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At least 991 records · Page 55

Bridging the Homogeneous-Heterogeneous Divide: Modeling Spin for Reactivity in Single Atom Catalysis

Single atom catalysts (SACs) are emergent catalytic materials that have the promise of merging the scalability of heterogeneous catalysts with the high activity and atom economy of homogeneous catalysts. Computational, first-principles modeling can provide essential insight into SAC mechanism and active site configuration, where the sub-nm-scale environment can challenge even the highest-resolution experimental spectroscopic techniques. Nevertheless, the very properties that make SACs attractive in catalysis, such as localized d electrons of the isolated transition metal center, make them challenging to study with conventional computational modeling using density functional theory (DFT). For example, Fe/N-doped graphitic SACs have exhibited spin-state dependent reactivity that remains poorly understood. However, spin-state ordering in DFT is very sensitive to the nature of the functional approximation chosen. In this work, we develop accurate benchmarks from correlated wavefunction theory (WFT) for relevant octahedral complexes. We use those benchmarks to evaluate optimal DFT functional choice for predicting spin state ordering in small octahedral complexes as well as models of pyridinic and pyrrolic nitrogen environments expected in larger SACs. Using these guidelines, we determine Fe/N-doped graphene SAC model properties and reactivity as well as their sensitivities to DFT functional choice. Finally, we conclude with broad recommendations for computational modeling of open-shell transition metal single-atom catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Multi-Objective Approach for Optimizing Edge-Based Resource Allocation Using TOPSIS

Existing approaches for allocating resources on edge environments are inefficient and lack the support of heterogeneous edge devices, which in turn fail to optimize the dependency on cloud infrastructures or datacenters. To this extent, we propose in this paper OpERA, a multi-layered edge-based resource allocation optimization framework that supports heterogeneous and seamless execution of offloadable tasks across edge, fog, and cloud computing layers and architectures. By capturing offloadable task requirements, OpERA is capable of identifying suitable resources within nearby edge or fog layers, thus optimizing the execution process. Throughout the paper, we present results which show the effectiveness of our proposed optimization strategy in terms of reducing costs, minimizing energy consumption, and promoting other residual gains in terms of processing computations, network bandwidth, and task execution time. We also demonstrate that by optimizing resource allocation in computation offloading, it is then possible to increase the likelihood of successful task offloading, particularly for computationally intensive tasks that are becoming integral as part of many IoT applications such robotic surgery, autonomous driving, smart city monitoring device grids, and deep learning tasks. The evaluation of our OpERA optimization algorithm reveals that the TOPSIS MCDM technique effectively identifies optimal compute resources for processing offloadable tasks, with a 96% success rate. Moreover, the results from our experiments with a diverse range of use cases show that our OpERA optimization strategy can effectively reduce energy consumption by up to 88%, and operational costs by 76%, by identifying relevant compute resources.

97 MATHEMATICS AND COMPUTING↗

Simulation studies of the physical and chemical processes occurring in the stratospheric clouds of the Mount St. Helens eruptions of May and June 1980

The large and diverse set of observational data collected in the high-altitude clouds of May 18, May 25, and June 13, 1980 was organized and analyzed for trends which reveal the processes at work. The data were used to guide and constrain model simulations of the volcanic eruptions. A comprehensive one-dimensional model of stratospheric sulfate aerosols, sulfur precursor gases, and volcanic ash and dust particles is utilized which accounts for homogeneous and heterogeneous chemistry in the clouds, aerosol nucleation and growth, and cloud expansion. Computational results are given for the time histories of the gaseous species concentrations, sulfate aerosol size dispersions, and ash burdens in the eruption clouds. The long-term buildup of stratospheric aerosols in the Northern Hemisphere and the persistent effects of injected chlorine and water vapor on ozone are discussed. It is concluded that SO2, water vapor, and ash are the most important substances injected by the volcano into the stratosphere, with respect to both the widespread effects on composition and the impact on climate. It is found that the volcano probably had little influence on the climate ( 0.05 K global surface cooling) or on stratospheric ozone ( 0.2 percent maximum hemispherical reduction).

Turco, R. P.↗

The 1980 eruptions of Mount St. Helens - Physical and chemical processes in the stratospheric clouds

The large and diverse set of observational data collected in the high-altitude plumes of the May 18, May 25, and June 13, 1980 eruptions is organized and analyzed with a view to discerning the processes at work. The data serve to guide and constrain detailed model simulations of the volcanic clouds. For this purpose, use is made of a comprehensive one-dimensional model of stratospheric sulfate aerosols, sulfur precursor gases, and volcanic ash and dust. The model takes into account gas-phase and condensed-phase (heterogeneous) chemistry in the clouds, aerosol nucleation and growth, and cloud expansion. Computational results are presented for the time histories of the gaseous species concentrations, aerosol size distributions, and ash burdens of the eruption clouds. Also investigated are the long-term buildup of stratospheric aerosols in the Northern Hemisphere and the persistent effects of injected chlorine and water vapor on stratospheric ozone. It is concluded that SO2, water vapor, and ash were probably the most important substances injected into the stratosphere by the Mount St. Helens volcano, both with respect to their widespread effects on composition and their effect on climate.

Turco, R. P.↗

Light Scattering by Nonspherical Particles

Improved understanding of electromagnetic scattering by nonspherical particles is important to many science and engineering disciplines and was the subject of the Conference on Light Scattering by Nonspherical Particles: Theory, Measurements, and Applications. The conference was held 29 September-1 October 1998 at the Goddard Institute for Space Studies in New York City and brought together 115 participants from 18 countries. The main objective of the conference was to highlight and summarize the rapid advancements in the field, including numerical methods for computing the single and multiple scattering of electromagnetic radiation by nonspherical and heterogeneous particles, measurement approaches, knowledge of characteristic features in scattering patterns, retrieval and remote sensing techniques, nonspherical particle sizing, and various practical applications. The conference consisted of twelve oral and one poster sessions. The presentations were loosely grouped based on broad topical categories. In each of these categories invited review talks highlighted and summarized specific active areas of research. To ensure a high-quality conference, all abstracts submitted had been reviewed by members of the Scientific Organizing Committee for technical merit and content. The conference program was published in the June 1998 issue of the Bulletin of the American Meteorological Society and is available on the World Wide Web at http://www.giss.nasa.gov/-crmim/conference/program.html. Authors of accepted papers and review presentations contributed to a volume of preprints published by the American Meteorological Society' and distributed to participants at the conference.

Mishchenko, Michael I.↗

First-Principles Modeling Of Electromagnetic Scattering By Discrete and Discretely Heterogeneous Random Media

A discrete random medium is an object in the form of a finite volume of a vacuum or a homogeneous material medium filled with quasi-randomly and quasi-uniformly distributed discrete macroscopic impurities called small particles. Such objects are ubiquitous in natural and artificial environments. They are often characterized by analyzing theoretically the results of laboratory, in situ, or remote-sensing measurements of the scattering of light and other electromagnetic radiation. Electromagnetic scattering and absorption by particles can also affect the energy budget of a discrete random medium and hence various ambient physical and chemical processes. In either case electromagnetic scattering must be modeled in terms of appropriate optical observables, i.e., quadratic or bilinear forms in the field that quantify the reading of a relevant optical instrument or the electromagnetic energy budget. It is generally believed that time-harmonic Maxwell's equations can accurately describe elastic electromagnetic scattering by macroscopic particulate media that change in time much more slowly than the incident electromagnetic field. However, direct solutions of these equations for discrete random media had been impracticable until quite recently. This has led to a widespread use of various phenomenological approaches in situations when their very applicability can be questioned. Recently, however, a new branch of physical optics has emerged wherein electromagnetic scattering by discrete and discretely heterogeneous random media is modeled directly by using analytical or numerically exact computer solutions of the Maxwell equations. Therefore, the main objective of this Report is to formulate the general theoretical framework of electromagnetic scattering by discrete random media rooted in the Maxwell- Lorentz electromagnetics and discuss its immediate analytical and numerical consequences. Starting from the microscopic Maxwell-Lorentz equations, we trace the development of the first principles formalism enabling accurate calculations of monochromatic and quasi-monochromatic scattering by static and randomly varying multiparticle groups. We illustrate how this general framework can be coupled with state-of-the-art computer solvers of the Maxwell equations and applied to direct modeling of electromagnetic scattering by representative random multi-particle groups with arbitrary packing densities. This first-principles modeling yields general physical insights unavailable with phenomenological approaches. We discuss how the first-order-scattering approximation, the radiative transfer theory, and the theory of weak localization of electromagnetic waves can be derived as immediate corollaries of the Maxwell equations for very specific and well-defined kinds of particulate medium. These recent developments confirm the mesoscopic origin of the radiative transfer, weak localization, and effective-medium regimes and help evaluate the numerical accuracy of widely used approximate modeling methodologies.

Michael I Mishchenko↗

Hardware Architectures for Data-Intensive Computing Problems: A Case Study for String Matching

DNA analysis is an emerging application of high performance bioinformatic. Modern sequencing machinery are able to provide, in few hours, large input streams of data, which needs to be matched against exponentially growing databases of known fragments. The ability to recognize these patterns effectively and fastly may allow extending the scale and the reach of the investigations performed by biology scientists. Aho-Corasick is an exact, multiple pattern matching algorithm often at the base of this application. High performance systems are a promising platform to accelerate this algorithm, which is computationally intensive but also inherently parallel. Nowadays, high performance systems also include heterogeneous processing elements, such as Graphic Processing Units (GPUs), to further accelerate parallel algorithms. Unfortunately, the Aho-Corasick algorithm exhibits large performance variability, depending on the size of the input streams, on the number of patterns to search and on the number of matches, and poses significant challenges on current high performance software and hardware implementations. An adequate mapping of the algorithm on the target architecture, coping with the limit of the underlining hardware, is required to reach the desired high throughputs. In this paper, we discuss the implementation of the Aho-Corasick algorithm for GPU-accelerated high performance systems. We present an optimized implementation of Aho-Corasick for GPUs and discuss its tradeoffs on the Tesla T10 and he new Tesla T20 (codename Fermi) GPUs. We then integrate the optimized GPU code, respectively, in a MPI-based and in a pthreads-based load balancer to enable execution of the algorithm on clusters and large sharedmemory multiprocessors (SMPs) accelerated with multiple GPUs.

Tumeo, Antonino↗

ULO_2.4W

ULO_2.4W is a computer program that can be used to model elastic wave propagation in heterogeneous media from earthquake (souble couple) point sources. The program is a modified version of the orginal program ULO_2.4 developed by Arben Pitarka. The modifications allow for treatment of solid liquid boundary conditions.

Pitarka, A.↗

Performance Assessment of OpenMP Compilers Targeting NVIDIA V100 GPUs

Heterogeneous systems are becoming increasingly prevalent. In order to exploit the rich compute resources of such systems, robust programming models are needed for application developers to seamlessly migrate legacy code from today’s systems to tomorrow’s. Over the past decade and more, directives have been established as one of the promising paths to tackle programmatic challenges on emerging systems. This work focuses on applying and demonstrating OpenMP offloading directives on five proxy applications. We observe that the performance varies widely from one compiler to the other; a crucial aspect of our work is reporting best practices to application developers who use OpenMP offloading compilers. While some issues can be worked around by the developer, there are other issues that must be reported to the compiler vendors. By restructuring OpenMP offloading directives, we gain an 18x speedup for the su3 proxy application on NERSC’s Cori system when using the Clang compiler, and a 15.7x speedup by switching max reductions to add reductions in the laplace mini-app when using the Cray-llvm compiler on Cori.

Davis, Josh↗

Heterogeneous Visualization: A Call for Empirically Driven Technology Advancement and Adoption; Preprint

Our ability to generate data from simulations and experimental platforms is generally outpacing our ability to analyze those data efficiently and effectively. There are a growing number and variety of possible visualization display modalities, from commodity head-mounted displays to large-scale immersive environments, from desktop and touch displays to high-resolution display walls. Many of these visualization technologies and visual environments are rapidly evolving and could revolutionize analysis for certain classes of complex scientific and engineering data. However, the choice of what technology or combination of technologies to use has historically been largely ad hoc and lacks a carefully validated understanding of how to best utilize different visualization technologies to advance the science. To maximize the impact of our data and analyses, it is imperative that we use the most effective visualization environments for the analysis task at hand.

heterogeneous visualization↗

Uncertainty propagation in full-core Monte Carlo depletion simulations using Serpent

The desire to accurately model the heterogeneity of the nuclear reactor environment combined with the ever more powerful computational resources have made in recent years the use of Monte Carlo method more attractive and feasible (if challenging) even for 3-D full core depletion simulation. However, in this case statistical uncertainty is combined with error propagating through the calculation from previous steps. In an effort to understand this error propagation, a numerical study was undertaken and previously reported modeling depletion of a four fuel assemblies (a 'quad'). This work extends results and analysis on a full nuclear reactor core depletion simulation where isotopics of individual fuel pins is tracked. By changing the code's initial random number seed, the data produced by a series of 19 replica runs was used to investigate the true and apparent variance in k{sub eff} and pin powers. It is hoped that this results can help to identify some common regularities in the behavior of uncertainty in several key parameters, and ultimately develop a predictive model. (authors)

97 MATHEMATICS AND COMPUTING↗

Verifying infectious disease scenario planning for geographically diverse populations

In the face of the COVID-19 pandemic, the literature saw a spike in publications for epidemic models, and a renewed interest in capturing contact networks and geographic movement of populations. There remains a general lack of consensus in the modeling community around best practices for spatiotemporal epi-modeling, specifically as it pertains to the infection rate formulation and the underlying contact or mixing model. We mathematically verify several common modeling assumptions in the literature, to prove when certain choices can provide consistent results across different geographic resolutions, population densities and patterns, and mixing assumptions. The most common infection rate formulation, a computationally low cost per capita infection rate assumption, fails the consistency tests for heterogeneous populations and gravity-weighting assumptions. Future modeling efforts in spatiotemporal disease modeling should be wary of this limitation, particularly when working with more heterogeneous or sparse populations. Our results provide guidance for testing that a model preserves desirable properties even when model inputs mask potential problems due to symmetry or homogeneity. We also provide a recipe for performing this type of verification, strengthening decision support tools.

59 BASIC BIOLOGICAL SCIENCES↗

Deep Learning for Simultaneous Inference of Hydraulic and Transport Properties

Abstract Identification of a heterogeneous conductivity field and reconstruction of a contaminant release history are key aspects of subsurface remediation. These two goals are achieved by combining model predictions with sparse and noisy hydraulic head and concentration measurements. Solution of this inverse problem is notoriously difficult due to, in part, high dimensionality of the parameter space and high computational cost of repeated forward solves. We use a convolutional adversarial autoencoder (CAAE) to parameterize a heterogeneous non‐Gaussian conductivity field via a low‐dimensional latent representation. A three‐dimensional dense convolutional encoder‐decoder (DenseED) network serves as a forward surrogate of the flow and transport model. The CAAE‐DenseED surrogate is fed into the ensemble smoother with multiple data assimilation (ESMDA) algorithm to sample from the Bayesian posterior distribution of the unknown parameters, forming a CAAE‐DenseED‐ESMDA inversion framework. The resulting CAAE‐DenseED‐ESMDA inversion strategy is used to identify a three‐dimensional contaminant source and conductivity field. A comparison of the inversion results from CAAE‐ESMDA with physical flow and transport simulator and from CAAE‐DenseED‐ESMDA shows that the latter yields accurate reconstruction results at the fraction of the computational cost of the former.

Zhou, Zitong↗

Using Pilot Jobs and CernVM File System for Simplified Use of Containers and Software Distribution

High Energy Physics (HEP) experiments entail an abundance of computing resources, i.e. sites, to run simulations and analyses by processing data. This requirement is fulfilled by local batch farms, grid sites, private/commercial clouds, and supercomputing centers via High Throughput Computing (HTC). The growing needs of such experiments and resources being prone to trends of heterogeneity make it difficult for physicists to handle these resources directly. Additionally, HEP collaborations heavily rely on data and software releases, typically in the order of tens of gigabytes, while conducting simulations and analyses. Hence, aspects of scalability, reliability, and maintenance become crucial with regards to the distribution of the necessary data and software stack. The GlideinWMS [4] framework helps with the resource management problem by using pilot jobs, aka Glideins, to provision reliable elastic virtual clusters. Glideins are submitted to unreliable heterogeneous resources which are validated and customized by the Glideins to make the worker nodes available for end-user job execution. On the other hand, the CernVM File System (CernVM-FS or CVMFS) [1] helps with data distribution. It is a write-once, read-everywhere filesystem used to deploy scientific software to thousands of nodes on a worldwide distributed computing infrastructure. CVMFS is based on the Hyper Text Transfer Protocol and has been widely used within the particle physics community for (1) distributing experiment software and data such as calibrations, and (2) facilitating containerization by efficiently hosting container images along with providing containerization software, especially Singularity [3] GlideinWMS relies on CVMFS installed locally on the computing resources to satisfy the experiments' software needs. This requires system administrators' effort to install and maintain CVMFS at the sites and limits the use of sites, especially HPC resources, that do not have CVMFS installed. This poster presents a solution, taking advantage of Glideins to provide CVMFS at most sites without the need for a local installation. Doing so expands the pool of resources available for HEP experiments and reduces the effort of system administrators for current resources. Additionally, the proposed solution allows GlideinWMS to also start Singularity [3], a containerization software that can run unprivileged, on sites where neither CVMFS nor Singularity are available, including HPC sites. The benefits provided by this solution are: (1) lower overhead for site administrators in that they have less software to install, (2) an expanded pool of resources that run user jobs with easy access to software and data provided by CVMFS, thus making life easier for the scientists, and (3) improved flexibility to use HPC resources by enabling GlideinWMS pilot jobs to support HPC sites.

Urs, Namratha↗

Influence of longitudinal isotope substitution on the thermal conductivity of carbon nanotubes: Results of nonequilibrium molecular dynamics and local density functional calculations

We report reverse nonequilibrium molecular dynamics calculations of the thermal conductivity of isotope substituted (10,10) carbon nanotubes (CNTs) at 300 K. {sup 12}C and {sup 14}C isotopes both at 50% content were arranged either randomly, in bands running parallel to the main axis of the CNTs or in bands perpendicular to this axis. It is found that the systems with randomly distributed isotopes yield significantly reduced thermal conductivity. In contrast, the systems where the isotopes are organized in patterns parallel to the CNTs axis feature no reduction in thermal conductivity when compared with the pure {sup 14}C system. Moreover, a reduction of approximately 30% is observed in the system with the bands of isotopes running perpendicular to the CNT axis. The computation of phonon dispersion curves in the local density approximation and classical densities of vibrational states reveal that the phonon structure of carbon nanotubes is conserved in the isotope substituted systems with the ordered patterns, yielding high thermal conductivities in spite of the mass heterogeneity. In order to complement our conclusions on the {sup 12}C-{sup 14}C mixtures, we computed the thermal conductivity of systems where the {sup 14}C isotope was turned into pseudo-atoms of 20 and 40 atomic mass units.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data Mining Critical Infrastructure Systems: Models and Tools

Critical infrastructures (CIs) such as power, water, transportation, and telecommunication are highly complex interacting systems that are vital to national security, economy and public life. They play an important role in several core urban computing challenges. Advances in computing resources and techniques have led to enormous progress in developing intelligent frameworks for analyzing these large heterogeneous systems. In this article, we survey state-of-the-art and foundational work in this upcoming area from a data mining perspective. We discuss basic concepts of CIs, their properties, impacts on them due to natural or human-caused disturbances and different computational methodologies used for modeling and understanding their behavior. We also discuss recent work that specifically deals with two critical sectors of CIs, namely power and transportation systems. Lastly, we also describe several existing tools and methods that are used to facilitate decision making for domain operators, enable efficient and faster disaster response for federal and state agencies and help improve the security and resiliency of these CIs.

97 MATHEMATICS AND COMPUTING↗

A simplified approach to characterizing a kilovoltage source spectrum for accurate dose computation

Purpose: To investigate and validate the clinical feasibility of using half-value layer (HVL) and peak tube potential (kVp) for characterizing a kilovoltage (kV) source spectrum for the purpose of computing kV x-ray dose accrued from imaging procedures. To use this approach to characterize a Varian Registered-Sign On-Board Imager Registered-Sign (OBI) source and perform experimental validation of a novel in-house hybrid dose computation algorithm for kV x-rays. Methods: We characterized the spectrum of an imaging kV x-ray source using the HVL and the kVp as the sole beam quality identifiers using third-party freeware Spektr to generate the spectra. We studied the sensitivity of our dose computation algorithm to uncertainties in the beam's HVL and kVp by systematically varying these spectral parameters. To validate our approach experimentally, we characterized the spectrum of a Varian Registered-Sign OBI system by measuring the HVL using a Farmer-type Capintec ion chamber (0.06 cc) in air and compared dose calculations using our computationally validated in-house kV dose calculation code to measured percent depth-dose and transverse dose profiles for 80, 100, and 125 kVp open beams in a homogeneous phantom and a heterogeneous phantom comprising tissue, lung, and bone equivalent materials. Results: The sensitivity analysis of the beam quality parameters (i.e., HVL, kVp, and field size) on dose computation accuracy shows that typical measurement uncertainties in the HVL and kVp ({+-}0.2 mm Al and {+-}2 kVp, respectively) source characterization parameters lead to dose computation errors of less than 2%. Furthermore, for an open beam with no added filtration, HVL variations affect dose computation accuracy by less than 1% for a 125 kVp beam when field size is varied from 5 Multiplication-Sign 5 cm{sup 2} to 40 Multiplication-Sign 40 cm{sup 2}. The central axis depth dose calculations and experimental measurements for the 80, 100, and 125 kVp energies agreed within 2% for the homogeneous and heterogeneous block phantoms, and agreement for the transverse dose profiles was within 6%. Conclusions: The HVL and kVp are sufficient for characterizing a kV x-ray source spectrum for accurate dose computation. As these parameters can be easily and accurately measured, they provide for a clinically feasible approach to characterizing a kV energy spectrum to be used for patient specific x-ray dose computations. Furthermore, these results provide experimental validation of our novel hybrid dose computation algorithm.

61 RADIATION PROTECTION AND DOSIMETRY↗