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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 469 records · Page 26

Algorithmic Patterns for $$\mathcal {H}$$-Matrices on Many-Core Processors

In this work, we consider the reformulation of hierarchical ( \(\mathcal {H}\) ) matrix algorithms for many-core processors with a model implementation on graphics processing units (GPUs). \(\mathcal {H}\) matrices approximate specific dense matrices, e.g., from discretized integral equations or kernel ridge regression, leading to log-linear time complexity in dense matrix–vector products. The parallelization of \(\mathcal {H}\) matrix operations on many-core processors is difficult due to the complex nature of the underlying algorithms. While previous algorithmic advances for many-core hardware focused on accelerating existing \(\mathcal {H}\) matrix CPU implementations by many-core processors, we here aim at totally relying on that processor type. As main contribution, we introduce the necessary parallel algorithmic patterns allowing to map the full \(\mathcal {H}\) matrix construction and the fast matrix–vector product to many-core hardware. In this work, crucial ingredients are space filling curves, parallel tree traversal and batching of linear algebra operations. The resulting model GPU implementation hmglib is the, to the best of the authors knowledge, first entirely GPU-based Open Source \(\mathcal {H}\) matrix library of this kind. We investigate application examples as present in kernel ridge regression, Gaussian Process Regression and kernel-based interpolation. In this context, an in-depth performance analysis and a comparative performance study against a standard multi-core CPU \(\mathcal {H}\) matrix library highlights profound speedups of our many-core parallel approach.

97 MATHEMATICS AND COMPUTING↗

ZERNIPAX: A fast and accurate Zernike polynomial calculator in Python

Zernike polynomials serve as an orthogonal basis on the unit disc, and have proven to be effective in optics simulations, astrophysics, and more recently in plasma simulations. Unlike Bessel functions, Zernike polynomials are inherently finite and smooth at the disc center (r=0), ensuring continuous differentiability along the axis. This property makes them particularly suitable for simulations, requiring no additional handling at the origin. We developed ZERNIPAX, an open-source Python package capable of utilizing CPU/GPUs, leveraging Google's JAX package and available on GitHub as well as the Python software repository PyPI. Furthermore, our implementation of the recursion relation between Jacobi polynomials significantly improves computation time compared to alternative methods by use of parallel computing while still performing more accurately for high-mode numbers.

Astrophysics↗

Two-level overlapping additive Schwarz preconditioner for training scientific machine learning applications

In this work we introduce a novel two-level overlapping additive Schwarz preconditioner for accelerating the training of scientific machine learning applications. The design of the proposed preconditioner is motivated by the nonlinear two-level overlapping additive Schwarz preconditioner. The neural network parameters are decomposed into groups (subdomains) with overlapping regions. In addition, the network’s feed-forward structure is indirectly imposed through a novel subdomain-wise synchronization strategy and a coarse-level training step. Through a series of numerical experiments, which consider physicsinformed neural networks and operator learning approaches, we demonstrate that the proposed two-level preconditioner significantly speeds up the convergence of the standard (LBFGS) optimizer while also yielding more accurate machine learning models. Moreover, the devised preconditioner is designed to take advantage of model-parallel computations, which can further reduce the training time.

97 MATHEMATICS AND COMPUTING↗

Approximation algorithms in combinatorial scientific computing

We survey recent work on approximation algorithms for computing degree-constrained subgraphs in graphs and their applications in combinatorial scientific computing. The problems we consider include maximization versions of cardinality matching, edge-weighted matching, vertex-weighted matching and edge-weighted $b$ -matching, and minimization versions of weighted edge cover and $b$ -edge cover. Exact algorithms for these problems are impractical for massive graphs with several millions of edges. For each problem we discuss theoretical foundations, the design of several linear or near-linear time approximation algorithms, their implementations on serial and parallel computers, and applications. Our focus is on practical algorithms that yield good performance on modern computer architectures with multiple threads and interconnected processors. We also include information about the software available for these problems.

Mathematics↗

A Computational Approach for Modeling Neutron Scattering Data from Lipid Bilayers

Biological cell membranes are responsible for a range of structural and dynamical phenomena crucial to a cell's well-being and its associated functions. Due to the complexity of cell membranes, lipid bilayer systems are often used as biomimetic models. These systems have led to signficant insights into vital membrane phenomena such as domain formation, passive permeation and protein insertion. Experimental observations of membrane structure and dynamics are, however, limited in resolution, both spatially and temporally. Importantly, computer simulations are starting to play a more prominent role in interpreting experimental results, enabling a molecular under- standing of lipid membranes. Particularly, the synergy between scattering experiments and simulations offers opportunities for new discoveries in membrane physics, as the length and time scales probed by molecular dynamics (MD) simulations parallel those of experiments. We also describe a coarse-grained MD simulation approach that mimics neutron scattering data from large unilamellar lipid vesicles over a range of bilayer rigidity. Specfically, we simulate vesicle form factors and membrane thickness fluctuations determined from small angle neutron scattering (SANS) and neutron spin echo (NSE) experiments, respectively. Our simulations accurately reproduce trends from experiments and lay the groundwork for investigations of more complex membrane systems.

59 BASIC BIOLOGICAL SCIENCES↗

BEYONDPLANCK III. Commander3

We describe the computational infrastructure for end-to-end Bayesian cosmic microwave background (CMB) analysis implemented by the BeyondPlanck Collaboration. The code is called Commander3. It provides a statistically consistent framework for global analysis of CMB and microwave observations and may be useful for a wide range of legacy, current, and future experiments. The paper has three main goals. Firstly, we provide a high-level overview of the existing code base, aiming to guide readers who wish to extend and adapt the code according to their own needs or re-implement it from scratch in a different programming language. Secondly, we discuss some critical computational challenges that arise within any global CMB analysis framework, for instance in-memory compression of time-ordered data, fast Fourier transform optimization, and parallelization and load-balancing. Thirdly, we quantify the CPU and RAM requirements for the current BEYONDPLANCK analysis, finding that a total of 1.5 TB of RAM is required for efficient analysis and that the total cost of a full Gibbs sample for LFI is 170 CPU-hrs, including both low-level processing and high-level component separation, which is well within the capabilities of current low-cost computing facilities. The existing code base is made publicly available under a GNU General Public Library (GPL) license.

79 ASTRONOMY AND ASTROPHYSICS↗

Computational investigation on tunable optical band gap in armchair polyacenes

Polyacenes in their armchair geometry (phenacenes) have recently been found to possess appealing electronic and optical properties with higher chemical stability and comparatively larger band gap as compared to linear polyacenes. They also behave as high-temperature superconductors upon alkali metal doping. Moreover, the optical properties of crystalline picene can be finely tuned by applying external pressure. We investigated the variation of optical gap as a function of altering the interplanar distances between parallel cofacial phenacene dimers. We employed both time-dependent density functional theory and density matrix renormalization group (DMRG) technique to investigate the lowest singlet excitations in phenacene dimer. Our study showed that the lowest singlet excitation in these systems evolved as a function of interplanar separation. The optical excitation energy gap decreases as a function of inverse interplanar separation of the phenacene dimer. The distant dependent variation of optical absorption at the dimer level may be comparable with experimental observation in picene crystal under pressure. DMRG study also demonstrates that besides picene, electronic properties of higher phenacenes can also be tunable by altering interplanar separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Particle-in-cell simulations of collisionless magnetic reconnection with a non-uniform guide field

Results are presented of a first study of collisionless magnetic reconnection starting from a recently found exact nonlinear force-free Vlasov–Maxwell equilibrium. The initial state has a Harris sheet magnetic field profile in one direction and a non-uniform guide field in a second direction, resulting in a spatially constant magnetic field strength as well as a constant initial plasma density and plasma pressure. It is found that the reconnection process initially resembles guide field reconnection, but that a gradual transition to anti-parallel reconnection happens as the system evolves. The time evolution of a number of plasma parameters is investigated, and the results are compared with simulations starting from a Harris sheet equilibrium and a Harris sheet plus constant guide field equilibrium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Flattening of the tokamak current profile by a fast magnetic reconnection with implications for the solar corona

During tokamak disruptions, the profile of the net parallel current is observed to flatten on a time scale that is so fast that it must be due to a fast magnetic reconnection. After a fast magnetic reconnection has broken magnetic surfaces, a single magnetic field line covers an entire volume and not just a magnetic surface. The current profile, given by K ≡ μ 0 j | | / B , relaxes to a constant within that volume by Alfven waves propagating along the chaotic magnetic field lines. The time scale for this relaxation determines the commonly observed disruption phenomena of a current spike and a sudden drop in the plasma internal inductance. An efficient method for studying this relaxation is derived, which allows a better understanding of the information encoded in the current spike and the associated sudden drop in the plasma internal inductance. Implications for coronal heating are also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The inductively driven transmission line: A passively coupled device for diagnostic applications on the Z pulsed power facility

The inductively driven transmission line (IDTL) is a miniature current-carrying device that passively couples to fringe magnetic fields in the final power feed on the Z Pulsed Power Facility. The IDTL redirects a small amount of Z’s magnetic energy along a secondary path to ground, thereby enabling pulsed power diagnostics to be driven in parallel with the primary load for the first time. IDTL experiments and modeling presented here indicate that IDTLs operate non-perturbatively on Z and that they can draw in excess of 150 kA of secondary current, which is enough to drive an X-pinch backlighter. Further experiments show that IDTLs are also capable of making cleaner, higher-fidelity measurements of the current flowing in the final feed.

47 OTHER INSTRUMENTATION↗

Grover Search and the No-Signaling Principle

Two of the prime properties of quantum physics are the no-signaling principle and the Grover search lower bound. That is, despite admitting stronger-than-classical correlations, quantum mechanics does not imply superluminal signaling, and despite a form of exponential parallelism, quantum mechanics does not imply polynomial-time brute force solution of NP-complete problems. Herein, we investigate the degree to which these two properties are connected. We explore four classes of deviations from quantum mechanics, for which we draw inspiration from the literature on the black hole information paradox. We show that in these models, the physical resources required to send a superluminal signal scale polynomially with the resources needed to speed up Grover’s algorithm. Hence the no-signaling principle is equivalent to the inability to solve NP-hard problems efficiently by brute force within the classes of theories analyzed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Distributed Stochastic Optimization of a Neural Representation Network for Time-Space Tomography Reconstruction

4D time-space reconstruction of dynamic events or deforming objects using X-ray computed tomography (CT) is an important inverse problem in non-destructive evaluation. Conventional back-projection based reconstruction methods assume that the object remains static for the duration of several tens or hundreds of X-ray projection measurement images (reconstruction of consecutive limited-angle CT scans). However, this is an unrealistic assumption for many in-situ experiments that causes spurious artifacts and inaccurate morphological reconstructions of the object. To solve this problem, we propose to perform a 4D time-space reconstruction using a distributed implicit neural representation (DINR) network that is trained using a novel distributed stochastic training algorithm. Our DINR network learns to reconstruct the object at its output by iterative optimization of its network parameters such that the measured projection images best match the output of the CT forward measurement model. Here, we use a forward measurement model that is a function of the DINR outputs at a sparsely sampled set of continuous valued 4D object coordinates. Unlike previous neural representation architectures that forward and back propagate through dense voxel grids that sample the object's entire time-space coordinates, we only propagate through the DINR at a small subset of object coordinates in each iteration resulting in an order-of-magnitude reduction in memory and compute for training. DINR leverages distributed computation across several compute nodes and GPUs to produce high-fidelity 4D time-space reconstructions. We use both simulated parallel-beam and experimental cone-beam X-ray CT datasets to demonstrate the superior performance of our approach.

36 MATERIALS SCIENCE↗

Computational and experimental study of laminar flames

During the past three years, our research has centered on an investigation of the effects of complex chemistry and detailed transport on the structure and extinction of hydrocarbon flames in coflowing axisymmetric configurations. We have pursued both computational and experimental aspects of the research in parallel on both steady-state and time-dependent systems. The computational work has focused on the application of accurate and efficient numerical methods for the solution of the steady-state and time-dependent boundary value problems describing the various reacting systems. Detailed experimental measurements were performed on axisymmetric coflow flames using two-dimensional imaging techniques. Previously, spontaneous Raman scattering, chemiluminescence, and laser-induced fluorescence were used to measure the temperature, major and minor species profiles. Particle image velocimetry (PIV) has been used to investigate velocity distributions and for calibration of time-varying flames. Laser-induced incandescence (LII) with an extinction calibration was used to determine soot volume fractions, while soot surface temperatures were measured with three-color optical pyrometry using a color digital camera. A blackbody calibration of the camera allows for determination of soot volume fraction as well, which can be compared with the LII measurements. More recently, we have concentrated on a detailed characterization of soot using a variety of techniques including time-resolved LII (TiRe-LII) for soot primary particles sizes, multi-angle light scattering (MALS) for soot radius of gyration, and spectrally-resolved line of sight attenuation (spec-LOSA). Combining the information from all of these soot measurements can be used to determine the soot optical properties, which are observed to vary significantly depending on spatial location and fuel dilution. Our goal has been to obtain a more fundamental understanding of the important fluid dynamic and chemical interactions in these flames so that this information can be used effectively in combustion modeling.

02 PETROLEUM↗

High Pressure Fire Loop Analysis

The scope will be limited to analyzing the effect of the EFC within the system and how one improperly installed coupling affects the rest of the HPFL system. The discussion will include normal operations, impaired flow, and service interruptions. Normal operations are defined as two-way flow to buildings. Impaired operations are defined as a building that only has one-way flow being provided to the building. Service interruptions will be when a building does not have water available to it. The project will look at the following aspects of the reliability of the HPFL system: mean time to failure (MTTF) of EFCs, mean time between failures (MTBF), series system models, and parallel system models. These calculations will then be used to discuss the reliability of the system when one of the couplings fails. Compare the reliability of two-way feeds versus one-way feeds.

42 ENGINEERING↗

In situ particle advection via parallelizing over particles

We extend the method for particle advection that parallelizes over particles to work in an in situ setting. We then compare our method with the typical method for in situ, parallelizing over data. Our experiments consist of parallelism at 512 cores, a data set with 67 million cells, and ten billion total advection steps. Our findings show that parallelizing over particles can be more than ten times faster for some workloads, for reasonable memory cost. Overall, the significance of these findings is to demonstrate that moving data can be worthwhile in some in situ settings.

Pugmire, Dave↗

Spin-flop Phase in a Honeycomb Antiferromagnet Mn 0.84 Mg 0.16 TiO 3

The spin-flop phase of a honeycomb antiferromagnet of Mn 0.84 Mg 0.16 TiO 3 has been studied under magnetic field along normal direction to the honeycomb plane by neutron scattering. With increasing a magnetic field from 0 to 5 T, the inelastic scattering intensity increased by 1.5 times at (1 0 0), where the magnetic structure was found to be collinear-antiferromagnet with the spin parallel to [1 1 0] direction. The spin direction is consistent with a 1.5 times increase of the inelastic intensity. Furthermore, the negligible energy difference between K and K' points suggests small values for both Dzyaloshinskii–Moriya interaction and bond-dependent symmetric anisotropic exchange interaction in this material.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗