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At least 613 records · Page 34

The Evaporation and Survival of Cluster Galaxies’ Coronae. II. The Effectiveness of Anisotropic Thermal Conduction and Survival of Stripped Galactic Tails

We simulate anisotropic thermal conduction between the intracluster medium (ICM) and the hot coronal interstellar medium (ISM) gas in cluster galaxies. In Paper I, we simulated the evaporation of the hot ISM due to isotropic (possibly saturated) conduction between the ISM and ICM. We found that hot coronae evaporate on ∼10{sup 2} Myr timescales, significantly shorter than the ∼10{sup 3} Myr gas loss times due to ram pressure stripping. No tails of stripped gas are formed. This is in tension with the observed ubiquity and implied longevity of compact X-ray coronae and stripped ISM tails, and requires the suppression of evaporation, possibly due to magnetic fields and anisotropic conduction. We perform a series of wind tunnel simulations similar to that in Paper I, now including ISM and ICM magnetic fields. We simulate the effect of anisotropic conduction for a range of extreme magnetic field configurations: parallel and perpendicular to the ICM wind, and continuous and completely disjointed between the ISM and ICM. We find that when conduction is anisotropic, gas loss due to evaporation is severely reduced; the overall gas loss rates with and without anisotropic conduction do not differ by more than 10%–20%. Magnetic fields also prevent stripped tails from evaporating in the ICM by shielding, and providing few pathways for heat transport between the ICM and ISM. The morphology of stripped tails and magnetic fields in the tails and wakes of galaxies are sensitive to the initial magnetic field configuration.

79 ASTRONOMY AND ASTROPHYSICS↗

THE STAR-FORMATION-RATE-DENSITY RELATION AT 0.6 < z < 0.9 AND THE ROLE OF STAR-FORMING GALAXIES

We study the star formation rates (SFRs) of galaxies as a function of local galaxy density at 0.6 < z < 0.9. We used a low-dispersion prism in IMACS on the 6.5 m Baade (Magellan I) telescope to obtain spectra and measured redshifts to a precision of {sigma}{sub z}/(1 + z) {approx} 1% for galaxies with z{sub AB} < 23.3 mag. We utilized a stellar mass-limited sample of 977 galaxies above M > 1.8 x 10{sup 10} M{sub sun} (log M/M{sub sun} >10.25) to conduct our main analysis. With three different SFR indicators, (1) Spitzer MIPS 24 {mu}m imaging, (2) spectral energy distribution (SED) fitting, and (3) [O II]{lambda}3727 emission, we find the median specific SFR (SSFR) and SFR to decline from the low-density field to the cores of groups and a rich cluster. For the SED- and [O II]-based SFRs, the decline in SSFR is roughly an order of magnitude while for the MIPS-based SFRs, the decline is a factor of {approx}4. We find approximately the same magnitude of decline in SSFR even after removing the sample of galaxies near the cluster. Galaxies in groups and a cluster at these redshifts therefore have lower star formation (SF) activity than galaxies in the field, as is the case at z {approx} 0. We investigated whether the decline in SFR with increasing density is caused by a change in the proportion of quiescent and star-forming galaxies (SFGs) or by a decline in the SFRs of SFGs. Using the rest-frame U - V and V - J colors to distinguish quiescent galaxies from SFGs (including both unattenuated blue galaxies and reddened ones), we find that the fraction of quiescent galaxies increases from {approx}32% to 79% from low to high density. In addition, we find the SSFRs of SFGs, selected based on U - V and V - J colors, to decline with increasing density by factors of {approx}5-6 for the SED- and [O II]-based SFRs. The MIPS-based SSFRs for SFGs decline with a shallower slope. The declining SFRs of SFGs with density are paralleled by a decline in the median A{sub V}, providing indirect evidence that the cold gas content that fuels future SF is diminished in higher density environments. The order of magnitude decline in the SSFR-density relation at 0.6 < z < 0.9 is therefore driven by both a combination of declining SFRs of SFGs as well as a changing mix of SFGs and quiescent galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Streamlined spatial and environmental expression signatures characterize the minimalist duckweed Wolffia australiana

Single-cell genomics permits a new resolution in the examination of molecular and cellular dynamics, allowing global, parallel assessments of cell types and cellular behaviors through development and in response to environmental circumstances, such as interaction with water and the light–dark cycle of the Earth. Here, we leverage the smallest, and possibly most structurally reduced, plant, the semiaquaticWolffia australiana, to understand dynamics of cell expression in these contexts at the whole-plant level. We examined single-cell-resolution RNA-sequencing data and foundWolffiacells divide into four principal clusters representing the above- and below-water-situated parenchyma and epidermis. Although these tissues share transcriptomic similarity with model plants, they display distinct adaptations thatWolffiahas made for the aquatic environment. Within this broad classification, discrete subspecializations are evident, with select cells showing unique transcriptomic signatures associated with developmental maturation and specialized physiologies. Assessing this simplified biological system temporally at two key time-of-day (TOD) transitions, we identify additional TOD-responsive genes previously overlooked in whole-plant transcriptomic approaches and demonstrate that the core circadian clock machinery and its downstream responses can vary in cell-specific manners, even in this simplified system. Distinctions between cell types and their responses to submergence and/or TOD are driven by expression changes of unexpectedly few genes, characterizingWolffiaas a highly streamlined organism with the majority of genes dedicated to fundamental cellular processes.Wolffiaprovides a unique opportunity to apply reductionist biology to elucidate signaling functions at the organismal level, for which this work provides a powerful resource.

Biochemistry & Molecular Biology↗

Designing Next Generation Massively Multithreaded Architectures for Irregular Applications

Irregular applications, such as data mining or graph-based computations, show unpredictable memory/network access patterns and control structures. Massively multi-threaded architectures with large node count, like the Cray XMT, have been shown to address their requirements better than commodity clusters. In this paper we present the approaches that we are currently pursuing to design future generations of these architectures. First, we introduce the Cray XMT and compare it to other multithreaded architectures. We then propose an evolution of the architecture, integrating multiple cores per node and next generation network interconnect. We advocate the use of hardware support for remote memory reference aggregation to optimize network utilization. For this evaluation we developed a highly parallel, custom simulation infrastructure for multi-threaded systems. Our simulator executes unmodified XMT binaries with very large datasets, capturing effects due to contention and hot-spotting, while predicting execution times with greater than 90% accuracy. We also discuss the FPGA prototyping approach that we are employing to study efficient support for irregular applications in next generation manycore processors.

Tumeo, Antonino↗

Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.

59 BASIC BIOLOGICAL SCIENCES↗

Hyperspectral Aquatic Radiative Transfer Modeling Using a High-Performance Cluster Computing-Based Approach

Abstract For aquatic studies, radiative transfer (RT) modeling can be used to compute hyperspectral above-surface remote sensing reflectance that can be utilized for inverse model development. Inverse models can provide bathymetry and inherent-and bottom-optical property estimation. Because measured oceanic field/organic datasets are often spatio-temporally sparse, synthetic data generation is useful in yielding sufficiently large datasets for inversion model development; however, these forward-modeled data are computationally expensive and time-consuming to generate. This study establishes the magnitude of wall-clock-time savings achieved for performing large, aquatic RT batch-runs using parallel computing versus a sequential approach. Given 2,600 simulations and identical compute-node characteristics, sequential architecture required ~100 hours until termination, whereas a parallel approach required only ~2.5 hours (42 compute nodes) a 40x speed-up. Tools developed for this parallel execution are discussed.

58 GEOSCIENCES↗

Parallelization of a Proxy Transport App Using ComputeCPP and SYCL

This document details the attempts to parallelize a multi-group Monte Carlo proxy app using SYCL and the ComputeCPP Community Edition compiler. SYCL is a standard set by the Khronos Group and is described as a, “cross-platform abstraction layer that builds on the underlying concepts, portability and efficiency of OpenCL that enables code for heterogeneous processors to be written in a “single-source” style using completely standard C++.” ComputeCpp Community Edition (CE) is a heterogeneous parallel programming platform that provides a conformant implementation of the SYCL™ 1.2.1 Khronos specification. ComputeCPP provides a compiler and an SDK containing a build system to improve the usability of the compiler. The supported OpenCL 1.2 platforms for ComputeCpp are AMD® and Intel®, with experimental support for PTX which is used on Nvidia graphics cards as well as experimental support for ARM chips. All testing reported in this document was done on the Darwin computer cluster using an Nvidia GTX Titan X graphics card. Since ComputeCPP does not support using this card with OpenCL, ComputeCPP’s experimental PTX64 bit-code generation was used to generate device code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The features of X-ray topographic contrast formation in silicon with dislocation clusters

The features of formation of diffraction images of edge dislocation sets forming clusters (of two, three and more dislocations) as well as small-angle dislocation boundaries (walls) have been studied. A variety of diffraction effects of wave fields created in strongly distorted crystals regions along dislocation lines have been observed. Various intensity interference effects of rescattering and internal reflection of the newly formed and already existing wave fields on thickness distributions of intensity for the case of presence in the same glide plane of edge dislocations with parallel and anti-parallel Burgers vectors were discovered.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Using Apptainer in a Pilot-based Distributed Workload

GlideinWMS is a pilot and pressure-based workload manager for distributed scientific computing. Many experiments like CMS and Fermilab’s Neutrino experiments use it to provision elastic clusters for their analysis and simulations, split into close to a million concurrent jobs. Most user jobs require containers, and the pilots use Apptainer to set up the desired platform. For the pilots that run as regular batch jobs, Apptainer is safer, lighter, and easier to use than other containerization solutions. Many images used by the pilots are expanded SIF images distributed via the CernVM-FS: this combination is very efficient. At Fermilab, for example, we store on GitHub Dockerfiles that mimic the platform in the worker nodes of local clusters. GitHub workflows build and push the images to Docker Hub, and a service periodically pulls and converts them to the expanded SIF images in the CernVM-FS, so the scientists can find a familiar environment everywhere. Apptainer has also been used to run services inside the pilot jobs, like benchmarks that characterize the worker node being used, or a Triton Inference Server that allows sharing a GPU with all the jobs that run in parallel on a node.

Mambelli, Marco [Fermilab] (ORCID:0000000294892681↗

Dynamic phases, clustering, and chain formation for driven disk systems in the presence of quenched disorder

In this paper, we numerically examine the dynamic phases and pattern formation of two-dimensional monodisperse repulsive disks driven over random quenched disorder. We show that there is a series of distinct dynamic regimes as a function of increasing drive, including a clogged or pile-up phase near depinning, a homogeneous disordered flow state, and a dynamically phase separated regime consisting of high-density crystalline regions surrounded by a low density of disordered disks. At the highest drives the disks arrange into one-dimensional moving chains. The phase separated regime has parallels with the phase separation observed in active matter systems, but arises from a distinct mechanism consisting of the combination of nonequilibrium fluctuations with density-dependent mobility. We discuss the pronounced differences between this system and previous studies of driven particles with longer-range repulsive interactions moving over random substrates, such as superconducting vortices or electron crystals, where dynamical phase separation and distinct one-dimensional moving chains are not observed. Finally, our results should be generic to a broad class of systems in which the particle-particle interactions are short ranged, such as sterically interacting colloids or Yukawa particles with strong screening driven over random pinning arrays, superconducting vortices in the limit of small penetration depths, or quasi-two-dimensional granular matter flowing over rough landscapes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stochastic density functional theory

Linear-scaling implementations of density functional theory (DFT) reach their intended efficiency regime only when applied to systems having a physical size larger than the range of their Kohn–Sham density matrix (DM). This causes a problem since many types of large systems of interest have a rather broad DM range and are therefore not amenable to analysis using DFT methods. For this reason, the recently proposed stochastic DFT (sDFT), avoiding exhaustive DM evaluations, is emerging as an attractive alternative linear-scaling approach. This review develops a general formulation of sDFT in terms of a (non)orthogonal basis representation and offers an analysis of the statistical errors (SEs) involved in the calculation. Using a new Gaussian-type basis-set implementation of sDFT, applied to water clusters and silicon nanocrystals, it demonstrates and explains how the standard deviation and the bias depend on the sampling rate and the system size in various types of calculations. We also develop a basis-set embedded-fragments theory, demonstrating its utility for reducing the SEs for energy, density of states and nuclear force calculations. Finally, we discuss the algorithmic complexity of sDFT, showing it has CPU wall-time linear-scaling. Lastly, the method parallelizes well over distributed processors with good scalability and therefore may find use in the upcoming exascale computing architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A generalized parallel replica dynamics

Metastability is a common obstacle to performing long molecular dynamics simulations. Many numerical methods have been proposed to overcome it. One method is parallel replica dynamics, which relies on the rapid convergence of the underlying stochastic process to a quasi-stationary distribution. Two requirements for applying parallel replica dynamics are knowledge of the time scale on which the process converges to the quasi-stationary distribution and a mechanism for generating samples from this distribution. By combining a Fleming–Viot particle system with convergence diagnostics to simultaneously identify when the process converges while also generating samples, we can address both points. This variation on the algorithm is illustrated with various numerical examples, including those with entropic barriers and the 2D Lennard-Jones cluster of seven atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Cold rolling texture evolution of TiB2 particle reinforced Al-based composites by Neutron Diffraction and EBSD analysis

Highlights: • Texture development of in-situ TiB{sub 2} particle reinforced Al matrix composites after cold rolling were characterized. • The sum of rolling texture volume fractions has been significantly reduced by the weak texture in particle deformation zone. • Recrystallization nuclei with the Cube and Rotated-Cube orientations were observed in the particle deformation zones. • Small TiB{sub 2} particles within Al grains kept the parallel relationship with surrounding matrix during the deformation. - Abstract: Texture development of particle-reinforced metal matrix materials (P-MMCs) has not been understood well, especially the effects of second-phase particles during the deformation. In this work, we have investigated the texture evolution of TiB{sub 2}/Al composites during cold rolling by Neutron Diffraction and EBSD analysis. Two forms of TiB{sub 2} particles influenced the texture evolution in different ways. The particle-clusters aggregated along grain boundaries led to a reduction of texture volume fraction; recrystallization nuclei with weak texture appeared around these particle-clusters. Small non-shearable TiB{sub 2} particles dispersed inside Al matrix contributed to strong Copper texture component at high strains; the individual particles rotated together with Al matrix during the deformation. These revealed effects of particles on the texture development in TiB{sub 2}/Al composites provide a reference for the texture control of P-MMCs.

36 MATERIALS SCIENCE↗

GAtor: A First-Principles Genetic Algorithm for Molecular Crystal Structure Prediction

We present the implementation of GAtor, a massively parallel, first-principles genetic algorithm (GA) for molecular crystal structure prediction. GAtor is written in Python and currently interfaces with the FHI-aims code to perform local optimizations and energy evaluations using dispersion-inclusive density functional theory (DFT). GAtor offers a variety of fitness evaluation, selection, crossover, and mutation schemes. Breeding operators designed specifically for molecular crystals provide a balance between exploration and exploitation. Evolutionary niching is implemented in GAtor by using machine learning to cluster the dynamically updated population by structural similarity and then employing a cluster-based fitness function. Evolutionary niching promotes uniform sampling of the potential energy surface by evolving several subpopulations, which helps overcome initial pool biases and selection biases (genetic drift). The various settings offered by GAtor increase the likelihood of locating numerous low-energy minima, including those located in disconnected, hard to reach regions of the potential energy landscape. The best structures generated are re-relaxed and re ranked using a hierarchy of increasingly accurate DFT functionals and dispersion methods. GAtor is applied to a chemically diverse set of four past blind test targets, characterized by different types of intermolecular interactions. Furthermore, the experimentally observed structures and other low-energy structures are found for all four targets. In particular, for Target II, 5-cyano-3-hydroxythiophene, the top ranked putative crystal structure is a Z' = 2 structure with PT symmetry and a scaffold packing motif, which has not been reported previously.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Making many-body interactions nearly pairwise additive: The polarized many-body expansion approach

The Many-Body Expansion (MBE) is a useful tool to simulate condensed phase chemical systems, often avoiding the steep computational cost of usual electronic structure methods. However, it often requires higher than 2-body terms to achieve quantitative accuracy. In this work, we propose the Polarized MBE (PolBE) method where each MBE energy contribution is treated as an embedding problem. In each energy term, a smaller fragment is embedded into a larger, polarized environment and only a small region is treated at the high-level of theory using embedded mean-field theory. The role of polarized environment was found to be crucial in providing quantitative accuracy at the 2-body level. PolBE accurately predicts noncovalent interaction energies for a number of systems, including CO 2 , water, and hydrated ion clusters, with a variety of interaction mechanisms, from weak dispersion to strong electrostatics considered in this work. We further demonstrate that the PolBE interaction energy is predominantly pairwise unlike the usual vacuum MBE that requires higher-order terms to achieve similar accuracy. We numerically show that PolBE often performs better than other widely used embedded MBE methods such as the electrostatically embedded MBE. Finally,owing to the lack of expensive diagonalization of Fock matrices and its embarrassingly parallel nature, PolBE is a promising way to access condensed phase systems with hybrid density functionals that are difficult to treat with currently available methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Integrated View of Hydraulic Induced Fracture Geometry in Hydraulic Fracture Test Site 2

Until relatively recently, most of our understanding about the geometry of hydraulically induced fractures in unconventional reservoirs has been inferred by patterns observed via microseismic monitoring. Important information, such as fracture-azimuth, fracture-length, height-growth and other geometric data has been determined from microseismic “event clouds”, which in turn has been used to interpret a stimulated reservoir volume (SRV). It is important to note that relatively limited microseismic results have been acquired in conjunction with other diagnostics and validated in a consistent manner. The Hydraulic Fracture Test Site 2 (HFTS2) in the Permian Delaware Basin provides a unique opportunity to compare the frac geometry interpretations derived from multiple frac diagnostic tools and at multiple scales. The integrated view that emerges from all the frac diagnostic tools is that in HFTS2 the geometries of hydraulically induced fractures are not random and with a highly complex branching architecture. In fact, the fracs are mostly vertical, parallel plana domains, and both vertically and horizontally asymmetrical. The hydraulically induced fractures have a very consistent azimuth with a strike that matches SHmax. At the distance corresponding to the spacing between nearby wells in HFTS2, ~ 660 ft, the pattern of strain interceptions observed from Low Frequency Distributed Acoustic Sensing (LF-DAS) shows far-field dimensions that are consistent with the stage length dimensions at the stimulated well. In general, larger stages with higher number of clusters create larger number of interceptions and wider stimulated intervals than that of shorter stages with the same cluster to cluster spacing and fewer clusters. The hydraulically induced fractures also show a clear tendency to preferentially grow upwards as shown by the microseismic data, by the relative lower number of LF-DAS interceptions in nearby deeper wells and finally by the observed LF-DAS strain patterns in the vertical observation well. In the near field, the geometries of the fracture domains are also consistent. As shown by the distributed strain measurements obtained during production via the monitoring of Rayleigh Frequency Shift (RFS), each cluster has a separate, non-overlapping, frac-zone-domain that are generally centered around the locations of each perforation cluster. Overall, the hydraulically induced fractures in HFTS2 are interpreted as occurring in swarms associated with individual clusters, each with its own unique geometry but with similar predictable geometric and propagation tendencies. The comprehensive frac diagnostic program in HFTS2, the well-pad layout that permits the investigation of the Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S018R003/2477511/urtec-2021-5396-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5396 2 impact that nearby producing wells has on frac geometry, together with an innovative Design of Experiment (DofE) that includes sequential-fracing, consistent cluster-to-cluster distances and few single-perforation cluster stages, has allowed us to gain a unique perspective about the geometry of the induced hydraulic fractures on this pad. Finally, the HFTS2 dataset has also provided us with a better understanding of the applicability and limitations of the different diagnostic tools.

58 GEOSCIENCES↗

A Brief Summary on Formalizing Parallel Tensor Distributions, Redistributions, and Algorithm Derivations

Large-scale datasets in computational chemistry typically require distributed-memory parallel methods to perform a special operation known as tensor contraction. Tensors are multidimensional arrays, and a tensor contraction is akin to matrix multiplication with special types of permutations. Creating an efficient algorithm and optimized implementation in this domain is complex, tedious, and error-prone. To address this, we develop a notation to express data distributions so that we can apply use automated methods to find optimized implementations for tensor contractions. We consider the spin-adapted coupled cluster singles and doubles method from computational chemistry and use our methodology to produce an efficient implementation. Experiments per- formed on the IBM Blue Gene/Q and Cray XC30 demonstrate impact both improved performance and reduced memory consumption.

97 MATHEMATICS AND COMPUTING↗