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At least 1,171 records · Page 65

A Hardware and Software Co-design Framework for Energy Efficient Neuromorphic Systems

Neuromorphic systems can be realized by a variety of algorithms and architectures. A common understanding is that spiking neuromorphic designs, which encode information into spatio-temporal spiking events, are both a biologically-accurate and efficient way of processing information. However, representing the information through timing relationships induces sophisticated circuit designs in traditional CMOS-based implementations. In recent years, high-capacity resistive memory (RRAM, aka, memristor) has demonstrated great potential in mimicking synaptic behaviors. Several RRAM-based spiking neuromorphic designs exist, most of which focus on rate coding schemes. These designs simplify circuit implementations of neuron models and explore challenges such as unsatisfactory speed, resolution, and performance. As an alternative, we will explore temporal coding spiking neuromorphic systems that encode information as the relative timing of neuron activations (spikes), which have been proven to be more adaptive and energy-efficient. Developing a neuromorphic system for spiking neural network (SNN) inference and online training, however, faces some major technical challenges: (1) It lacks circuit implementation support for temporal-coding SNN to achieve satisfying power efficiency and accuracy; (2) Although existing research works have investigated memristive synapse and neuron designs for spike-timing-dependent plasticity, the non-ideal conditions in implementation, such as device variations and signal degradation, degrade online learning accuracy of large scale systems; and (3) Non-optimized, inter-layer data traffic in SNNs, leads to unnecessary data communication costs. In this project, we plan to address these challenges by a hardware and software co-design framework that incorporates solutions at the circuit, architecture, and algorithm levels. At the circuit-level, we will elaborate on the in-situ SNN processing element designs for supporting both inference and online training modes. Variation-aware schemes will be studied to improve reliability. At the architecture level, we propose a pipelined, asynchronous architecture to retain the timing resolution of spikes. At the algorithm level, we will investigate an innovative SNN training algorithm for enabling activation sparsification and reducing unnecessary data communication costs. This neuromorphic system will provide an effective solution to real-life energy-constrained applications and significantly contribute to the exploration of next-generation high-performance computing systems under the DOE context.

97 MATHEMATICS AND COMPUTING↗

Sounding-Diagnosed Convective Environments and Preliminary Energy Budgets Diagnosed during the TRMM Field Campaigns

An overview of mean convective thermodynamic and wind profiles for the Tropical Rainfall Measuring Mission (TRMM) Large Scale Biosphere-Atmosphere Experiment (LBA) and Kwajalein Experiment (KWAJEX) field campaigns will be presented, highlighting the diverse continental and marine tropical environments in which rain clouds and mesoscale convective systems evolved. An assessment of ongoing sounding quality control procedures will be shown. Additionally, we will present preliminary budgets of sensible heat source (Q1) and apparent moisture sink (Q2), which have been diagnosed from the various sounding networks.

Halverson, Jeffrey B.↗

Distributed Saturation

The Saturation algorithm for symbolic state-space generation, has been a recent break-through in the exhaustive veri cation of complex systems, in particular globally-asyn- chronous/locally-synchronous systems. The algorithm uses a very compact Multiway Decision Diagram (MDD) encoding for states and the fastest symbolic exploration algo- rithm to date. The distributed version of Saturation uses the overall memory available on a network of workstations (NOW) to efficiently spread the memory load during the highly irregular exploration. A crucial factor in limiting the memory consumption during the symbolic state-space generation is the ability to perform garbage collection to free up the memory occupied by dead nodes. However, garbage collection over a NOW requires a nontrivial communication overhead. In addition, operation cache policies become critical while analyzing large-scale systems using the symbolic approach. In this technical report, we develop a garbage collection scheme and several operation cache policies to help on solving extremely complex systems. Experiments show that our schemes improve the performance of the original distributed implementation, SmArTNow, in terms of time and memory efficiency.

Chung, Ming-Ying↗

Lagrangian large eddy simulations via physics-informed machine learning

High-Reynolds number homogeneous isotropic turbulence (HIT) is fully described within the Navier–Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as large eddy simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about effects of subgrid scales on the resolved scales. Here, we take an alternative approach and design LES heuristics stated in terms of Lagrangian particles moving with the flow. Our Lagrangian LES, thus L-LES, is described by equations generalizing the weakly compressible smoothed particle hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from direct numerical simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The subgrid-scale contributions are modeled separately with physical constraints to account for the effects from unresolved scales. We build the resulting model under the differentiable programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our L-LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Hybrid Approaches for Data Reduction of Spatiotemporal Scientific Applications

Scientists conduct large-scale simulations to compute derived quantities from primary data. Thus, it is crucial that data compression techniques maintain bounded errors on these derived quantities or quantities of interest (QOI). For many spatiotemporal applications, these QOIs are binary in nature and represent presence or absence of a physical phenomenon. In this work, we propose to use a hybrid approah for differential compression for such applications. We use a neural network (NN) approach to determine regions-of-interest (ROIs) where the binary QOIs are going to be prevalent. This is then used with traditional approaches that compress at a lower level (and higher accuracy) for these ROIs as compared to other regions.

Li, Xiao↗

DDStore: Distributed Data Store for Scalable Training of Graph Neural Networks on Large Atomistic Modeling Datasets

Graph neural networks (GNNs) are a class of Deep Learning models used in designing atomistic materials for effective screening of large chemical spaces. To ensure robust prediction, GNN models must be trained on large volumes of atomistic data on leadership class supercomputers. Even with the advent of modern architectures that consist of multiple storage layers that include node-local NVMe devices in addition to device memory for caching large datasets, extreme-scale model training faces I/O challenges at scale.We present DDStore, an in-memory distributed data store designed for GNN training on large-scale graph data. DDStore provides a hierarchical, distributed, data caching technique that combines data chunking, replication, low-latency random access, and high throughput communication. DDStore achieves near-linear scaling for training a GNN model using up to 1000 GPUs on the Summit and Perlmutter supercomputers, and reaches up to a 6.15x reduction in GNN training time compared to state-of-the-art methodologies.

Choi, Jong Youl↗

Clusters of Regional Precipitation Seasonality Change in the Community Earth System Model, Version 2

Abstract The likely changes to precipitation seasonality with warming are both impactful and not well understood. This work aims to describe areas that experience similar changes to seasonal precipitation irrespective of the original underlying precipitation seasonality. We train a self-organizing map on the difference between the seasonal cycle of precipitation in the past and in a high-warming future climate as represented by the Community Earth System Model, version 2, to create regions with similar changes in precipitation seasonality. This method is applied separately over land and ocean surfaces because of the differing processes leading to precipitation over each. This method indicates that future changes in seasonal precipitation are most varied in the tropics because of a southward shift in the intertropical convergence zone. The seasonal shifts found over midlatitude oceans indicate a poleward shift in atmospheric river activity. We find a correspondence between certain land-based precipitation changes and Köppen climate classification. The seasonality of large-scale and convective precipitation is examined for each region. The relationship between the seasonal changes to precipitation and associated atmospheric processes is discussed. These processes include atmospheric rivers, the intertropical convergence zone, tropical cyclones, and monsoons.

54 ENVIRONMENTAL SCIENCES↗

The X-shaped Radio Galaxy J0725+5835 is Associated with an AGN Pair

X-shaped radio galaxies (XRGs) are those that exhibit two pairs of unaligned radio lobes (main radio lobes and wings). One of the promising models for the peculiar morphology is jet reorientation. To clarify this, we conducted a 5 GHz observation with the European VLBI Network (EVN) of XRG J0725+5835, which resembles the archetypal binary active galactic nuclei (AGNs) 0402+379 in radio morphology, but it is larger in angular size. In our observation, two milliarcsecond-scale radio components with nonthermal radio emission are detected. Each of them coincides with an optical counterpart with similar photometric redshift and (optical and infrared) magnitude, corresponding to dual active nuclei. Furthermore, with the improved Very Large Array (VLA) images, we find a bridge between the two radio cores and a jet bending in the region surrounding the companion galaxy. This further supports the interplay between the main and companion galaxies. In addition, we also report the discovery of an arcsecond-scale jet in the companion. Given the projected separation of ~100 kpc between the main and companion galaxies, XRG J0725+5835 is likely associated with a dual jetted-AGN system. In both EVN and VLA observations, we find signatures that the jet is changing its direction, which is likely responsible for the X-shaped morphology. For the origin of jet reorientation, several scenarios are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the “Version 2” validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities.

SMAP L4_SM↗

Proposed Mars Surveyor Landing Sites in Northern Meridiani Sinus, Southern Elysium Planitia, and Argyre Planitia

Our objective is to propose two landing sites that the Mars Surveyor 2001 Lander and Athena Rover could go to on Mars that should meet the safety requirements of the spacecraft landing system and optimize surface operations (chiefly driven by power and communications requirements). An additional site within Argyre Planitia, initially proposed by Parker to the Mars Surveyor Landing Site program, is also proposed for potential consideration for post-2001 missions to Mars, as it is well outside the current latitude limits for the Athena Rover. All three sites are designed to be situated as close to a diversity of geologic units within a few kilometers of the landing site so that diversity can be placed in a geologic context. This objective is very different from the Mars Pathfinder requirement to land at a site with a maximum chance for containing a diversity of rocks within a few tens of meters of the lander. That requirement was driven by the Sojourner mobility limit of a few tens of meters. It can be argued that the Athena project, with its much larger mobility capability, might actually want to avoid such a site, because placing collected samples in geologic context would be difficult. While it has been argued, both before and after the Mars Pathfinder landing, that the provenance for local blocks may be determined by orbiter spectra, primarily from the MGS TES instrument, our ability to do so has yet to be demonstrated. Indeed, several months after conclusion of the Pathfinder mission, we have yet to reach a consensus on the composition of local materials. Our primary data set for selecting a landing site within the latitude and elevation constraints of the 2001 mission is the Viking Orbiter image archive. The site must be selected to place the landing ellipse so as to avoid obvious hazards, such as steep slopes, large or numerous craters, or abundant large knobs. For this purpose, we chose a resolution limit of better than 50 m/pixel. This necessarily excludes from the present study images from current and future orbiter spacecraft, until such data does become readily available. Within each proposed region, it may be possible to identify additional sites once these data become available. Second, the fine-component thermal inertia data, should be greater than about 5 or 6 cgs Units (10(exp -3) cal/sq cm s(exp -0.5)/K). Low thermal inertias imply dusty environments, which could pose a mobility hazard. Similarly, the albedo of the site should not be particularly high, which would also suggest dusty surfaces. Low albedos are preferred, as they often coincide with low Viking red:violet ratios and indicate less dusty surfaces. Next, the Modeled Block Abundance should also not be too high or too low. Based on the Viking Lander and Mars Pathfinder experiences, percentages of blocks should be on the order of 5-25%. Too many blocks could pose a hazard to the landing and mobility. Too few blocks could also indicate a dusty surface. Primary Landing Site: Northern Meridiani Sinus (Proposed by T. J. Parker and K., S. Edgett) Vital Statistics: (1) Latitude, Longitude: 0-3 N, 350-2 W. *Elevation (Viking): about0.5-1.5 Ian. (2) Viking Orbiter Image coverage: Excellent coverage by 15 - 25 m/pixel images (orbits 709A and 410B). Possible stereo coverage in region where two orbits overlap (probably small parallax angle, as these orbits are not listed in NASA Contractor Report 3501) (3) Albedo: about .18 -.26 (4) Block Abundance: 5-26% (5)Fine-Component Thermal Inertia: 5-9 cgs units This region consists of bright deposits similar to those described by Edgett et al, that also lie within a prominent dark albedo region. These deposits are flat-lying, to such a degree that they ramp against topography rather than draping over it. This led Edgett and Parker to suggest that they may be subaqueous sediments, possibly lacustrine or marine evaporites, laid down sometime from the late Noachian to middle Hesperian (age determination pending crater counts). A contact between this material and elevated, dissected highlands to the south was identified , and is described by Edgett et al. Our desire in proposing this landing site is to sample the edge of this deposit where it has been exposed through etching, presumably eolian deflation (the deposit, though in the highlands, is itself only lightly to moderately cratered). This should enable access to in situ stratigraphy. The actual landing site will be selected where slopes are not expected to be steep, such that the rover itself should be able to traverse them and sample layered materials on the way, either up or down the slope. Perhaps due to uncertainties at this time as to the friability or meter-scale roughness of the deposit, it might make sense to place the landing ellipse on the exhumed highland surface adjacent to the deflated margin of the deposit and plan on driving to the deposit rather than landing on it and driving downslope. This should also enable imaging the margin for evidence of layering should it prove too difficult to climb. A target ellipse on the highland surface should also allow Athena access to ancient Noachian highland materials, particularly if placed near crater ejecta or an inlier of knobby material. Secondary Landing Site: Southern Elysium Planitia (Proposed by T. J. Parker) Vital Statistics: (1) Latitude, Longitude: 1.5-3.5 S, 195-198 W. (2) Elevation (Viking): -1.0 km. (3) Viking Orbiter Image coverage: Excellent coverage by 15 - 25 m/pixel images (orbit 725). Possible stereo coverage between images from beginning and end of orbit that overlap (probably small parallax angle) (4) Albedo: about .27-.28 (5) Block Abundance: 4-7% (6) Fine-Component Thermal Inertia: about 3 cgs units This region consists of eroded knobby material, probably of Noachian age, though much of the crater population has been destroyed, that is onlapped at a sharp contact by an extensive plains unit in southern Elysium Planitia that is Amazonian in age. The plains materials have been attributed to unusually low-viscosity flood lavas from fissures south of the Elysium volcanic rise, or to lacustrine materials associated with a large, Amazonian lake at the source of Marte Vallis. Parker and Schenk presented evidence in support of the latter interpretation, though they attributed the putative shore morphology to an embayment of a northern plains ocean into the southern Elysium region. Detailed examination of the margin of the deposit, showing erosion, not simply burial, of small crater rims and fluidized ejecta blankets, also points to lacustrine or marine sedimentation rather than volcanic plains burial. The plains surface exhibits a "crusty" appearance that many researchers have attributed to pressure ridges in lava flows. In a lacustrine context, they also resemble pressure ridges in desiccated evaporite deposits and salt-rimmed pools (now dry) similar in scale and morphology to spectacular, hundred meter-scale pool rims in alkaline Lake Natron, East African Rift. The eroded highland margin surface adjacent to these plains appears to be fairly smooth, even at 15 m/pixel. Isolated knob inliers are scattered from a few kilometers to several tens of "kilometers apart. Heights of the knobs have not been measured yet but, based on experience with similar features in the Pathfinder landing ellipse, are probably typically on the order of several tens of meters high and smaller, though some of the largest knobs in the region are probably up to a few hundred meters high. Two craters larger than a kilometer in diameter, with fluidized deposits, lie nearby the proposed landing site. Very high-resolution images from MOC should help to determine whether a landing site navigable by the Athena rover could be placed in this region. The space between knobs and craters is large enough to enable placement of a target landing ellipse between them but still provide access to one or more of them and to the margin of the Elysium plains material. Post-2001 Mars Surveyor Landing Site: Argyre Planitia (Proposed by T. J. Parker) Vital Statistics: (1) Latitude, Longitude: 55-56 S, 41-43 W. (2) Elevation (Viking): 1.0 km. (3) Viking Orbiter Image coverage: Excellent coverage by 40 m/pixel images (orbits 567B, 568B, and 569B). Excellent stereo coverage with large parallax angles over the entire landing site region, and much of central and southern Argyre. (4) Albedo: about .23-.24 (5) Block Abundance: No data (6) Fine-Component Thermal Inertia: No data The floors of both the Argyre and Hellas basins contain etched layered materials that are probably thick accumulations of channel or lacustrine sediments. The deposits in Hellas are much more eroded than those in Argyre, and Hellas lacks a channel outlet. Argyre is unique in that Uzboi Vallis flowed out of the basin, requiring overflow of a standing body of water within Argyre. This makes it the largest impact basin on Mars with channels both draining into it and flowing out from it. Hellas' channels may be catastrophic flood channels, whereas Argyre was fed by modest-scale valley networks, though the outlet at Uzboi Vallis was a catastrophic flood Highland craters and basins of this kind should be high-priority landing targets for missions intended to focus on the search for either prebiotic organic materials or even simple fossil microorganisms. Basins with internally-draining valley networks should be preferred over flood channels, as they could have provided the long-term influx of water favorable to the origin of life. (Catastrophic floods are not conducive to fossil preservation, due to their very short durations and high transportation energies). They also afford an opportunity to study the evolution of the planet's climate and volatiles during the period of time between the late Noachian and early Hesperian, when a drastic change from a proposed early warm, wet climate to one more closely resembling the modern environment is thought to have occurred. Large basin

Parker, T. J.↗

Study of beyond nearest-neighbor environment and intermediate-range order in a sodium aluminosilicate geopolymer using Reverse Monte Carlo modeling

A large scale three-dimensional structural model of a geopolymer with an approximate composition of NaAlSi 2 O 6 .5.5H 2 O obtained by Reverse Monte Carlo (RMC) modeling based on experimental high-energy x-ray diffraction is presented for the first time in order to obtain information regarding beyond nearest-neighbor environment and intermediate-range order (IRO). RMC model exhibits a three-dimensional network consisting of randomly cross-linked AlO 4 and SiO 4 tetrahedral units with uniformly distributed Na atoms and H 2 O molecules. The bond angle distributions, i.e. T-O-T, O-T-O and Na-O-Na angles, are somewhat distorted with lower values compared to analogous crystal systems. The origin of the first peak in the structure factor indicating IRO is investigated using the partial structure factors; Na-Na, Si-Na, Al-Si, O-H, and H-H atom pairs are found to be the main contributors. Ring size distribution analysis demonstrates that the structure mainly involves 6-, 7- and 8-membered rings. Finally, the coherence length of these IRO characteristics is ~10.3 Å.

36 MATERIALS SCIENCE↗

Reconstructing cosmological initial conditions from late-time structure with convolutional neural networks

ABSTRACT We present a method to reconstruct the initial linear-regime matter density field from the late-time non-linearly evolved density field in which we channel the output of standard first-order reconstruction to a convolutional neural network (CNN). Our method shows dramatic improvement over the reconstruction of either component alone. We show why CNNs are not well-suited for reconstructing the initial density directly from the late-time density: CNNs are local models, but the relationship between initial and late-time density is not local. Our method leverages standard reconstruction as a preprocessing step, which inverts bulk gravitational flows sourced over very large scales, transforming the residual reconstruction problem from long-range to local and making it ideally suited for a CNN. We develop additional techniques to account for redshift distortions, which warp the density fields measured by galaxy surveys. Our method improves the range of scales of high-fidelity reconstruction by a factor of 2 in wavenumber above standard reconstruction, corresponding to a factor of 8 increase in the number of well-reconstructed modes. In addition, our method almost completely eliminates the anisotropy caused by redshift distortions. As galaxy surveys continue to map the Universe in increasingly greater detail, our results demonstrate the opportunity offered by CNNs to untangle the non-linear clustering at intermediate scales more accurately than ever before.

Astronomy & Astrophysics↗

Effectiveness and predictability of in-network storage cache for Scientific Workflows

Large scientific collaborations often have multiple scientists accessing the same set of files while doing different analyses, which create repeated accesses to the large amounts of shared data located far away. These data accesses have long latency due to distance and occupy the limited bandwidth available over the wide-area network. To reduce the wide-area network traffic and the data access latency, regional data storage caches have been installed as a new networking service. To study the effectiveness of such a cache system in scientific applications, we examine the Southern California Petabyte Scale Cache for a high-energy physics experiment. By examining about 3TB of operational logs, we show that this cache removed 67.6% of file requests from the wide-area network and reduced the traffic volume on wide-area network by 12. 3TB (or 35.4%) an average day. The reduction in the traffic volume (35.4%) is less than the reduction in file counts (67.6%) because the larger files are less likely to be reused. Due to this difference in data access patterns, the cache system has implemented a policy to avoid evicting smaller files when processing larger files. We also build a machine learning model to study the predictability of the cache behavior. Tests show that this model is able to accurately predict the cache accesses, cache misses, and network throughput, making the model useful for future studies on resource provisioning and planning.

Sim, Caitlin↗

Network structure of vertebrate scavenger assemblages at the global scale: drivers and ecosystem functioning implications

The organization of ecological assemblages has important implications for ecosystem functioning, but little is known about how scavenger communities organize at the global scale. Here, we test four hypotheses on the factors affecting the network structure of terrestrial vertebrate scavenger assemblages and its implications on ecosystem functioning. We expect scavenger assemblages to be more nested (i.e. structured): 1) in species-rich and productive regions, as nestedness has been linked to high competition for carrion resources, and 2) regions with low human impact, because the most efficient carrion consumers that promote nestedness are large vertebrate scavengers, which are especially sensitive to human persecution. 3) We also expect climatic conditions to affect assemblage structure, because some scavenger assemblages have been shown to be more nested in colder months. Finally, 4) we expect more organized assemblages to be more efficient in the consumption of the resource. We first analyzed the relationship between the nestedness of the scavenger assemblages and climatic variables (i.e. temperature, precipitation, temperature variability and precipitation variability), ecosystem productivity and biomass (i.e. NDVI) and degree of human impact (i.e. human footprint) using 53 study sites in 22 countries across five continents. Then, we related structure (i.e. nestedness) with its function (i.e. carrion consumption rate). We found a more nested structure for scavenger assemblages in regions with higher NDVI values and lower human footprint. Moreover, more organized assemblages were more efficient in the consumption of carrion. However, our results did not support the prediction that the structure of the scavenger assemblages is directly related to climate. Our findings suggest that the nested structure of vertebrate scavenger assemblages affects its functionality and is driven by anthropogenic disturbance and ecosystem productivity worldwide. Disarray of scavenger assemblage structure by anthropogenic disturbance may lead to decreases in functionality of the terrestrial ecosystems via loss of key species and trophic facilitation processes.

54 ENVIRONMENTAL SCIENCES↗

Parallel Computing for Probabilistic Response Analysis of High Temperature Composites

The objective of this Phase I research was to establish the required software and hardware strategies to achieve large scale parallelism in solving PCM problems. To meet this objective, several investigations were conducted. First, we identified the multiple levels of parallelism in PCM and the computational strategies to exploit these parallelisms. Next, several software and hardware efficiency investigations were conducted. These involved the use of three different parallel programming paradigms and solution of two example problems on both a shared-memory multiprocessor and a distributed-memory network of workstations.

Sues, R. H.↗

Physics-Informed Learning for Predictive Multi-Scale Modeling of Water Cycle and Extreme Events

Climate and earth system models have limited skill in predicting water cycle and associated extremes such as intense rain- and wind-producing storms and resulting hazards across all timescales. Water cycle predictions are inherently limited by the predictability of the chaotic system, but large potential for improving predictions remains untapped due to limited use of data-model integration to improve predictive modeling. This white paper proposes a hybrid data-physics paradigm based on physics-informed neural networks (PINNs) to improve the Energy Exascale Earth System Model (E3SM). In particular, we aim to predict and quantify uncertainties of water cycle processes and low probability high impact events.

54 ENVIRONMENTAL SCIENCES↗

MIRACL Co‐Simulation platform for control and operation of distributed wind in microgrid

Abstract This paper presents a co‐simulation platform (CSP) developed as a part of the “Microgrids, Infrastructure Resilience and Advanced Controls Launchpad (MIRACL)” project, hereafter called MIRACL‐CSP, to allow simulation‐based testing, demonstration, and evaluations of distributed wind under various grid operating conditions. MIRACL‐CSP provides modular interactions among the power distribution system, distributed wind, and utility decision‐making framework. A hierarchical engine for large‐scale infrastructure co‐simulations (HELICS) is used as the core engine of MIRACL‐CSP to establish time and information coordination among the MIRACL‐CSP modules. In this study, MIRACL‐CSP performance is demonstrated using the IEEE 123‐node test distribution grid modelled in GridLAB‐D and the utility decision support application modelled in Python. The functionality of MIRACL‐CSP is demonstrated through various grid operational scenarios in a microgrid and networked microgrid environment. A co‐simulation study is described that demonstrated MIRACL‐CSP capabilities for the microgrid operational scenario in the IEEE 123‐node test system. MIRACL‐CSP is a generic platform that facilitates distributed wind research for different test systems, applications, and valuation of distributed wind.

17 WIND ENERGY↗