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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

ConnectIt: a framework for static and incremental parallel graph connectivity algorithms

Connected components is a fundamental kernel in graph applications. The fastest existing multicore algorithms for solving graph connectivity are based on some form of edge sampling and/or linking and compressing trees. However, many combinations of these design choices have been left unexplored. In this paper, we design the ConnectIt framework, which provides different sampling strategies as well as various tree linking and compression schemes. ConnectIt enables us to obtain several hundred new variants of connectivity algorithms, most of which extend to computing spanning forest. In addition to static graphs, we also extend ConnectIt to support mixes of insertions and connectivity queries in the concurrent setting. We present an experimental evaluation of ConnectIt on a 72-core machine, which we believe is the most comprehensive evaluation of parallel connectivity algorithms to date. Compared to a collection of state-of-the-art static multicore algorithms, we obtain an average speedup of 12.4x (2.36x average speedup over the fastest existing implementation for each graph). Using ConnectIt, we are able to compute connectivity on the largest publicly-available graph (with over 3.5 billion vertices and 128 billion edges) in under 10 seconds using a 72-core machine, providing a 3.1x speedup over the fastest existing connectivity result for this graph, in any computational setting. For our incremental algorithms, we show that our algorithms can ingest graph updates at up to several billion edges per second. To guide the user in selecting the best variants in ConnectIt for different situations, we provide a detailed analysis of the different strategies. Finally, we show how the techniques in ConnectIt can be used to speed up two important graph applications: approximate minimum spanning forest and SCAN clustering.

Computer Science↗
DOE OSTI2014

Reliable and Efficient Distributed Checkpointing System for Grid Environments

In Fine-Grained Cycle Sharing (FGCS) systems, machine owners voluntarily share their unused CPU cycles with guest jobs, as long as their performance degradation is tolerable. However, unpredictable evictions of guest jobs lead to fluctuating completion times. Checkpoint-recovery is an attractive mechanism for recovering from such “failures”. Today’s FGCS systems often use expensive, high-performance dedicated checkpoint servers. However, in geographically distributed clusters, this may incur high checkpoint transfer latencies. Here we present a distributed checkpointing system called FALCON that uses available disk resources of the FGCS machines as shared checkpoint repositories. However, an unavailable storage host may lead to loss of checkpoint data. Therefore, we model the failures of a storage host and develop a prediction algorithm for choosing reliable checkpoint repositories. We experiment with FALCON in the university-wide Condor testbed at Purdue and show improved and consistent performance for guest jobs in the presence of irregular resource availability.

checkpoint↗
DOE OSTI2014

High and low frequency instabilities driven by counter-streaming electron beams in space plasmas

A four-component plasma composed of a drifting (parallel to ambient magnetic field) population of warm electrons, drifting (anti-parallel to ambient magnetic field) cool electrons, stationary hot electrons, and thermal ions is studied in an attempt to further our understanding of the excitation mechanisms of broadband electrostatic noise (BEN) in the Earth's magnetospheric regions such as the magnetosheath, plasmasphere, and plasma sheet boundary layer (PSBL). Using kinetic theory, beam-driven electrostatic instabilities such as the ion-acoustic, electron-acoustic instabilities are found to be supported in our multi-component model. The dependence of the instability growth rates and real frequencies on various plasma parameters such as beam speed, number density, temperature, and temperature anisotropy of the counter-streaming (relative to ambient magnetic field) cool electron beam are investigated. It is found that the number density of the anti-field aligned cool electron beam and drift speed play a central role in determining which instability is excited. Using plasma parameters which are closely correlated with the measurements made by the Cluster satellites in the PSBL region, we find that the electron-acoustic and ion-acoustic instabilities could account for the generation of BEN in this region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Electronic Structure and Properties of Berkelium Iodates

The reaction of 249 Bk(OH) 4 with iodate under hydrothermal conditions results in the formation of Bk(IO 3 ) 3 as the major product with trace amounts of Bk(IO 3 ) 4 also crystallizing from the reaction mixture. The structure of Bk(IO 3 ) 3 consists of nine-coordinate Bk III cations that are bridged by iodate anions to yield layers that are isomorphous with those found for Am III , Cf III , and with lanthanides that possess similar ionic radii. Bk(IO 3 ) 4 was expected to adopt the same structure as M(IO 3 ) 4 (M = Ce, Np, Pu), but instead parallels the structural chemistry of the smaller Zr IV cation. Bk III –O and Bk IV –O bond lengths are shorter than anticipated and provide further support for a postcurium break in the actinide series. Photoluminescence and absorption spectra collected from single crystals of Bk(IO 3 ) 4 show evidence for doping with Bk III in these crystals. In addition to luminescence from Bk III in the Bk(IO 3 ) 4 crystals, a broad-band absorption feature is initially present that is similar to features observed in systems with intervalence charge transfer. However, the high-specific activity of 249 Bk ( t 1/2 = 320 d) causes oxidation of Bk III and only Bk IV is present after a few days with concomitant loss of both the BkIII luminescence and the broadband feature. The electronic structure of Bk(IO 3 ) 3 and Bk(IO 3 ) 4 were examined using a range of computational methods that include density functional theory both on clusters and on periodic structures, relativistic ab initio wave function calculations that incorporate spin–orbit coupling (CASSCF), and by a full-model Hamiltonian with spin–orbit coupling and Slater–Condon parameters (CONDON). Some of these methods provide evidence for an asymmetric ground state present in Bk IV that does not strictly adhere to Russel–Saunders coupling and Hund’s Rule even though it possesses a half-filled 5 f 7 shell. Multiple factors contribute to the asymmetry that include 5 f electrons being present in microstates that are not solely spin up, spin–orbit coupling induced mixing of low-lying excited states with the ground state, and covalency in the Bk IV –O bonds that distributes the 5f electrons onto the ligands. These factors are absent or diminished in other f 7 ions such as Gd III or Cm III .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

3-D Simulations of earthquakes rupture jumps: 1. Homogeneous pre-stress conditions

SUMMARY Observational and modelling studies indicate that earthquake ruptures can jump between fault sections as large as ∼3 and ∼5 km for compressional and extensional offsets, respectively. Here, we compare characteristics of the rupture jump process on parallel but offset fault sections from traditional 3-D dynamic rupture simulations governed by slip weakening friction using the finite element code, FaultMod, to those from quasi-dynamic simulations governed by rate- and state-dependent friction (rate-state friction) using the code RSQSim. These simulations use spatially uniform initial stresses. For a variety of measures the rupture renucleation position on the offset fault, the rate-state friction and slip weakening friction models produce very similar results. The principal difference is the additional occurrence of delayed rupture jumps that arise from the time- and stress-dependent nucleation that is characteristic of rate-state friction. For immediate rupture jumps, models with slip weakening friction span greater offsets than those with rate-state friction. However the jump distances are nearly identical when delayed rupture jumps are included in the comparisons. We propose that delayed rupture jumps are the likely mechanism for adjacent large-earthquake pairs and clusters. Based on the similarity of renucleation positions with both dynamic and quasi-dynamic models, we conclude that the renucleation positions for rupture initiation on the receiver fault (separated by less than ∼3 km from the source fault) are primarily controlled by static stress changes induced by slip on the initiating fault. However, in light of the slightly greater maximum jump distances (>3 km) seen with the dynamic slip weakening friction model, dynamic stress changes from seismic waves play an increasingly important role as offset distances increase.

, RSQSim↗
DOE OSTI2014

Compositional effects on Si–OH bond length in hydrous silicates with implications for trends in the SiOH acidity

Theoretical calculations of the structure and Brønsted acidity of SiOH groups in silica clusters have never addressed the question if these vary with the degree of SiOH deprotonation. In this connection, a statistical analysis is presented of Si–OH bond lengths in crystalline hydrogen silicates with well-determined structures with a special emphasis placed on effects of the silicate composition. It is found that among hydrogen silicates of large cations with low charges the Si–OH bonds are always longer than terminal Si–O bonds in the same anion and correlate in length with the anionic charge per tetrahedron. The findings are explained by steric limitations on charge balancing at oxygen atoms by hydrogen bonds and/or cations. It is suggested that similar limitations and imbalances may underlie the well-known trends in the Brønsted acidity of silicic acids and silicas in aqueous media: decreased acidity with increased SiOH deprotonation and increased acidity with increased tetrahedra connectivity. - Graphical abstract: Si–OH bonds in crystalline silicates lengthen with the anionic charge per tetrahedron, which is in parallel with the well-known trend of decreased acidity of silicic acids and silicas in solution with increased degree of deprotonation. - Highlights: • Si–OH bonds in alkali hydrogen silicates are always longer than terminal Si–O bonds. • Si–OH bonds in silicates lengthen with the anionic charge per tetrahedron. • The Si–OH bond elongation results from inherent underbonding of terminal O atoms. • The longer the Si–OH bond, the less acidic the OH group is.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Fine-Tuning the Activity of Metal–Organic Framework Supported Cobalt Catalysts for the Oxidative Dehydrogenation of Propane

Few-atom cobalt-oxide clusters, when dispersed on a Zr-based metal–organic framework (MOF) NU-1000, have previously been shown to be active for the oxidative dehydrogenation (ODH) of propane at low temperatures (< 230 °C), affording a selective and stable propene production catalyst. In our current work, a series of promoter ions with varying Lewis acidity, including Ni(II), Zn(II), Al(III), Ti(IV) and Mo(VI), are anchored as metal-oxide,hydroxide clusters to NU-1000 via SIM (solvothermal deposition within MOFs–specifically the nodes) followed by incorporation of Co(II) ions via vapor-phase AIM (atomic layer deposition (ALD) in MOFs). This process yields a series of NU-1000-supported bimetallic-oxo,hydroxo,aqua clusters. Using difference envelope density (DED) analyses, the spatial locations of the promoter ions and catalytic cobalt ions are determined. For all samples the SIM-anchored promoter ions are sited between pairs of Zr 6 nodes along the MOF c-axis (channel-aligned axis) whereas the location of the AIM-anchored cobalt ions varies depending on the identity of promoter metal ion. With Ni(II)-, Al(III)-, or Ti(IV)-containing clusters as promoters, the oxy-cobalt species are sited atop the promoter sites; with Mo(VI) they grow exclusively on the MOF nodes sites (hexa-Zr(IV)- oxo,hydroxo,aqua units); with Zn(II) they grow on both the node and promoter. The NU-1000- supported bimetallic-oxide clusters are active for propane ODH after thermal activation under O 2 to open a cobalt coordination site and to oxidize Co(II) to Co(III), as evidenced by operando Xray absorption spectroscopy at the Co K-edge. The cobalt component is exclusively responsible for the observed catalysis. In accord with the decreasing Lewis acidity of the promoter ion, catalytic activity increases in the order: Mo(VI)<Ti(IV)<Al(III)<Zn(II)<Ni(II). The finding is attributed to increasing ease of formation Co(III)-O• species and stabilization of a cobalt(III)- oxyl/propane transition state as the Lewis acidity of the promoter ions decreases. (The promoterfree catalyst is sited on the oxy-Zr(IV) node of the MOF and is inferior catalytically to the strongly promoted versions of the catalyst.) The relative Lewis acidities of the promoters are inferred from the initial pKa values of aqua complexes of the corresponding single metal ions. Departures from the (ODH-rate)/(promoter-pKa) correlation are paralleled by differences in cobalt catalyst siting or structure. The combined results point to an increasing ability to fine-tune, with close to atomic specificity, the structure-dependent activity of MOF-supported heterogeneous catalysts for gas phase chemical reactions. When coupled with mechanistic studies–computational or experimental–this ability may translate into informed prediction of improved catalysts for propane ODH and other chemical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Newton trust-region methods with primary variable switching for simulating high temperature multiphase porous media flow

Coupling multiphase flow with energy transport due to high temperature heat sources introduces significant new challenges since boiling and condensation processes can lead to dry-out conditions with subsequent re-wetting. The transition between two-phase and single-phase behavior can require changes to the primary dependent variables adding discontinuities as well as extending constitutive nonlinear relations to extreme physical conditions. Practical simulations of large-scale engineered domains lead to Jacobian systems with a very large number of unknowns that must be solved efficiently using iterative methods in parallel on high-performance computers. Performance assessment of potential nuclear repositories, carbon sequestration sites and geothermal reservoirs can require numerous Monte-Carlo simulations to explore uncertainty in material properties, boundary conditions, and failure scenarios. Due to the numerical challenges, standard NR iteration may not converge over the range of required simulations and require more sophisticated optimization method like trust-region. In this study, we use the open-source simulator PFLOTRAN for the important practical problem of the safety assessment of future nuclear waste repositories in the U.S. DOE geologic disposal safety assessment Framework. The simulator applies the PETSc parallel framework and a backward Euler, finite volume discretization. We demonstrate failure of the conventional NR method and the success of trust-region modifications to Newton’s method for a series of test problems of increasing complexity. Trust-region methods essentially modify the Newton step size and direction under some circumstances where the standard NR iteration can cause the solution to diverge or oscillate. Furthermore, we show how the Newton Trust-Region method can be adapted for Primary Variable Switching (PVS) when the multiphase state changes due to boiling or condensation. The simulations with high-temperature heat sources which led to extreme nonlinear processes with many state changes in the domain did not converge with NR, but they do complete successfully with the trust-region methods modified for PVS. This implementation effectively decreased weeks of simulation time needing manual adjustments to complete a simulation down to a day. Finally, we show the strong scalability of the methods on a single node and multiple nodes in an HPC cluster.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

PIC simulations of the effect of velocity space instabilities on electron viscosity and thermal conduction

In low-collisionality plasmas, velocity-space instabilities are a key mechanism providing an effective collisionality for the plasma. We use particle-in-cell (PIC) simulations to study the interplay between electron- and ion-scale velocity-space instabilities and their effect on electron pressure anisotropy, viscous heating, and thermal conduction. The adiabatic invariance of the magnetic moment in low-collisionality plasmas leads to pressure anisotropy, Δp{sub j}≡p{sub ⊥,j}−p{sub ∥,j}>0, if the magnetic field B is amplified (p{sub ⊥,j} and p{sub ∥,j} denote the pressure of species j (electron, ion) perpendicular and parallel to B). If the resulting anisotropy is large enough, it can in turn trigger small-scale plasma instabilities. Our PIC simulations explore the nonlinear regime of the mirror, IC, and electron whistler instabilities, through continuous amplification of the magnetic field |B| by an imposed shear in the plasma. In the regime 1≲β{sub j}≲20 (β{sub j}≡8πp{sub j}/|B|{sup 2}), the saturated electron pressure anisotropy, Δp{sub e}/p{sub ∥,e}, is determined mainly by the (electron-lengthscale) whistler marginal stability condition, with a modest factor of ∼1.5–2 decrease due to the trapping of electrons into ion-lengthscale mirrors. We explicitly calculate the mean free path of the electrons and ions along the mean magnetic field and provide a simple physical prescription for the mean free path and thermal conductivity in low-collisionality β {sub j} ≳ 1 plasmas. Our results imply that velocity-space instabilities likely decrease the thermal conductivity of plasma in the outer parts of massive, hot, galaxy clusters. We also discuss the implications of our results for electron heating and thermal conduction in low-collisionality accretion flows onto black holes, including Sgr A* in the Galactic Center.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Comparison of Distributive Consensus Algorithms for AnomalyDetection on the Power-Grid

As an increasing number of devices in the power-grid rely on high-precision clocks to measure electrical properties and time stamp data, GPS receivers have become a vulnerability on the power-grid. GPS spoofing attacks, in which a fake signal is transmitted, can cause sensor measurement errors that can misinform protective equipment and grid operators for both the transmission and distribution grid. The technology being developed to secure precision clocks in the transmission grid are not appropriate for the distribution grid. Thus, there is a need to developed anomaly detection algorithms that are suitable for the hardware available on the distribution grid. Traditionally, a distributed detection framework is comprised of spatially distributed nodes which acquire observations about a quantity of interest and sends the data to the fusion center, where a global decision is made. Instead the distribution grid has low-power devices, such as smart inverters and microPMUs, that could be used to perform highly parallelized calculations. Having on node calculations is beneficial since it is more network and computation efficient, as the more calculations can be performed where the data is being captured instead of communicating across a slow network to a centralized fusion center. Instead, we could employ an alternate peer-to-peer type of information exchange on the distribution grid that can still reach a global decision. A decentralized approach to anomaly detection makes efficient use of the computational and network bandwidth that exists, and it also lacks the single point of failure of a centralized approach. Thus, a decentralized local information exchange and/or inference is preferred. Lastly, the unreliability of the distribution grid network connections and potential noise or error in the measurements must be considered. In order to produce an effective detection tool, a Byzantine-fault tolerant and asynchronous algorithm must be developed. Thus, the first phase of our project is to develop a distributed, decentralized, asynchronous, Byzantine-fault tolerant, collaborative autonomy-based anomaly detection algorithm to collectively analyze clusters of data for signs of a malicious attack.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

The Dark Energy Spectrometer (DESpec): A Multi-Fiber Spectroscopic Upgrade of the Dark Energy Camera and Survey for the Blanco Telescope

We describe an initiative to build and use the Dark Energy Spectrometer (DESpec), a wide-field spectroscopic survey instrument for the Blanco 4-meter telescope at Cerro Tololo Inter-American Observatory (CTIO) in Chile. A new system with about 4000 robotically positioned optical fibers will be interchangeable with the CCD imager of the existing Dark Energy Camera (DECam), accessing a field of view of 3.8 square degrees in a single exposure. The proposed instrument will be operated by CTIO and available for use by the astronomy community. Our collaboration proposes to use DESpec to conduct a wide, deep spectroscopic survey to study Dark Energy, sharing the survey products with the community, while providing community access to fibers in parallel with survey observations. In a survey of ~350 nights, the DESpec collaboration proposes to obtain spectroscopic redshifts for ~8 million galaxies over 5000 sq. deg. selected from precision imaging from the Dark Energy Survey (DES). This Dark Energy Spectroscopic Survey will advance our knowledge of cosmic expansion and structure growth significantly beyond that obtainable with imaging-only surveys. Since it adds a spectroscopic third dimension to the same sky as DES, the world’s largest and deepest photometric survey, DESpec will enable a powerful array of new, increasingly precise techniques to discriminate among alternative explanations of cosmic acceleration, such as Dark Energy and Modified Gravity. In the 2020 decade, a wider-area spectroscopic survey will enhance the science reach of the next-generation imaging project, LSST, by providing spectroscopy for tens of millions of galaxies and QSO’s over its 15,000-20,000 square degree survey area. DESpec will create a comprehensive, three dimensional, critically-sampled map of large scale cosmic structure – a database encompassing the “cosmic web” of galaxies and clusters over the entire, deeply-imaged southern sky – over most of cosmic history. DESpec will take advantage of the substantial hardware infrastructure recently built for DECam to achieve excellent science at low cost and low technical and schedule risk. It will be mounted in the DECam prime focus cage with its hexapod positioning system (recently installed on the Blanco Telescope) and will share the four largest DECam optical corrector elements. It will be routinely interchangeable with the DECam CCD imager and preserve f/8 secondary capability, to allow flexible use of the telescope. The robotically positioned optical fibers will feed 10 relatively simple, high-throughput spectrometers outfitted with existing, spare, red-sensitive, science-grade DECam CCDs. An Atmospheric Dispersion Compensator similar to existing designs can be accommodated in the existing DECam filter slot. Examples that meet requirements for all major subsystems are in existing or highly developed instruments, showing that cost, technical, and schedule risks are manageable.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Knowledge Discovery for Smart Grid Operation, Control, and Situation Awareness -- A Big Data Visualization Platform

In this paper, a big data visualization platform is designed to discover the hidden useful knowledge for smart grid (SG) operation, control and situation awareness. The spawn of smart sensors at both grid side and customer side can provide large volume of heterogeneous data that collect information in all time spectrums. Extracting useful knowledge from this big-data poll is still challenging. In this paper, the Apache Spark, an open source cluster computing framework, is used to process the big-data to effectively discover the hidden knowledge. A high-speed communication architecture utilizing the Open System Interconnection (OSI) model is designed to transmit the data to a visualization platform. This visualization platform uses Google Earth, a global geographic information system (GIS) to link the geological information with the SG knowledge and visualize the information in user defined fashion. The University of Denver's campus grid is used as a SG test bench and several demonstrations are presented for the proposed platform.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Hard Disk/Solid State Drive Synergy in Support of Data-Intensive Computing [Slides]

Data-intensive applications are becoming increasingly common in high-performance computing. Examples include combustion simulation, human genome analysis, and satellite image processing. Efficient access of data sets is critical to the performance of these applications. Because of the size of the data today's economically feasible approach is to store the data files on an array of hard disks or data servers equipped with hard disks and managed by a parallel file system such as PVFS or Lustre wherein the data is striped over a (large) number of disks for high aggregate I/O throughout. With file striping, a request for a segment of logically contiguous file space is decomposed into multiple sub-requests, each to a different server. While the data unit for this striping is usually reasonably large to benefit disk efficiency, the first and/or last sub-requests can be much smaller than the striping unit if the request does not align with the striping pattern, severely compromising hard disk efficiency and thus application performance. We propose to exploit solid state drives (SSD), whose efficiency is much less sensitive to small random accesses, to enable the alignment of requests to disk with the data striping pattern. In this scheme hard disks mainly serve large, aligned, sequential requests, with SSDs serving small or unaligned requests, thus respecting the relative cost, performance, and durability characteristics of the two media, and thereby achieving synergy in performance/cost. We will describe the design of the proposed scheme, its implementation on CCS-7's Darwin cluster, and performance results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Description of Sensor Assignment Optimization Method as Deployed on a Multi-Node Cluster

Data analytic methods are being developed to address the problem of how to assign a sensor set in a nuclear facility such that a requisite level of process monitoring capability is realized and that the sensor set is sufficiently rich to determine the status of the individual sensors with respect to need for calibration. There is an awareness in the nuclear industry that data analytics combined with rich sensor sets represent a means to improve operations and reduce costs. In the industry the calibration problem has been previously approached as an empirical data-driven problem with several methods having been developed. However, the experience of the utilities over the past ten years with these methods indicates that the absence of physics-based information renders the data-driven approach less reliable. Complicating factors such as the inherent variability of operation (both equipment alignment and operating condition) can confound a pure data-driven approach while there are no rigorous guidelines for determining what constitutes an adequate sensor set. The solution under development to overcome these shortcomings supplements the data analytic method with process information in a so-called process-constrained data-analytic approach. Simple balance equations are written for generic components (e.g., mechanical pump, valve, and heat exchanger). These do not require a priori knowledge of process parameters, such as heat transfer coefficients or friction factors. All that is needed on the part of the utility user is to identify the components and how they are connected. This report describes the development of a parallel computing capability for determining the optimal sensor set. The optimal sensor set problem suffers from the curse of dimensionality. Computation time increases exponentially as the size of the system grows. To overcome this difficulty a pre-conditioner algorithm is developed to find an approximate solution close the actual solution. This serves as a seed for the full-blown algorithm and acts to constrain the space that must searched. The optimization algorithms are described and the implementation on a parallel computing platform is described. The application of the method to a use case we are solving in collaboration with our utility partner served to illustrate how the default sensor set in a nuclear plant may not provide sufficient coverage to infer sensor calibration status.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Cost-effective description of strong correlation: Efficient implementations of the perfect quadruples and perfect hextuples models

Novel implementations based on dense tensor storage are presented here for the singlet-reference perfect quadruples (PQ) [J. A. Parkhill et al., J. Chem. Phys. 130, 084101 (2009)] and perfect hextuples (PH) [J. A. Parkhill and M. Head-Gordon, J. Chem. Phys. 133, 024103 (2010)] models. The methods are obtained as block decompositions of conventional coupled-cluster theory that are exact for four electrons in four orbitals (PQ) and six electrons in six orbitals (PH), but that can also be applied to much larger systems. PQ and PH have storage requirements that scale as the square, and as the cube of the number of active electrons, respectively, and exhibit quartic scaling of the computational effort for large systems. Applications of the new implementations are presented for full-valence calculations on linear polyenes (C n H n+2 ), which highlight the excellent computational scaling of the present implementations that can routinely handle active spaces of hundreds of electrons. The accuracy of the models is studied in the π space of the polyenes, in hydrogen chains (H 50 ), and in the π space of polyacene molecules. In all cases, the results compare favorably to density matrix renormalization group values. With the novel implementation of PQ, active spaces of 140 electrons in 140 orbitals can be solved in a matter of minutes on a single core workstation, and the relatively low polynomial scaling means that very large systems are also accessible using parallel computing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Linear chains of Ge/Si quantum dots grown on a prepatterned surface formed by ion irradiation

The growth of Ge nanoclusters on a prepatterned Si (100) surface formed by imprint lithography in combination with subsequent irradiation with Ge{sup +} ions is studied. The prepatterned surface presents a system of parallel 10-nm-wide grooves repeating with a period of 180 nm. Irradiation of the substrate was conducted at two temperatures, room temperature (cold irradiation) and 400°C (hot irradiation). It is shown that, during epitaxy (550–700°C), the residual radiation defects located in the bulk under the grooves suppress the nucleation of Ge nanoclusters in the grooves. In the case of prepatterned substrates, from which imperfect regions are completely removed, nanoclusters grow in the grooves.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Large-scale Nanostructure Simulations from X-ray Scattering Data On Graphics Processor Clusters

X-ray scattering is a valuable tool for measuring the structural properties of materialsused in the design and fabrication of energy-relevant nanodevices (e.g., photovoltaic, energy storage, battery, fuel, and carbon capture andsequestration devices) that are key to the reduction of carbon emissions. Although today's ultra-fast X-ray scattering detectors can provide tremendousinformation on the structural properties of materials, a primary challenge remains in the analyses of the resulting data. We are developing novelhigh-performance computing algorithms, codes, and software tools for the analyses of X-ray scattering data. In this paper we describe two such HPCalgorithm advances. Firstly, we have implemented a flexible and highly efficient Grazing Incidence Small Angle Scattering (GISAXS) simulation code based on theDistorted Wave Born Approximation (DWBA) theory with C++/CUDA/MPI on a cluster of GPUs. Our code can compute the scattered light intensity from any givensample in all directions of space; thus allowing full construction of the GISAXS pattern. Preliminary tests on a single GPU show speedups over 125x compared tothe sequential code, and almost linear speedup when executing across a GPU cluster with 42 nodes, resulting in an additional 40x speedup compared to usingone GPU node. Secondly, for the structural fitting problems in inverse modeling, we have implemented a Reverse Monte Carlo simulation algorithm with C++/CUDAusing one GPU. Since there are large numbers of parameters for fitting in the in X-ray scattering simulation model, the earlier single CPU code required weeks ofruntime. Deploying the AccelerEyes Jacket/Matlab wrapper to use GPU gave around 100x speedup over the pure CPU code. Our further C++/CUDA optimization deliveredan additional 9x speedup.

36 MATERIALS SCIENCE↗
DOE OSTI2019

iez: Resource Contention Aware Load Balancing for Large-Scale Parallel File Systems

Parallel I/O performance is crucial to sustaining scientific applications on large-scale High-Performance Computing (HPC) systems. However, I/O load imbalance in the underlying distributed and shared storage systems can significantly reduce overall application performance. There are two conflicting challenges to mitigate this load imbalance: (i) optimizing systemwide data placement to maximize the bandwidth advantages of distributed storage servers, i.e., allocating I/O resources efficiently across applications and job runs; and (ii) optimizing client-centric data movement to minimize I/O load request latency between clients and servers, i.e., allocating I/O resources efficiently in service to a single application and job run. Moreover, existing approaches that require application changes limit wide-spread adoption in commercial or proprietary deployments. We propose iez, an “end-to-end control plane” where clients transparently and adaptively write to a set of selected I/O servers to achieve balanced data placement. Our control plane leverages realtime load information for distributed storage server global data placement while our design model leverages trace-based optimization techniques to minimize I/O load request latency between clients and servers. We evaluate our proposed system on an experimental cluster for two common use cases: synthetic I/O benchmark IOR for large sequential writes and a scientific application I/O kernel, HACC-I/O. Results show read and write performance improvements of up to 34% and 32%, respectively, compared to the state of the art.

Wadhwa, Bharti↗