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At least 1,189 records · Page 66

Optimizing End-to-End Big Data Transfers over Terabits Network Infrastructure

While future terabit networks hold the promise of significantly improving big-data motion among geographically distributed data centers, significant challenges must be overcome even on today's 100 gigabit networks to realize end-to-end performance. Multiple bottlenecks exist along the end-to-end path from source to sink, for instance, the data storage infrastructure at both the source and sink and its interplay with the wide-area network are increasingly the bottleneck to achieving high performance. In this study, we identify the issues that lead to congestion on the path of an end-to-end data transfer in the terabit network environment, and we present a new bulk data movement framework for terabit networks, called LADS. LADS exploits the underlying storage layout at each endpoint to maximize throughput without negatively impacting the performance of shared storage resources for other users. LADS also uses the Common Communication Interface (CCI) in lieu of the sockets interface to benefit from hardware-level zero-copy, and operating system bypass capabilities when available. It can further improve data transfer performance under congestion on the end systems using buffering at the source using flash storage. With our evaluations, we show that LADS can avoid congested storage elements within the shared storage resource, improving input/output bandwidth, and data transfer rates across the high speed networks. We also investigate the performance degradation problems of LADS due to I/O contention on the parallel file system (PFS), when multiple LADS tools share the PFS. We design and evaluate a meta-scheduler to coordinate multiple I/O streams while sharing the PFS, to minimize the I/O contention on the PFS. Finally, with our evaluations, we observe that LADS with meta-scheduling can further improve the performance by up to 14 percent relative to LADS without meta-scheduling.

97 MATHEMATICS AND COMPUTING↗

Parallel elastic elements improve energy efficiency on the STEPPR bipedal walking robot

This study describes how parallel elastic elements can be used to reduce energy consumption in the electric motor driven, fully-actuated, STEPPR bipedal walking robot without compromising or significantly limiting locomotive behaviors. A physically motivated approach is used to illustrate how selectively-engaging springs for hip adduction and ankle flexion predict benefits for three different flat ground walking gaits: human walking, human-like robot walking and crouched robot walking. Based on locomotion data, springs are designed and substantial reductions in power consumption are demonstrated using a bench dynamometer. These lessons are then applied to STEPPR (Sandia Transmission-Efficient Prototype Promoting Research), a fully actuated bipedal robot designed to explore the impact of tailored joint mechanisms on walking efficiency. Featuring high-torque brushless DC motors, efficient low-ratio transmissions, and high fidelity torque control, STEPPR provides the ability to incorporate novel joint-level mechanisms without dramatically altering high level control. Unique parallel elastic designs are incorporated into STEPPR, and walking data shows that hip adduction and ankle flexion springs significantly reduce the required actuator energy at those joints for several gaits. These results suggest that parallel joint springs offer a promising means of supporting quasi-static joint torques due to body mass during walking, relieving motors of the need to support these torques and substantially improving locomotive energy efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

High performance techniques for micro channel plate computations in photo multipliers

Monte Carlo - MC methods, requiring heavy computations of large data volume, can be used to predict the amplitude distribution and variance of outputted electron charge in Micro Channel Plates - MCPs, which are fed with primary emitted electrons in their inputs. The concept of parallel and serial combination of separate stages of such stochastic processes, which can be applied in MCP systems and simulated using MC computations, has recently proposed and shown interesting theorems and results. Separating the electron multiplication procedures, occurring in the channels of MCP systems, into sub-procedures, which are similar in nature and occur either in parallel or in consecutive manners, is equivalent to splitting the relevant stochastic system calculations into smaller ones, which can be performed concurrently and/or sequentially. In this way, calculations similar in nature, can be executed only once, thus, eliminating a great percentage of heavy computations. However, when designing and implementing the calculation inferences of the derived theorems using High Performance Computation - HPC techniques, the overall computation cost can further and significantly be reduced. In this paper, the hardware mappings of the relevant theorem inferences onto parallel computing architectures, resulting in circuits of computing blocks for calculation purposes of MCP system stochastic processes, are investigated. Each of the designed and implemented computing circuits corresponds to a theorem inference or to a combination of inferences. The parallelism of the proposed circuits consists of both the concurrent functioning of all the system blocks and of the simultaneous operation of each block, which is processing pieces of data, for many parts of the whole circuit in which it belongs. All the circuits are designed and tested using Altera Quartus II environment and can be implemented as chips, which can be incorporated in computing devices to assist Monte Carlo computations for the estimation of different MCP electron multiplication system performances.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Duality-Free Decomposition Based Data-Driven Stochastic Security-Constrained Unit Commitment

To incorporate the superiority of both stochastic and robust approaches, a data-driven stochastic optimization is employed to solve the security-constrained unit commitment model. This approach makes the most use of the historical data to generate a set of possible probability distributions for wind power outputs and then it optimizes the unit commitment under the worst-case probability distribution. However, this model suffers from huge computational burden, as a large number of scenarios are considered. To tackle this issue, a duality-free decomposition method is proposed in this paper. This approach does not require doing duality, which can save a large set of dual variables and constraints, and therefore reduces the computational burden. In addition, the inner max-min problem has a special mathematical structure, where the scenarios have the similar constraint. Thus, the max-min problem can be decomposed into independent sub-problems to be solved in parallel, which further improves the computational efficiency. A numerical study on an IEEE 118-bus system with practical data of a wind power system has demonstrated the effectiveness of the proposal.

42 ENGINEERING↗

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

We present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

On the Evolution From Micrometer-Scale Inhomogeneity to Global Overheated Structure During the Intense Joule Heating of a z-Pinch Rod

Ultrafast optical microscopy of metal z-pinch rods pulsed with megaampere current is contributing new data and critical insight into what provides the fundamental seed for the magneto-Rayleigh-Taylor (MRT) instability. A two-frame near infrared/visible intensified-charge-coupled device gated imager with 2-ns temporal resolution and 3-μm spatial resolution captured emissions from the nonuniformly Joule heated surfaces of ultrasmooth aluminum (Al) rods. Nonuniform surface emissions are consistently first observed from discrete, 10-μm scale, subelectronvolt spots. Aluminum 6061 alloy, with micrometer-scale nonmetallic resistive inclusions, forms several times more spots than 99.999% pure Al 5N; 5-10 ns later, azimuthally stretched elliptical spots and distinct strata (40-100 μm wide by 10 μm tall) are observed on Al 6061, but not on Al 5N. In such overheat strata, aligned parallel to the magnetic field, we find that they are highly effective seeds for MRT instability growth. Our data give credence to the hypothesis that early nonuniform Joule heating, such as the electrothermal instability, may provide the dominant seed for MRT.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An efficient parallel sampling technique for Multivariate Poisson-Lognormal model: Analysis with two crash count datasets

Our study investigates the Multivariate Poisson-lognormal (MVPLN) model that jointly models crash frequency and severity accounting for correlations. The ordinary univariate count models analyze crashes of different severity level separately ignoring the correlations among severity levels. The MVPLN model is capable to incorporate the general correlation structure and takes account of the over dispersion in the data that leads to a superior data fitting. But, the traditional estimation approach for MVPLN model is computationally expensive, which often limits the use of MVPLN model in practice. In this work, a parallel sampling scheme is introduced to improve the original Markov Chain Monte Carlo (MCMC) estimation approach of the MVPLN model, which significantly reduces the model estimation time. Two MVPLN models are developed using the pedestrian vehicle crash data collected in New York City from 2002 to 2006, and the highway-injury data from Washington State (5-year data from 1990 to 1994) The Deviance Information Criteria (DIC) is used to evaluate the model fitting. The estimation results show that the MVPLN models provide a superior fit over univariate Poisson-lognormal (PLN), univariate Poisson, and Negative Binomial models. Moreover, the correlations among the latent effects of different severity levels are found significant in both datasets that justifies the importance of jointly modeling crash frequency and severity accounting for correlations.

97 MATHEMATICS AND COMPUTING↗

Low power on-chip data transmission for wafer-scale monolithic active pixel sensors

Here, this paper details the implementation of the digital pulse shaping subsystem within the Backbone Transmission Line Encoding (BTLE) driver, a low-power, long-distance on-chip data transmission solution designed in a 65 nm CMOS process. Digital pulse shaping is critical for minimizing inter-symbol interference (ISI) caused by bandwidth limitations of on-chip interconnects, especially in wafer-scale monolithic active pixel sensors (MAPS). A duobinary encoder coupled with a parallelized polyphase finite impulse response (FIR) filter is used for efficient shaping of the transmitted signal spectrum. This reconfigurable architecture achieves reliable 160 Mb/s data transfer over a 10 cm on-chip link, as validated by simulations demonstrating low power consumption (FoM 37.3 fJ/bit/mm of transmission line length) and effective ISI mitigation.

47 OTHER INSTRUMENTATION↗

Severe Accident Test Station Design Document

The purpose of the ORNL severe accident test station (SATS) is to provide a platform for evaluation of advanced fuels under projected beyond design basis accident (BDBA) conditions. The SATS delivers the capability to map the behavior of advanced fuels concepts under accident scenarios across various temperature and pressure profiles, steam and steam-hydrogen gas mixtures, and thermal shock. The overall facility will include parallel capabilities for examination of fuels and irradiated materials (in-cell) and non-irradiated materials (out-of-cell) at BDBA conditions as well as design basis accident (DBA) or loss of coolant accident (LOCA) conditions. Also, a supporting analytical infrastructure to provide the data-needs for the fuel-modeling components of the Fuel Cycle Research and Development (FCRD) program will be put in place in a parallel manner. This design report contains the information for the first, second and third phases of design and construction of the SATS. The first phase consisted of the design and construction of an out-of-cell BDBA module intended for examination of non-irradiated materials. The second phase of this work was to construct the BDBA in-cell module to test irradiated fuels and materials as well as the module for DBA (i.e. LOCA) testing out-of-cell, The third phase was to build the in-cell DBA module. The details of the design constraints and requirements for the in-cell facility have been closely captured during the deployment of the out-of-cell SATS modules to ensure effective future implementation of the in-cell modules.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Fast tree-based algorithms for DBSCAN for low-dimensional data on GPUs

DBSCAN is a well-known density-based clustering algorithm to discover arbitrary shape clusters. While conceptually simple in serial, the algorithm is challenging to efficiently parallelize on manycore GPU architectures. Common pitfalls, such as asynchronous range query calls, result in high thread execution divergence in many implementations. In this paper, we propose a new framework for GPU-accelerated DBSCAN, and describe two tree-based algorithms within that framework. Both algorithms fuse the search for neighbors with updating cluster information, but differ in their treatment of dense regions of the data. We show that the time taken to compute clusters is at most twice that of determination of the neighbors. We compare the proposed algorithms with existing CPU and GPU implementations, and demonstrate their competitiveness and performance using a fast traversal structure (bounding volume hierarchy) for low dimensional data. We also show that the memory usage can be reduced by processing object neighbors dynamically without storing them.

Prokopenko, Andrey↗

A Survey on Error-Bounded Lossy Compression for Scientific Datasets

Error-bounded lossy compression has been effective in significantly reducing the data storage/transfer burden while preserving the reconstructed data fidelity very well. Many error-bounded lossy compressors have been developed for a wide range of parallel and distributed use cases for years. They are designed with distinct compression models and principles, such that each of them features particular pros and cons. In this article, we provide a comprehensive survey of emerging error-bounded lossy compression techniques. The key contribution is fourfold. (1) We summarize a novel taxonomy of lossy compression into six classic models. (2) We provide a comprehensive survey of 10 commonly used compression components/modules. (3) We summarized pros and cons of 47 state-of-the-art lossy compressors and present how state-of-the-art compressors are designed based on different compression techniques. (4) We discuss how customized compressors are designed for specific scientific applications and use-cases. We believe this survey is useful to multiple communities including scientific applications, high-performance computing, lossy compression, and big data.

Error-Bounded Lossy Compression↗

Code modernization strategies for short-range non-bonded molecular dynamics simulations

Modern HPC systems are increasingly relying on greater core counts and wider vector registers. Thus, applications need to be adapted to fully utilize these hardware capabilities. One class of applications that can benefit from this increase in parallelism are molecular dynamics simulations. In this paper, we describe our efforts at modernizing the ESPResSo++ simulation package for molecular dynamics by restructuring its particle data layout for efficient memory accesses and applying vectorization techniques to benefit the calculation of short-range non-bonded forces, which results in an overall three times speedup and serves as a baseline for further optimizations. We also implement fine-grained parallelism for multi-core CPUs through HPX, a C++ runtime system which uses lightweight threads and an asynchronous many-task approach to maximize concurrency. Our goal is to evaluate the performance of an HPX-based approach compared to the bulk-synchronous MPI-based implementation. This requires the introduction of an additional layer to the domain decomposition scheme that defines the task granularity. On spatially inhomogeneous systems, which impose a corresponding load-imbalance in traditional MPI-based approaches, we demonstrate that by choosing an optimal task size, the efficient work-stealing mechanisms of HPX can overcome the overhead of communication resulting in an overall 1.4 times speedup compared to the baseline MPI version.

97 MATHEMATICS AND COMPUTING↗

Monitoring spatiotemporal evolution of fractures during hydraulic stimulations at the first EGS collab testbed using anisotropic elastic-waveform inversion

The EGS Collab project acquired continuous active-source seismic monitoring (CASSM) data before, during, and after hydraulic stimulations at the first testbed at the depth of 4850 ft (1478 m) at the Sanford Underground Research Facility in Lead, South Dakota, for monitoring fracture creation and evolution. CASSM acquisition was conducted using 24 hydrophones, 18 accelerometers, and 17 piezoelectric sources within four fracture-parallel wells and two orthogonal wells. 3D anisotropic traveltime tomography and anisotropic elastic-waveform inversion of the campaign cross-borehole seismic data show that the rock within the stimulation region is a heterogeneous horizontal transverse isotropic medium. Here we use these inversion results as the initial models and apply 3D anisotropic first-arrival traveltime tomography and 3D anisotropic elastic-waveform inversion to the CASSM data acquired after each stimulation in May, 2018 and December, 2018. We observe the spatiotemporal evolution of seismic velocities and anisotropic parameters caused by hydraulic fracture stimulations, showing the regions of rock alternation caused by hydraulic fracture stimulation.

15 GEOTHERMAL ENERGY↗

Measurement of temperature of a dusty plasma from its configuration

A new concept called “configurational temperature” is introduced in the context of dusty plasma, where the temperature of the dust particles submerged in the plasma can be measured directly from the positional information of the individual dust particles and the interaction potential between the dust grains. This method does not require the velocity information of individual particles, which is a key parameter to measure the dust temperature in the conventional method. The technique is initially tested using two-dimensional (2D) OpenMP parallel molecular dynamics and Monte Carlo simulation and then compared with the temperature evaluated from experimental data. The experiment have been carried out in the Dusty Plasma Experimental (DPEx) device, where a 2D stationary plasma crystal of melamine formaldehyde particles is formed in the cathode sheath of a DC glow discharge argon plasma. The kinetic temperature of the dust is calculated using the standard particle image velocimetry technique at different pressures. An extended simulation result for the three-dimensional case is also presented, which can be employed for the temperature measurement of a three-dimensional dust crystal in laboratory devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Airborne Single Particle Mass Spectrometers (SPLAT II & miniSPLAT) and New Software for Data Visualization and Analysis in a Geo-Spatial Context

Understanding the effect of aerosols on climate requires knowledge of the size and chemical composition of individual aerosol particles - two fundamental properties that determine an aerosol’s optical properties and ability to serve as cloud condensation or ice nuclei. Here we present miniSPLAT, our new aircraft compatible single particle mass spectrometer, that measures in-situ and in real-time size and chemical composition of individual aerosol particles with extremely high sensitivity, temporal resolution, and sizing precision on the order of a monolayer. miniSPLAT operates in dual data acquisition mode to measure, in addition to single particle size and composition, particle number concentrations, size distributions, density, and asphericity with high temporal resolution. When compared to our previous instrument, SPLAT II, miniSPLAT has been significantly reduced in size, weight, and power consumption without loss in performance. We also present ND-Scope, our newly developed interactive visual analytics software package. ND-Scope is designed to explore and visualize the vast amount of complex, multidimensional data acquired by our single particle mass spectrometers, along with other aerosol and cloud characterization instruments on-board aircraft. We demonstrate that ND-Scope makes it possible to visualize the relationships between different observables and to view the data in a geo-spatial context, using the interactive and fully coupled Google Earth and Parallel Coordinates displays. Here we illustrate the utility of ND-Scope to visualize the spatial distribution of atmospheric particles of different compositions, and explore the relationship between individual particle composition and their activity as cloud condensation nuclei.

54 ENVIRONMENTAL SCIENCES↗

Quasielastic neutron scattering in biology: Theory and applications

Neutrons scatter quasielastically from stochastic, diffusive processes, such as overdamped vibrations, localized diffusion and transitions between energy minima. In biological systems, such as proteins and membranes, these relaxation processes are of considerable physical interest. We review here recent methodological advances and applications of quasielastic neutron scattering (QENS) in biology, concentrating on the role of molecular dynamics simulation in generating data with which neutron profiles can be unambiguously interpreted. We examine the use of massively-parallel computers in calculating scattering functions, and the application of Markov state modeling. The decomposition of MD-derived neutron dynamic susceptibilities is described, and the use of this in combination with NMR spectroscopy. We discuss dynamics at very long times, including approximations to the infinite time mean-square displacement and nonequilibrium aspects of single-protein dynamics. Lastly, we examine how neutron scattering and MD can be combined to provide information on lipid nanodomains.

59 BASIC BIOLOGICAL SCIENCES↗

Homomolecular Triplet–Triplet Annihilation in Metalloporphyrin Photosensitizers

Metalloporphyrins are ubiquitous in their applications as triplet photosensitizers, particularly for promoting sensitized photochemical upconversion processes. In this study, bimolecular excited state triplet–triplet quenching kinetics, termed homomolecular triplet–triplet annihilation (HTTA), exhibited by the traditional triplet photosensitizers–zinc(II) tetraphenylporphyrin (ZnTPP), palladium(II) octaethylporphyrin (PdOEP), platinum(II) octaethylporphyrin (PtOEP), and platinum(II) tetraphenyltetrabenzoporphyrin (PtTPBP)–were revealed using conventional transient absorption spectroscopy. Nickel(II) tetraphenylporphyrin was used as a control sample as it is known to be rapidly quenched intramolecularly through ligand-field state deactivation and, therefore, cannot result in triplet–triplet annihilation (TTA). The single wavelength transients associated with the metalloporphyrin triplet excited state decay–measured as a function of incident laser pulse energy in toluene–were well modeled using parallel first- and second-order kinetics, consistent with HTTA being operable. The combined transient kinetic data enabled the determination of the first-order rate constants (k T ) for excited triplet decay in ZnTPP (4.0 × 10 3 s –1 ), PdOEP (3.6 × 10 3 s –1 ), PtOEP (1.2 × 10 4 s –1 ), and PtTPBP (2.1 × 10 4 s –1 ) as well as the second-order rate constant (k TT ) for HTTA in ZnTPP (5.5 × 10 9 M –1 s –1 ), PdOEP (1.1 × 10 10 M –1 s –1 ), PtOEP (7.1 × 10 9 M –1 s –1 ), and PtTPBP (1.6 × 10 10 M –1 s –1 ). In most instances, triplet excited state extinction coefficients are either reported for the first time or have been revised using ultrafast transient absorption spectroscopy and singlet depletion: ZnTPP (78,000 M –1 cm –1 ) at 470 nm, PdOEP (67,000 M –1 cm –1 ) at 430 nm, PtOEP (51,000 M –1 cm –1 ) at 418 nm, and PtTPBP (100,000 M –1 cm –1 ) at 460 nm. Furthermore, the combined experimental results establish competitive time scales for homo- and heteromolecular TTA rate constants, implying the significance of considering HTTA processes in future research endeavors harnessing TTA photochemistry using common metalloporphyrin photosensitizers.

14 SOLAR ENERGY↗

Anisotropic Ion Diffusion and Electrochemically Driven Transport in Nanostructured Block Copolymer Electrolytes

Nanostructured block copolymer electrolytes have the potential to enable solid-state batteries with lithium metal anodes. We present complete continuum characterization of ion transport in a lamellar polystyrene-b-poly(ethylene oxide) copolymer/lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) electrolyte as a function of salt concentration. Electrochemical measurements are used to determine the Stefan–Maxwell salt diffusion coefficients $^D_{+, 0}$, $^D_{-, 0}$, and $^D_{+, -}$. Individual self-diffusion coefficients of the lithium- and TFSI-containing species were measured by pulsed-field gradient NMR (PFG-NMR). The NMR data indicate that salt diffusion is locally anisotropic, and this enables determination of a diffusion coefficient parallel to the lamellae, D ∥ , and a diffusion coefficient through defects in the lamellae, D ⊥ . We quantify anisotropic diffusion by defining an NMR morphology factor and demonstrate that it is correlated to defect density seen by transmission electron microscopy. We find agreement between the electrochemically determined Stefan–Maxwell diffusion coefficients and the diffusion coefficient D⊥ determined by PFG-NMR. Our work indicates that the performance of nanostructured block copolymer electrolytes in batteries is strongly influenced by ion transport through defects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗