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At least 1,081 records · Page 60

A Framework for Load Balancing of Tensor Contraction Expressions via Dynamic Task Partitioning

In this paper, we introduce the Dynamic Load-balanced Tensor Contractions (DLTC), a domain-specific library for efficient task parallel execution of tensor contraction expressions, a class of computation encountered in quantum chemistry and physics. Our framework decomposes each contraction into smaller unit of tasks, represented by an abstraction referred to as iterators. We exploit an extra level of parallelism by having tasks across independent contractions executed concurrently through a dynamic load balancing run- time. We demonstrate the improved performance, scalability, and flexibility for the computation of tensor contraction expressions on parallel computers using examples from coupled cluster methods.

Tensor contraction, domain-specific language, dyna↗

Effects of magnetic field on anisotropic temperature relaxation

In a strongly magnetized plasma, where the particles' thermal gyro-radii are smaller than the Debye length, the magnetic field greatly affects the plasma's relaxation processes. The expressions for the time rates of change of the electron and ion parallel and perpendicular temperatures are obtained and calculated analytically for small anisotropies through considering binary collisions between charged particles in the presence of a uniform magnetic field by using perturbation theory. Based on these expressions, the effects of the magnetic field on the relaxation of anisotropic electron and ion temperatures due to electron-electron collisions, ion-ion collisions, and electron-ion collisions are investigated. Consequently, the relaxation times of anisotropic electron and ion temperatures to isotropy are calculated. It is shown that electron-ion collisions can affect the relaxation of an anisotropic ion distribution in the strong magnetic field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Accelerating and Parallelizing Lagrangian Simulations of Mixing-Limited Reactive Transport

Recent advances in random walk particle tracking have enabled direct simulation of mixing and reactions by allowing the particles to interact with each other using a multipoint mass transfer scheme. The mass transfer scheme allows separation of mixing and spreading processes, among other advantages, but it is computationally expensive because its speed depends on the number of interacting particle pairs. This note explores methods for relieving the computational bottleneck caused by the mass transfer step, and we use these algorithms to develop a new parallel, interacting particle model. The new model is a combination of a sparse search algorithm and a novel domain decomposition scheme, both of which offer significant speedup relative to the reference case—even when they are executed serially. We combine the strengths of these methods to create a parallel particle scheme that is highly accurate and efficient with run times that scale as 1/P for a fixed number of particles, where P is the number of computational cores (equivalently, subdomains, in this work) being used. Here, the new parallel model is a significant advance because it enables efficient simulation of large particle ensembles that are needed for environmental simulations and also because it can naturally pair with parallel geochemical solvers to create a practical Lagrangian tool for simulating mixing and reactions in complex chemical systems.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity Analysis of Passive Heat Removal Capability of FHR Based on Efficient Surrogate Model and GenFlow

Code Scaling, Applicability and Uncertainty Evaluation Methodology (CSAU) is used for quantifying reactor safety margins and works as an alternative method for licensing nuclear power plant. In the framework of CSAU, sensitivity and uncertainty analysis (SA and UA) should be performed. However, for large-scale complicated thermal hydraulics analysis simulated by code (e.g. RELAP5, CFD and subchannel analysis, the sensitivity and uncertainty analysis is really time-consuming. Furthermore, sometimes it is not feasible to perform SA and UA. Specifically, the computation time for Monte Carlo sampling or advanced LHS sampling can be neglected, but the computation time for thermal hydraulics code makes up main part of time during SA and UA process. In order to accelerate the speed of SA and UA, thermal hydraulics code can be improved based on advanced mathematic algorithm or using parallel method. However, the development for new mathematic method needs long time and strict verification and validation process is needed for a new code, which usually takes a couple of years or even longer time to have an approved code that can be used in nuclear industry. An alternative way to improve the speed of SA and UA is using surrogate model. The surrogate model is derived from the input as well as output data of the original code, assuming the code as a black box. The most common method is using response surface method (RSM) as a surrogate for the code, the input parameters are then sampled from their assumed distribution and the corresponding value of the response surface function is calculated. However, a couple of input parameters need hundreds or even thousands of original code calculations. The large number of runs is an obvious disadvantage of this method. Besides, the second disadvantage is an appropriate response surface function must be selected (e.g. quadratic, cubic, quartic, with or without cross product terms, or using a non-polynomial form) to avoid the overfit and underfit problem. This process is time consuming and expensive. Polynomial chaos expansion method is a reasonably fast and attractive alternative, stochastic model. The chaos expansion provides an efficient high-order method of including non-linear effects in stochastic analysis. Usually, the information about the model parameters and their probability distribution is limited and the dependence between them is not known. However, if arbitrary polynomial chaos is used, instead of assuming probability distribution for input parameters which may introduces additional subjectivity into the analysis, the available information can directly and most purely be used in stochastic analysis based on arbitrary data distribution. Thus, it is not necessary to know the exact probability density functions to perform SA and UA based on arbitrary polynomial chaos (aPC). The aPC has been applied for uncertainty quantification in many fields (e.g. in solid mechanics, fluid flows, thermal sciences), and become widely used in nuclear industry recently. Mk1 PB-FHR is a small modular fluoride-salt-cooled, high-temperature reactors (FHRs) that is a concept design by University of California, Berkeley (UCB). It has inherently safe features like natural-circulation-driven systems (e.g. direct reactor auxiliary cooling system (DRACS)) to passively remove decay heat from the reactor core during design basis and beyond design. It is necessary to perform SA and UA, since the licensing process of this new kind of reactor is under way and there are many design parameters that have not been fixed. Current nuclear commercial codes, such as RELAP5, have mainly been developed for light water reactors, which require the use of comprehensive two-phase flow models. This capability is not required to simulate single-phase flow phenomena in FHRs, whose baseline coolant, flibe, remains liquid up to 1430 deg. C at atmospheric pressure. The FHR advanced natural circulation analysis (FANCY) code has been developed specifically for FHR technology modeling and validation work has been performed by using CIET data in UCB. The code has been renamed General Flow (GenFlow) because it has been further developed to have the capability to model complicated pipework system based on object-oriented concept for user friendly purpose. Besides, it can be used to simulate both the force circulation as well as natural circulation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A performance analysis of ensemble averaging for high fidelity turbulence simulations at the strong scaling limit

We analyze the potential performance benefits of estimating expected quantities in large eddy simulations of turbulent flows using true ensembles rather than ergodic time averaging. Multiple realizations of the same flow are simulated in parallel, using slightly perturbed initial conditions to create unique instantaneous evolutions of the flow field. Each realization is then used to calculate statistical quantities. Provided each instance is sufficiently de-correlated, this approach potentially allows considerable reduction in the time to solution beyond the strong scaling limit for a given accuracy. This study focuses on the theory and implementation of the methodology in Nek5000, a massively parallel open-source spectral element code.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

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↗

The right circular polarized waves in the three-dimensional anisotropic dispersive photonic crystals consisting of the magnetized plasma and uniaxial material as the Faraday effects considered

In this paper, the properties of the right circular polarized (RCP) waves in the three-dimensional (3D) dispersive photonic crystals (PCs) consisting of the magnetized plasma and uniaxial material with face-centered-cubic (fcc) lattices are theoretically investigated by the plane wave expansion method, which the homogeneous anisotropic dielectric spheres (the uniaxial material) immersed in the magnetized plasma background, as the Faraday effects of magnetized plasma are considered (the incidence electromagnetic wave vector is parallel to the external magnetic field at any time). The equations for calculating the anisotropic photonic band gaps (PBGs) for the RCP waves in the first irreducible Brillouin zone are theoretically deduced. The anisotropic PBGs and a flatbands region can be obtained. The effects of the ordinary-refractive index, extraordinary-refractive index, anisotropic dielectric filling factor, plasma frequency, and plasma cyclotron frequency (the external magnetic field) on the properties of first two anisotropic PBGs for the RCP waves are investigated in detail, respectively. The numerical results show that the anisotropy can open partial band gaps in fcc lattices at U and W points, and the complete PBGs for the RCP waves can be achieved compared to the conventional 3D dispersive PCs composed of the magnetized plasma and isotropic material. It is also shown that the first two anisotropic PBGs can be tuned by those parameters as mentioned above. Those PBGs can be enlarged by introducing the uniaxial material into such 3D PCs as the Faraday effects are considered.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

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↗

Cosmic-ray parallel and perpendicular transport in turbulent magnetic fields

A correct description of cosmic-ray (CR) diffusion in turbulent plasma is essential for many astrophysical and heliospheric problems. This paper aims to present the physical diffusion behavior of CRs in actual turbulent magnetic fields, a model of which has been numerically tested. We perform test particle simulations in compressible magnetohydrodynamic turbulence. We obtain scattering and spatial diffusion coefficients by tracing particle trajectories. We find no resonance gap for pitch-angle scattering at 90°. Our result confirms the dominance of mirror interaction with compressible modes for most pitch angles, as revealed by the nonlinear theory. For cross-field transport, our results are consistent with normal diffusion predicted earlier for large scales. The diffusion behavior strongly depends on the Alfvénic Mach number and the particle's parallel mean free path. We, for the first time, numerically derive the dependence of M{sub A}{sup 4} for the perpendicular diffusion coefficient with respect to the mean magnetic field. We conclude that CR diffusion coefficients are spatially correlated to the local turbulence properties. On scales smaller than the injection scale, we find that CRs are superdiffusive. We emphasize the importance of our results in a wide range of astrophysical processes, including magnetic reconnection.

79 ASTRONOMY AND ASTROPHYSICS↗

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↗