data from an environmental remediation experiment near Rifle, Colorado. Similar trends observed in both our solution and another 2D inversion were in accordance with previous findings about the IP effects due to subsurface microbial activity.

15 GEOTHERMAL ENERGY↗

Energy scaling advantages of resistive memory crossbar based computation and its application to sparse coding

In this study, the exponential increase in data over the last decade presents a significant challenge to analytics efforts that seek to process and interpret such data for various applications. Neural-inspired computing approaches are being developed in order to leverage the computational properties of the analog, low-power data processing observed in biological systems. Analog resistive memory crossbars can perform a parallel read or a vector-matrix multiplication as well as a parallel write or a rank-1 update with high computational efficiency. For an N × N crossbar, these two kernels can be O(N) more energy efficient than a conventional digital memory-based architecture. If the read operation is noise limited, the energy to read a column can be independent of the crossbar size (O(1)). These two kernels form the basis of many neuromorphic algorithms such as image, text, and speech recognition. For instance, these kernels can be applied to a neural sparse coding algorithm to give an O(N) reduction in energy for the entire algorithm when run with finite precision. Sparse coding is a rich problem with a host of applications including computer vision, object tracking, and more generally unsupervised learning.

97 MATHEMATICS AND COMPUTING↗

Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs

Uncertainty quantification for forward and inverse problems is a central challenge across physical and biomedical disciplines. We address this challenge for the problem of modeling subsurface flow at the Hanford Site by combining stochastic computational models with observational data using physics-informed GAN models. The geographic extent, spatial heterogeneity, and multiple correlation length scales of the Hanford Site require training a computationally intensive GAN model to thousands of dimensions. We develop a highly optimized implementation that scales to {\herogpucount} NVIDIA Volta GPUs. We develop a hierarchical scheme based on a multi-player game-theoretic approach for exploiting domain parallelism, map discriminators and generators to multiple GPUs, and employ efficient communication schemes to ensure training stability and convergence. Our implementation scales to {\heronodecount} nodes on the Summit supercomputer with a \weakscalingeff\% scaling efficiency, achieving peak and sustained half-precision rates of {\heropeakperf} PF/s and {\herosustainedperf} PF/s.

physics informed ML, machine learning, generative ↗

An Impartial Perspective for Superconducting Nb$_3$Sn coated Copper RF Cavities for Future Linear Accelerators

This Snowmass21 Contributed Paper encourages the Particle Physics community in fostering R&D in Superconducting Nb3Sn coated Copper RF Cavities instead of costly bulk Niobium. It describes the pressing need to devote effort in this direction, which would deliver higher gradient and higher temperature of operation and reduce the overall capital and operational costs of any future collider. It is unlikely that an ILC will be built in the next ten years with Nb as one of the main cost drivers of SRFs. This paper provides strong arguments on the benefits of using this time for R&D on producing Nb3Sn on inexpensive and thermally efficient metals such as Cu or bronze, while pursuing in parallel the novel U.S. concept of parallel-feed RF accelerator structures. A technology that synergistically uses both of these advanced tools would make an ILC or equivalent machines more affordable and more likely to be built. Such a successful enterprise would readily apply to other HEP accelerators, for instance a Muon Collider, and to accelerators beyond HEP. We present and assess current efforts in the U.S. on the novel concept of parallel-feed RF accelerator structures, and in the U.S. and abroad in producing Nb3Sn films on either Cu or bronze despite minimal funding.

43 PARTICLE ACCELERATORS↗

Preparatory Verification of a New Monte Carlo Code cosRMC based on VERA Core Physics Benchmark

To promote nuclear power plant system design and simulation software self-reliance development, DOE of China approved a R and D key project to develop an integrated engine for pressurized water reactor core and system design and analysis, referred as COSINE hereafter. The scope of this code package includes reactor physics, thermal hydraulics, safety analysis, severe accidents, probability safety assessment and etc. Many universities, research institutes and nuclear related corporations in China are involved in the code development, among which the State Nuclear Power Software Development Center (SNPSDC) plays the leading role. With the requirement of accurate three-dimensional modeling of the advanced, special or new complex core in reactor neutronics and shielding analysis, Monte Carlo method is becoming a more powerful tool for reactor analysis. Thus, a new Monte Carlo transport code named cosRMC (abbreviation for COSINE Reactor Monte Carlo) has been developed jointly by SNPSDC and Department of Engineering Physics, Tsinghua University, the main developer of RMC code. The cosRMC now has many functions as criticality calculation, fixed-source calculation, burnup calculation, and etc. Some techniques for geometry treatment, new burnup algorithm, source convergence acceleration, massive tally and parallel calculation have been implemented in cosRMC to improve the efficiency. In order to ensure its reliability, several types of V and V work have been and are being carried out for cosRMC. In this paper, some preparatory verification results based on VERA Core Physics Benchmark are presented. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Optimal Operation of a Hybrid Hydraulic Electric Architecture (HHEA) for Off-Road Vehicles Over Discrete Operating Decisions

Many off-highway machines including construction and agriculture equipment use hydraulics for power transmission and throttling as a means for control. Trends towards better efficiency and electrification have led to the creation of a novel Hybrid Hydraulic-Electric Architecture (HHEA) which could significantly reduce energy consumption and maintain control performance, even in machines that are too large to be directly electrified. This is achieved by using a set of common pressure rails to transmit the majority of power via power dense hydraulics and modulating the power with small electric motor-drives to achieve precise control. This paper proposes a computationally efficient method for computing the optimal sequence of pressure rail selections for the HHEA over finite drive cycles. This is useful for fairly comparing the novel architecture’s energy performance to existing architectures and for use in iterative optimal design of the architecture. The optimal control technique makes use of a static model of the architecture and losses. Constraints are enforced such that the drive cycle is repeatable. The constrained optimal operation is solved using a Lagrange multiplier technique that transforms the optimization into a small set of sub-problems by considering combinations of active constraints. Each of these sub-problems can be solved efficiently because loss calculations for all time steps can be computed in parallel. A case study of an off-road construction machine demon-strates that the HHEA reduces energy consumption by 2/3 compared to the baseline load sensing architecture.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Compact 50kW High Power Density, Hybrid 3-Level Paralleled T-type Inverter for More Electric Aircraft Applications

The demand for high performing, lightweight, reliable inverters, increased the scope of wide bandgap and high-switching frequency based solutions. To achieve such high efficiency inverters, it is vital to focus on the system level design considerations to maximize the benefits of these advanced technologies. This paper presents an improved design based on considerations to further reap the benefits of choosing the right inverter topology; increased capabilities through paralleling devices, with reduced total number of switches; and designing a planarized inverter with PCB based busbar. Appropriate thermal analysis and heatsink design has aided in increased system power density along with the overall efficiency. Demonstration of a 50kW 3-phase 3-level paralleled T-type SiC inverter operating at 40kHz switching frequency for aircraft applications is shown to evaluate the benefits of proposed design methodology. Here, the prototype achieves a high power density of 11kW/L.

42 ENGINEERING↗

Array-based Hierarchical Mesh Generation in Parallel

In this paper, we describe an array-based hierarchical mesh generation capability through uniform refinement of unstructured meshes for efficient solution of PDE's using finite element methods and multigrid solvers. A multi-degree, multi-dimensional and multi-level framework is designed to generate the nested hierarchies from an initial mesh that can be used for a number of purposes such as multi-level methods to generating large meshes. The capability is developed under the parallel mesh framework “Mesh Oriented dAtaBase” a.k.a MOAB. We describe the underlying data structures and algorithms to generate such hierarchies and present numerical results for computational efficiency and mesh quality. In conclusion, we also present results to demonstrate the applicability of the developed capability to a multigrid finite-element solver.

97 MATHEMATICS AND COMPUTING↗

Alfvén wave propagation through a moderate-amplitude transverse inhomogeneity in a magnetized plasma

Parallel propagation of a plane Alfvén wave in a moderate-amplitude Gaussian-shaped transverse inhomogeneity is studied numerically using a fluid model retaining low-frequency kinetic effects. It is shown that in such a situation, common in the solar wind where elongated pressure-balanced structures are frequently observed, phase mixing competes with wave focusing, in contrast with coronal loops or auroral regions where sharp gradients present at the edges of the inhomogeneities make phase mixing dominant. Some understanding about this competition is provided by a model based on an envelope formalism. Depending on the magnitude of the Alfvén wavelength and of the inhomogeneity transverse scale relative to the ion inertial length, various regimes can develop, ranging from the formation of localized gradients when phase mixing dominates to the development of an intense magnetic filament when focusing is stronger, with a different efficiency for the generation of magnetosonic and kinetic Alfvén waves. Electron parallel heating and parallel electric field generation are also briefly discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Electrochemical Reduction of Flue Gas Carbon Dioxide to Commercially Viable C2-C4 Products (Final Report)

This is the final scientific/technical report for a DOE project focused on the electrochemical conversion of CO 2 in non-aqueous solvents to novel products. Electrochemical reduction of CO 2 provides an attractive route to produce valuable fuels and chemicals that can simultaneously lower greenhouse gas emissions when powered by renewable electricity. While recent technological advances have shown the feasibility of industrial CO 2 electroreduction, many challenges remain to improve this technology and expand the list of economically viable products. The vast majority of electrochemical CO 2 reduction research has been conducted in aqueous media under neutral to alkaline conditions, leading to commonly reported products including carbon monoxide, formic acid, methane, methanol, ethylene, acetic acid, and ethanol. In comparison, non-aqueous media for CO 2 reduction has been underexplored but represents a possible avenue to yield new products and improved operating conditions. The aim of the project was to convert waste CO 2 in the form of flue gas to a multicarbon C2 - C4 chemical product in a reactor designed to achieve economically competitive values of current density and selectivity. The project strived to advance the technology readiness of an electrochemical CO 2 reduction process in alcohol solvents from the proof-of-concept stage to a device capable of meeting performance metrics for commercial viability. In the initial plan, the University of Louisville researchers were to focus on investigating the electrochemical process and improving the faradaic efficiency for novel C2 – C4 species, while also working on a parallel effort to build a practical electrolysis reactor to markedly increase the CO 2 reduction current density. The reactor development effort also aimed to engineer a dual-electrolyte feed strategy with non-aqueous catholyte and aqueous anolyte to promote water oxidation as the coupling anodic half-reaction to enable a sustainable and economical overall process. At the outset, the University of North Dakota was to investigate the feasibility of operating directly from coal-derived flue gas without separate capture and purification. The research team sought to determine impurity effects and test mitigation strategies, as well as engineer the gaseous feed system for high reactor tolerance to lower CO 2 concentration. In the last half year of the project, the focus was planned to shift to integrating the advances in the catalysis, electrochemical conditions, reactor design, and flue gas compatibility into a fully functional device and improve it for maximum current density and faradaic efficiency for C2 – C4 species. Knowledge of the full system components, constraints, and maximum performance was then to be used as the basis for a thorough technoeconomic analysis (TEA) and life cycle analysis (LCA) at the end of the project.

01 COAL, LIGNITE, AND PEAT↗

High-Efficiency AlGaAs/GaAs Photovoltaic Converters with Edge Input of Laser Light

High-efficiency photovoltaic converters (PVCs) have been developed and fabricated by liquidphase epitaxy in the AlGaAs–GaAs system with laser light (λ = 850 nm) introduced through the edge surface in parallel to the plane of the p–n junction of the device structure. To raise the efficiency of light “capture” by the p–n junction, an Al{sub x}Ga{sub 1–x}As waveguide layer is formed, in which the content of aluminum gradually varies from x = 0.55 to 0.15 so that the refractive index gradient is created in this layer and light beams are diverted toward the p–n junction. When a PVC (having no antireflection coating) is exposed to 0.1- to 0.2-W laser light, an efficiency of 41.5% is obtained. Depositing an antireflection coating on the edge surface of a PVC raises its efficiency to 55%.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Parallel scalability of Hartree–Fock calculations

Quantum chemistry is increasingly performed using large cluster computers consisting of multiple interconnected nodes. For a fixed molecular problem, the efficiency of a calculation usually decreases as more nodes are used, due to the cost of communication between the nodes. This paper empirically investigates the parallel scalability of Hartree–Fock calculations. The construction of the Fock matrix and the density matrix calculation are analyzed separately. For the former, we use a parallelization of Fock matrix construction based on a static partitioning of work followed by a work stealing phase. For the latter, we use density matrix purification from the linear scaling methods literature, but without using sparsity. When using large numbers of nodes for moderately sized problems, density matrix computations are network-bandwidth bound, making purification methods potentially faster than eigendecomposition methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enabling Low-Overhead HT-HPC Workflows at Extreme Scale using GNU Parallel

GNU Parallel is a versatile and powerful tool for process parallelization widely used in scientific computing. This paper demonstrates its effective application in high-performance computing (HPC) environments, particularly focusing on its scalability and efficiency in executing large-scale high-throughput high-performance computing (HT-HPC) workflows. Through real-world examples, we highlight GNU Parallel’s performance across various HPC workloads, including GPU computing, container-based workloads, and node-local NVMe storage. Our results on two leading supercomputers, OLCF’s Frontier and NERSC’s Perlmutter, showcase GNU Parallel’s rapid process dispatching ability and its capacity to maintain low overhead even at extreme scales. We explore GNU Parallel’s application in massive parallel file transfers using a scheduled Data Transfer Node (DTN) cluster, emphasizing its broad utility in diverse scientific workflows. Beyond its direct application as a viable workflow manager, GNU Parallel can be employed in conjunction with other workflow systems as a "last-mile" parallelizing driver and as a quick prototyping tool to design and extract parallel profiles from application executions. We then argue that the potential for GNU Parallel to transform workflow management at extreme scales is substantial, paving the way for more efficient and effective scientific discoveries.

Maheshwari, Ketan↗

Information criteria for quantifying loss of reversibility in parallelized KMC

Parallel Kinetic Monte Carlo (KMC) is a potent tool to simulate stochastic particle systems efficiently. However, despite literature on quantifying domain decomposition errors of the particle system for this class of algorithms in the short and in the long time regime, no study yet explores and quantifies the loss of time-reversibility in Parallel KMC. Inspired by concepts from non-equilibrium statistical mechanics, we propose the entropy production per unit time, or entropy production rate, given in terms of an observable and a corresponding estimator, as a metric that quantifies the loss of reversibility. Typically, this is a quantity that cannot be computed explicitly for Parallel KMC, which is why we develop a posteriori estimators that have good scaling properties with respect to the size of the system. Through these estimators, we can connect the different parameters of the scheme, such as the communication time step of the parallelization, the choice of the domain decomposition, and the computational schedule, with its performance in controlling the loss of reversibility. From this point of view, the entropy production rate can be seen both as an information criterion to compare the reversibility of different parallel schemes and as a tool to diagnose reversibility issues with a particular scheme. As a demonstration, we use Sandia Lab's SPPARKS software to compare different parallelization schemes and different domain (lattice) decompositions.

97 MATHEMATICS AND COMPUTING↗

Implicit high-order method for calculating rarefied gas flow in a planar microchannel

An efficient numerical algorithm for calculating rarefied gas flows in planar microchannels on the basis of the Boltzmann kinetic equation with the linearized S-model collision integral is presented. The algorithm consists of a high-order spatial discretisation on unstructured meshes, conservative procedure to calculate macroscopic quantities and efficient one-step implicit time evolution method. It therefore works across all flow regimes from the free-molecular to nearly continuum ones and provides rapid convergence to steady state solutions. The parallel implementation is provided via MPI programming paradigm. The performance of the method is illustrated by computing the flow for length to the width ratios for up to 10{sup 3} in the wide range of Knudsen numbers. Numerical estimates of efficiency of implicit time marching and parallel performance as well as convergence studies in both physical and velocity spaces are provided. The end effects and other essentially two-dimensional features of the flow are analysed and a detailed comparison with the case of an infinitely long channel is carried out. The presented numerical data can be used as reference for future studies of nonlinear flows as well as for comparison with other numerical approaches and flow models.

97 MATHEMATICS AND COMPUTING↗