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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

To Pave the Way for Large-Scale Electrode Processing of Moisture-Sensitive Ni-Rich Cathodes

High-capacity Ni-rich cathode such as LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) has a great potential to enable high energy lithium-ion batteries (LIBs) for long-range electrical vehicles. However, the utilization of NMC 811 in large-scale application is still challenging. While many published papers on NMC811 focus on materials modification, the moisture sensitivity of NMC811 and its implications in storage and large-scale electrode coating are not well explored, not to mention how to overcome those challenges for industry application. This work discusses the key parameters impacting the rheological properties of NMC811 slurries and their correlations to the properties of dried electrodes. Effective solutions are proposed to address the gelation issue of NMC811 slurry during large-scale coating to hopefully inspire more effective and practical approaches to tackle the grand challenges in electrochemical energy storage.

25 ENERGY STORAGE↗
DOE OSTI2025

Detection of supernova magnitude fluctuations induced by large-scale structure

The peculiar velocities of supernovae and their host galaxies are correlated with the large-scale structure of the Universe, and can be used to constrain the growth rate of structure and test the cosmological model. In this work, we measure the correlation statistics of the large-scale structure traced by the Dark Energy Spectroscopic Instrument Bright Galaxy Survey Data Release 1 sample, and magnitude fluctuations of type Ia supernova from the Pantheon+ compilation across redshifts z < 0.1. We find a detection of the cross-correlation signal between galaxies and type Ia supernova magnitudes. Fitting the normalised growth rate of structure f sigma_8 to the auto- and cross-correlation function measurements we find f sigma_8 = 0.384 +0.094 -0.157, which is consistent with the Planck LambdaCDM model prediction, and indicates that the supernova magnitude fluctuations are induced by peculiar velocities. Using a large ensemble of N-body simulations, we validate our methodology, calibrate the covariance of the measurements, and demonstrate that our results are insensitive to supernova selection effects. We highlight the potential of this methodology for measuring the growth rate of structure, and forecast that the next generation of type Ia supernova surveys will improve f sigma_8 constraints by a further order of magnitude.

Nguyen, A. [Swinburne U., Ctr. Astrophys. Supercom↗
DOE OSTI2022

Transition of Large-Scale Environmental Conditions and Characteristics of Four Rainfall Types Observed by S-PolKa During the MJO-1 Active Phase of DYNAMO/CINDY/AMIE

Analyses of National Center for Atmospheric Research (NCAR) S-PolKa dual-polarization radar data and ERA5 reanalysis fields indicate gradual changes in convection characteristics and large-scale environmental conditions during a central Indian Ocean Madden-Julian Oscillation (MJO) event observed by the DYNAMO/CINDY/AMIE field campaigns in late October 2011 (MJO-1). Examination of four rainfall types (isolated convective cores, convective, mixed, and stratiform) reveals a transition of convection characteristics (i.e., areal coverage and depth) between distinct 5-day environmental periods at the beginning and end of this ~2-week MJO active phase. A shift toward less frequent rainfall covering less of the radar domain for all four rainfall types occurs when large-scale lower-tropospheric dry air advects into the region with the westerly wind burst (WWB). Drier and warmer lower-free-tropospheric conditions associated with the WWB contribute to increased large-scale surface-based convective inhibition (CIN), surface-based convective available potential energy (CAPE), and cloud base heights. A thermodynamic budget analysis indicates reduced surface heat fluxes contribute to the increased surface-based CAPE. Greater CAPE at the end of MJO-1 coincides with deeper 50-dBZ convective echoes, while decreased 10-dBZ depth for all rainfall types corresponds in time with WWB-related dry-air advection. Increased (decreased) reflectivity values in the lower-level vertical reflectivity distribution of convective (stratiform) precipitation indicate increased (decreased) convective (stratiform) intensities when the WWB is present. The opposite depth changes for convective echoes and opposite shifts in convective and stratiform precipitation intensities underscore how the WWB can have differing impacts at different reflectivity thresholds and stages of the deep convection lifecycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Large‐Scale Statistically Meaningful Patterns (LSMPs) Associated With Precipitation Extremes Over Northern California

Abstract We analyze large‐scale statistically meaningful patterns (LSMPs) that precede extreme precipitation (PEx) events over Northern California (NorCal). We find LSMPs by applying k‐means clustering to the two leading principal components of daily 500 hPa geopotential height anomalies two days before the onset, from October to March during 1948–2015. Statistical significance testing based on Monte Carlo simulations suggests a minimum of four statistically distinguished LSMP clusters. The four LSMP clusters are characterized as Northwest continental negative height anomaly, Eastward positive “Pacific‐North American Pattern (PNA),” Westward negative “PNA,” and Prominent Alaskan ridge. These four clusters, shown in multiple variables, evolve very differently and have differing links to the Arctic and tropical Pacific regions. Using binary forecast skill measures and a new copula‐based framework for predicting PEx events, we find LSMP indices that are useful predictors of NorCal PEx events, with moisture‐based variables being the best predictors of PEx events at least 6 days before the onset, and the lower atmospheric variables being better than their upper atmospheric counterparts any day in advance tested. To ensure statistical rigor, the LSMPs analyzed here (with the modified acronym) include local tests of both significance and consistency, which are not always featured in the literature on large‐scale meteorological patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Visualization of large-scale charged domain Walls in hexagonal manganites

A ferroelectric charged domain wall (CDW) carries bound charges, originating from the variation of the normal components of polarization across the domain boundary, leading to a possible two-dimensional conductive interface in insulating materials. The ferroelectric CDW can be precisely created, erased, and manipulated, therefore offering an intriguing pathway toward the design of nano-devices. However, due to rather large energy costs, the size of the CDW is usually on the nanoscale. Here, taking flux-grown ferroelectric hexagonal manganites (h-RMnO 3 ) as an example, we creatively adopted an accessible inclined polishing process to reveal the domain evolution of stripe, loop, and vortex domain patterns by depth profiling. Interestingly, we observed an unexpected large-scale straight CDW in as-grown LuMnO 3 with length up to a millimeter size, which may result from the “polar catastrophe” during the flux growth. The large-scale CDW has a residual influence on the formation of the loop domain when the crystal anneals below the ferroelectric transition temperature, but completely disappears as the topological vortices emerge. The observed large-scale CDWs make h-RMnO 3 a potential candidate for advanced electronic devices, leading to a panoply of desired properties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Neutron Diffraction Residual Stress Characterization of Large-Scale Components by WA-DED

Two large scale 316L stainless steel cylindrical shells were fabricated by wire arc directed energy deposition (WA DED). Residual stresses were measured by neutron diffraction, and the microstructure and mechanical properties of the printed material were characterized. Longitudinal and transverse residual stresses were compressive at the inner diameter, near neutral at mid wall, and tensile at the outer diameter; radial (through thickness) residual stresses were relatively low in magnitude, and peak tensile residual stresses occurred at the outer diameter surface along the longitudinal direction. The printed 316L SS exhibited a heterogeneous microstructure with finely dispersed δ ferrite, and demonstrated high yield and tensile strengths with large elongation and ductile fracture at ambient temperature and at 250 °C. These results indicate that the outer diameter surface and near surface regions—where tensile residual stress is highest—are the most vulnerable to residual stress–sensitive failure modes, such as stress corrosion cracking and fatigue.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A study on the statistical significance of mutual information between morphology of a galaxy and its large-scale environment

ABSTRACT A non-zero mutual information between morphology of a galaxy and its large-scale environment is known to exist in Sloan Digital Sky Survey (SDSS) upto a few tens of Mpc. It is important to test the statistical significance of these mutual information if any. We propose three different methods to test the statistical significance of these non-zero mutual information and apply them to SDSS and Millennium run simulation. We randomize the morphological information of SDSS galaxies without affecting their spatial distribution and compare the mutual information in the original and randomized data sets. We also divide the galaxy distribution into smaller subcubes and randomly shuffle them many times keeping the morphological information of galaxies intact. We compare the mutual information in the original SDSS data and its shuffled realizations for different shuffling lengths. Using a t-test, we find that a small but statistically significant (at $99.9{{\ \rm per\ cent}}$ confidence level) mutual information between morphology and environment exists upto the entire length-scale probed. We also conduct another experiment using mock data sets from a semi-analytic galaxy catalogue where we assign morphology to galaxies in a controlled manner based on the density at their locations. The experiment clearly demonstrates that mutual information can effectively capture the physical correlations between morphology and environment. Our analysis suggests that physical association between morphology and environment may extend to much larger length-scales than currently believed, and the information theoretic framework presented here can serve as a sensitive and useful probe of the assembly bias and large-scale environmental dependence of galaxy properties.

Sarkar, Suman↗
DOE OSTI2021

Evaluating long-term emission impacts of large-scale electric vehicle deployment in the US using a human-Earth systems model

While large-scale adoption of electric vehicles (EVs) globally would reduce carbon dioxide (CO 2 ) and traditional air pollutant emissions from the transportation sector, emissions from the electric sector, refineries, and potentially other sources would change in response. Here, a multi-sector human-Earth systems model is used to evaluate the net long-term emission implications of large-scale EV adoption in the US over widely differing pathways of the evolution of the electric sector. Our results indicate that high EV adoption would decrease net CO 2 emissions through 2050, even for a scenario where all electric sector capacity additions through 2050 are fossil fuel technologies. Greater net CO 2 reductions would be realized for scenarios that emphasize renewables or decarbonization of electricity production. Net air pollutant emission changes in 2050 are relatively small compared to expected overall decreases from recent levels to 2050. States participating in the Regional Greenhouse Gas Initiative experience greater CO 2 and air pollutant reductions on a percentage basis. These results suggest that coordinated, multi-sector planning can greatly enhance the climate and environmental benefits of EVs. Additional factors are identified that influence the net emission impacts of EVs, including the retirement of coal capacity, refinery operations under reduced gasoline demands, and price-induced fuel switching in residential heating and in the industrial sector.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Post-process annealing of large-scale 3D printed polyphenylene sulfide composites

Large-scale extrusion-based additive manufacturing of high-performance thermoplastic composites like fiber reinforced polyphenylene sulfide (PPS) is well-suited for tooling applications to lower manufacturing costs and lead times. Autoclave tooling requires good mechanical performance at temperatures even above the glass transition temperature (T g ). In this work, the authors have investigated a post-process isothermal annealing technique to improve the mechanical properties of various grades of carbon fiber reinforced PPS components printed on the Big Area Additive Manufacturing (BAAM) system. Since PPS is a semi-crystalline polymer, crystallinity can change during annealing and affect the mechanical properties of the part. In addition, isothermal annealing can also lead to solid-state structural changes in the form of thermal and oxidative branching and/or crosslinking reactions in some grades of PPS which can alter the crystallization process. This work reports the effect of annealing on dynamic mechanical properties of BAAM printed components, along with studies to determine the effect of annealing on crystallinity and the occurrence of oxidative reactions. Results showed that isothermal annealing at 250 °C for 18 h improved the storage modulus of all selected grades (neat and reinforced) of PPS at temperatures above T g . Annealing led to an overall increase in the degree of crystallinity, with secondary crystallization taking place. Although oxidative structural changes were observed to occur more on the surface of the PPS parts, they primarily influenced the size of crystals formed and did not significantly alter the degree of crystallinity at various regions within the sample.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Physical and Thermomechanical Properties of Yttrium Hydride from Large Scale Bulk Metal Hydriding Furnace

Given the superior thermal stability and highly attainable hydrogen density, yttrium hydride is an excellent high-temperature moderator material in advanced thermal neutron spectrum reactors that require small core volumes. Yttrium hydride has been selected as the moderator material for the Transformational Challenge Reactor, which was launched at Oak Ridge National Laboratory (ORNL) in 2019. However, fabrication of large-scale crack-free yttrium hydride is challenging and very limited efforts have been committed to the characterization of bulk yttrium hydride in response to the need to establish a complete database of the thermomechanical properties of YHx. In this report, the challenges associated with fabricating large-scale crack-free yttrium hydride are discussed herein. In response to those challenges, a hydriding system was designed and constructed at ORNL and was used to successfully fabricate crack-free yttrium hydride in complex geometries at large scales. This was accomplished by precisely controlling the hydrogen’s partial pressure and the retort temperature, which was informed by the well-established thermodynamic properties of the binary H-Y system. Hydrogen content in as-fabricated hydride was determined by the weight change method and vacuum hot extraction technique, complemented by the X-ray diffraction (XRD). In addition, significant efforts are being dedicated to establishing a complete database of the thermomechanical properties of as-fabricated yttrium hydride. In FY2020, we investigated the thermophysical properties of yttrium hydrides as a function of temperature (room temperature to 700°C) and hydrogen concentration (H/Y ratio ranges from 1.52 to 1.93). The results indicate that at the temperatures below 300 °C, the hydrogen content did not have a significant influence on the thermal expansion, while the specific heat capacity, the thermal diffusivity, and the calculated thermal conductivity were slightly higher for the higher H/Y ratio. Between 300°C and 700 °C, a reversible second-order endothermic transition in all measured thermal properties was observed. It was also found that the onset temperatures of the observed transition varied, with the composition having inverse dependence on the hydrogen content. An attempt was made to explain the behavior of the thermophysical properties at higher temperatures by considering the order– disorder transition as a result of hydrogen redistribution. In addition, nanoindentation was employed to determine the elastic modulus and hardness and to capture the crystal orientation dependence of these parameters. Vickers hardness was also reported. The final section of the report introduces ongoing neutron irradiation campaign of yttrium hydride.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Synthesis of historical reservoir operations from 1980 to 2020 for the evaluation of reservoir representation in large-scale hydrologic models

Abstract. All the major river systems in the contiguous United States (CONUS) (and many in the world) are impacted by dams, yet reservoir operations remain difficult to quantify and model due to a lack of data. Reservoir operation data are often inaccessible or distributed across many local operating agencies, making the acquisition and processing of data records quite time-consuming. As a result, large-scale models often rely on simple parameterizations for assumed reservoir operations and have a very limited ability to evaluate how well these approaches match actual historical operations. Here, we use the first national dataset of historical reservoir operations in the CONUS domain, ResOpsUS, to analyze reservoir storage trends and operations in more than 600 major reservoirs across the US. Our results show clear regional differences in reservoir operations. In the eastern US, which is dominated by flood control storage, we see storage peaks in the winter months with sharper decreases in the operational range (i.e., the difference between monthly maximum and minimum storage) in the summer. In the more arid western US where storage is predominantly for irrigation, we find that storage peaks during the spring and summer with increases in the operational range during the summer months. The Lower Colorado region is an outlier because its seasonal storage dynamics more closely mirrored those of flood control basins, yet the region is classified as arid, and most reservoirs have irrigation uses. Consistent with previous studies, we show that average annual reservoir storage has decreased over the past 40 years, although our analyses show a much smaller decrease than previous work. The reservoir operation characterizations presented here can be used directly for development or evaluation of reservoir operations and their derived parameters in large-scale models. We also evaluate how well historical operations match common assumptions that are often applied in large-scale reservoir parameterizations. For example, we find that 100 dams have maximum storage values greater than the reported reservoir capacity from the Global Reservoirs and Dams database (GRanD). Finally, we show that operational ranges have been increasing over time in more arid regions and decreasing in more humid regions, pointing to the need for operating policies which are not solely based on static values.

Geology↗
DOE OSTI2025

Material extrusion with integrated compression molding of NdFeB/SmFeN nylon bonded magnets using small- and large-scale pellet-based 3D-printers

High-density bonded rare-earth magnets are manufactured using pellet-fed additive manufacturing (AM)/material extrusion and an integrated additive manufacturing-compression molding (AM-CM) process. Neodymium iron boron – samarium iron nitride in polyamide 12 (NdFeB-SmFeN/PA12) of 93 % weight fraction (65 % volume fraction) are used for the study. The mechanical properties (tensile strength and modulus), magnetic properties (maximum energy density, coercivity, remanence) are reported. Manufacturing parameters such as layer height, barrel temperatures, screw speed and gantry feed rate are optimized to obtain the highest possible density of the magnets using a small-scale desktop material extrusion printer. Large scale integrated additive manufacturing-compression molding (AM-CM) is then utilized to increase the density of the magnets by reducing porosity defects common in the material extrusion process. The density of as-printed magnets was 5.2 g/cm 3 with a BH max value of 124.14 kJ/m 3 , tensile strength of 20 MPa and a modulus of 2 GPa. AM-CM increased the density of the compound by 5.5 % (5.49 g/cm 3 ). The reduction in porosity was confirmed using X-ray tomography (XCT). Improvement in mechanical strength of the material was also observed, with an increase in tensile strength of 25 % (25.09 MPa) and increase in tensile modulus of 275 % (5.49 GPa). Scanning electron microscopy showed increased particle-matrix adhesion with the integrated AM-CM process.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bioeconomic benefits of managing fishing effort in a coexisting small- and large-scale fishery game

Abstract Fishing systems provide employment, income generation, poverty alleviation, and food security. The coexistence of small-scale fisheries (SSFs) and large-scale fisheries (LSFs) increases management complexity. Management actions have ecological and social implications that must be addressed carefully. We applied a bioeconomic game-theoretical model to the four-gear mullet fishery in southern Brazil—one industrial LSF (purse seine) and three artisanal SSFs (gillnet, beach seine, and drift net). All fishing gears target adult individuals during mullet's reproductive migration. First, we explored whether the current fishing efforts of all fishing gears could persist over time. Second, we investigated their interactions through a non-cooperative game. Finally, we studied the response of these interactions when fishing effort was restricted. We found that when the current fishing effort was maintained, the stock reduced to 26.4% of its capacity in 25 years. In addition, under non-cooperation, the traditional beach seine fleet exited the fishery. Interestingly, the constrained scenario had a coexistence output with increasing values for the final stock size and the per capita labour income, suggesting that limiting fishing effort can maintain all fishing gears in the fishery with social and ecological benefits.

de Azevedo, Eric Zettermann Dias (ORCID:0000000323↗
DOE OSTI2022

An automated workflow that generates atom mappings for large‐scale metabolic models and its application to Arabidopsis thaliana

SUMMARY Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large‐scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large‐scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana . We demonstrate the accuracy of RDT through a comparative analysis with atom mappings from a large database of biochemical reactions, MetaCyc. We further show the utility of our automated workflow by simulating 15 N isotope enrichment and identifying nitrogen (N)‐containing metabolites which show enrichment patterns that are informative for flux estimation in future 15 N‐MFA studies of A. thaliana . The automated workflow established in this study can be readily expanded to other species for which metabolic models have been established and the resulting atom mappings will facilitate MFA and graph‐theoretic structural analyses with large‐scale metabolic networks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Linking large-scale weather patterns to observed and modeled turbine hub-height winds offshore of the US West Coast

The US West Coast holds great potential for wind power generation, although its potential varies due to the complex coastal climate. Characterizing and modeling turbine hub-height winds under different weather conditions are vital for wind resource assessment and management. This study uses a two-stage machine learning algorithm to identify five large-scale meteorological patterns (LSMPs): post-trough, post-ridge, pre-ridge, pre-trough, and California high. The LSMPs are linked to offshore wind patterns, specifically at lidar buoy locations within lease areas for future wind farm development off Humboldt and Morro Bay. While each LSMP is associated with characteristic large-scale atmospheric conditions and corresponding differences in wind direction, diurnal variation, and jet features at the two lidar sites, substantial variability in wind speeds can still occur within each LSMP. Wind speeds at Humboldt increase during the post-trough, pre-ridge, and California-high LSMPs and decrease during the remaining LSMPs. Morro Bay has smaller responses in mean speeds, showing increased wind speed during the post-trough and California-high LSMPs. Besides the LSMPs, local factors, including the land–sea thermal contrast and topography, also modify mean winds and diurnal variation. The High-Resolution Rapid Refresh model analysis does a good job of capturing the mean and variation at Humboldt but produces large biases at Morro Bay, particularly during the pre-ridge and California-high LSMPs. The findings are anticipated to guide the selection of cases for studying the influence of specific large-scale and local factors on California offshore winds and to contribute to refining numerical weather prediction models, thereby enhancing the efficiency and reliability of offshore wind energy production.

17 WIND ENERGY↗
DOE OSTI2022

Layer Time Control for Large Scale Additive Manufacturing Using High Performance Computing

This work proposes to optimize an additive manufacturing AM process to reduce energy and printing cost. The polymer AM process is inherently dependent on the time-temperature history of each layer to maintain geometric tolerances and mechanical integrity. Our preliminary study shows that regression-based layer time control model using thermal images could result in up to 30% build time reduction for simple geometries. This proposed work would use high-performance computing (HPC) to couple the data-driven model with thermal simulation for better predicting layer temperature profiles, improving throughput of large-scale additive manufacturing, and reducing its energy cost. We have developed a method to optimize a layer deposition time (a.k.a. layer time) for large-scale AM via physics-based simulations. A long layer time leads to an over-cooled surface on which a new layer is deposited, and therefore, it may result in a weak bonding or debonding between layers, cracking, or warping. A short layer time leads to a high temperature of the structure due to insufficient cooling, and therefore, the structure may not be stiff enough and may collapse during manufacturing. Therefore, it is important to estimate the optimal layer time in additive manufacturing for a high-quality product. The temperature of a top layer right before deposition is recommended to be slightly higher than the glass temperature of the material. A temperature cooling was approximated to an exponential function of time, and the optimized layer time was obtained based on a target temperature while maintaining a minimal printing time. The material used is carbon fiber-reinforced polycarbonate (CF/PC), and the large-scale deposition system used is LSAM TM from Thermwood Corporation. Three different layer time cases were used for experiments, and a series of thermal images were obtained via an infra-red (IR) camera during the entire AM processes. AM process simulations were performed using a finite element method and the temperature profiles from the simulation were in good agreements with those from experiments. The layer time optimization was performed based on the temperature profiles from the simulations. A layer temperature with the optimal layer time was confirmed as the target temperature through simulation. In addition to the development of a layer time optimization method, we have developed a numerical framework for AM simulation with element activations in sync with toolpath, based on an open source finite element framework, DEAL.II. A major portion of this work was presented at SAMPE 2022 Conference and Exhibition on May 2022, and published in Proceedings of SAMPE 2022.

42 ENGINEERING↗
DOE OSTI2026

Commissioning of the large-scale lead tungstate scintillating calorimeter

Here, we report on the installation and initial commissioning of a large-scale lead tungstate (PbWO4) scintillating crystal calorimeter developed for high-rate photon detection and precise energy measurement. The calorimeter comprises 1596 high-granularity, high-resolution scintillating crystals optimized for electromagnetic-shower detection over a wide energy range. Scintillation light from each crystal is read out by Hamamatsu R4125 photomultiplier tubes equipped with a custom voltage divider and front-end amplifier to ensure stable gain at high rates. All calorimeter modules were fabricated and characterized using a light-emitting diode–based optical test system prior to installation to verify uniformity and photodetector performance. After installation, the electromagnetic calorimeter was fully integrated into the experiment data acquisition and energy-based trigger systems. The optical response of the modules was equalized using the light-monitoring system, cosmic-ray muons, and photons from Compton-scattering events. Commissioning results demonstrate a reliably calibrated optical response and stable detector performance during the first run. These results validate the calorimeter design and commissioning methodology for large-scale scintillator-based photonic instrumentation.

Analog to digital converters↗
DOE OSTI2020

Compiler and Runtime Approaches to Enable Large-Scale Irregular Programs. Final report, July 2013 - July 2019

While regular algorithms, characterized by operations on dense matrices and arrays, have long been the mainstay of scientific, high-performance computing, irregular algorithms, which feature unpredictable accesses to pointer-based data structures, are becoming increasingly common in high performance computing, arising in graph analysis, data mining and visualization, among other domains. Unfortunately, the defining characteristics of irregular applications, their dynamic, unpredictable, data-dependent access patterns and data layouts, make achieving high performance on large scale systems difficult. Scaling applications to peta- and exa-scale requires carefully controlling communication and data movement and placement, an inherently difficult task when access patterns and data layouts are unpredictable! Most irregular applications that attain high performance must be painstakingly hand-written and hand-tuned, with few common principles or paradigms uniting various implementations and easing future development. Despite the increasing importance of irregular applications, there is little programmer knowledge, and even less compiler ability, devoted to optimizing them. This project aims to solve these problems. By allowing programmers to write irregular applications in high level forms, with at most a few annotations highlighting key structural properties, programmers can focus on developing their algorithms and methods. The compiler and run-time system can take on the tedious task of optimizing the application for execution at large scales, and can automatically provide efficient implementations. This will provide portability and ease maintenance for existing irregular applications, but, more importantly, open up whole new domains of computational science to large-scale, high-performance simulation codes.

97 MATHEMATICS AND COMPUTING↗