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NASA NTRS2011

Alaska: Glaciers of Kenai Fjords National Park and Katmai and Lake Clark National Parks and Preserve

There are hundreds of glaciers in Kenai Fjords National Park (KEFJ) and Katmai National Park and Preserve (KATM) covering over 2276 sq km of park land (circa 2000). There are two primary glacierized areas in KEFJ -- the Harding Icefield and the Grewingk-Yalik Glacier Complex, and three primary glacierized areas in KATM - the Mt. Douglas area, the Kukak Volcano to Mt. Katmai area and the Mt. Martin area. Most glaciers in these parks terminate on land, though a few terminate in lakes. Only KEFJ has tidewater glaciers, which terminate in the ocean. Glacier mapping and analysis of the change in glacier extent has been accomplished on a decadal scale using satellite imagery, primarily Landsat data from the 1970s, 1980s, and from 2000. Landsat Multispectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) imagery was used to map glacier extent on a park-wide basis. Classification of glacier ice using image processing software, along with extensive manual editing, was employed to create Geographic Information System (GIS) outlines of the glacier extent for each park. Many glaciers that originate in KEFJ but terminate outside the park boundaries were also mapped. Results of the analysis show that there has been a reduction in the amount of glacier ice cover in the two parks over the study period. Our measurements show a reduction of approximately 21 sq km, or -1.5% (from 1986 to 2000), and 76 sq km, or -7.7% (from 1986/87 to 2000), in KEFJ and KATM, respectively. This work represents the first comprehensive study of glaciers of KATM. Issues that complicate the mapping of glacier extent include: debris-cover (moraine and volcanic ash), shadows, clouds, fresh snow, lingering snow from the previous season, and differences in spatial resolution between the MSS and TM or ETM+ sensors. Similar glacier mapping efforts in western Canada estimate mapping errors of 3-4%. Measurements were also collected from a suite of glaciers in KEFJ and KATM detailing terminus positions and rates of recession using datasets including the 15-minute USGS quadrangle maps (1950/1951), Landsat imagery (1986/1987, 2000, 2006) and 2005 Ikonos imagery (KEFJ only).

Giffen, bruce A.↗

DOE OSTI2023

Crack-Free Joining of High-Strength AA7055 Sheets by Friction Based Self-Piercing Riveting with the Aid of Numerical Design

Unique friction-based self-piercing riveting (F-SPR) was employed to join high-strength, low-ductility aluminum alloy 7055 for lightweight vehicle applications. This study aimed to maximize the joint strength of the AA7055 F-SPR joint while avoiding cracking issues due to low ductility at room temperature. A fully coupled Eulerian–Lagrangian (CEL) model was employed to predict the process temperature during F-SPR, and the temperature field was then mapped onto a 2D axisymmetric equivalent model for accelerated numerical analysis. The geometry, dimensions, and material strength of the rivet, as well as the depth of the die cavity and plunging depth, were investigated to enhance joint formation. Also, a static finite-element analysis model was developed to predict and analyze the stress distribution in the rivet under different mechanical testing loading conditions. Overall, the numerical model showed good agreement with the experiment results, such as joint formation and mechanical joint strength. With the aid of virtual fabrication through numerical modeling, the joint design iterations and process development time of F-SPR were greatly reduced regarding the goal of lightweight, high-strength aluminum joining.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

GeoAI advances in specific landform mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation. References: Arundel, Samantha T., Wenwen Li, and Sizhe Wang. 2020. “GeoNat v1.0: A Dataset for Natural Feature Mapping with Artificial Intelligence and Supervised Learning.” Transactions in GIS 24 (3): 556–72. https://doi.org/10.1111/tgis.12633. Arundel, Samantha T, and Gaurav Sinha. 2018. “Validating GEOBIA Based Terrain Segmentation and Classification for Automated Delineation of Cognitively Salient Landforms BT - Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017).” In Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017), Lecture Notes in Geoinformation and Cartography, edited by Paolo Fogliaroni, Andrea Ballatore, and Eliseo Clementini, 9–14. Cham: Springer International Publishing. Arundel, Samantha T., Gaurav Sinha, Wenwen Li, David P. Martin, Kevin G. McKeehan, and Philip T. Thiem. 2023. “Historical Maps Inform Landform Cognition in Machine Learning.” Abstracts of the ICA 6 (August): 1–2. https://doi.org/10.5194/ica-abs-6-10-2023. Evans, Ian S. 2012. “Geomorphometry and Landform Mapping: What Is a Landform?” Geomorphology 137 (1): 94–106. https://doi.org/10.1016/j.geomorph.2010.09.029.

machine learning↗

NASA NTRSDate not supplied

GeoAI Advances in Specific Landform Mapping

machine learning↗

DOE OSTI2021

Nonequilibrium phonon tuning and mapping in few-layer graphene with infrared nanoscopy

Electron-phonon interactions are fundamentally important physical processes responsible for many key discoveries in condensed matter physics and material sciences. Herein, by exploiting the scattering-type scanning near-field optical microscope (s-SNOM) excited with a femtosecond infrared (IR) laser, we explored the strong coupling between IR phonons in few-layer graphene (FLG) with ultrahot electrons, which are heated up by the intense laser field enhanced by the s-SNOM tip. More specifically, we found that the intensity of the phonon resonance can be tuned systematically by varying the laser power that controls the electron temperature. Furthermore, the high spatial resolution of s-SNOM allows us to map the local phonon characteristics at sharp boundaries and nanostructures. Our results offer insights into the intriguing physics behind the electron-phonon interactions in nonequilibrium conditions and open a pathway for manipulating phonons with optical means.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1987

Laser Scanner for Tile-Cavity Measurement

Irregular surfaces mapped and digitized for numerical-control machinery. Fast, accurate laser scanning system measures size and shape of cavity without making any physical contact with cavity and walls. Measurements processed into control signals for numerically controlled machining of tile or block to fit cavity. System generates map of grid points representing cavity and portion of outer surface surrounding cavity. Map data used to control milling machine, which cuts tile or block to fit in cavity.

Yoshino, Stanley Y.↗

DOE OSTI2018

Hyperspectral remote sensing of fire: state-of-the-art and future perspectives

We report that fire is a widespread Earth system process with important carbon and climate feedbacks. Multispectral remote sensing has enabled mapping of global spatiotemporal patterns of fire and fire effects, which has significantly improved our understanding of interactions between ecosystems, climate, humans and fire. With several upcoming spaceborne hyperspectral missions like the Environmental Mapping And Analysis Program (EnMAP), the Hyperspectral Infrared Imager (HyspIRI) and the Precursore Iperspettrale Della Missione Applicativa (PRISMA), we provide a review of the state-of-the-art and perspectives of hyperspectral remote sensing of fire. Hyperspectral remote sensing leverages information in many (often more than 100) narrow (smaller than 20 nm) spectrally contiguous bands, in contrast to multispectral remote sensing of few (up to 15) non-contiguous wider (greater than 20 nm) bands. To date, hyperspectral fire applications have primarily used airborne data in the visible to short-wave infrared region (VSWIR, 0.4 to 2.5 μm). This has resulted in detailed and accurate discrimination and quantification of fuel types and condition, fire temperatures and emissions, fire severity and vegetation recovery. Many of these applications use processing techniques that take advantage of the high spectral resolution and dimensionality such as advanced spectral mixture analysis. So far, hyperspectral VSWIR fire applications are based on a limited number of airborne acquisitions, yet techniques will approach maturity for larger scale application when spaceborne imagery becomes available. Recent innovations in airborne hyperspectral thermal (8 to 12 μm) remote sensing show potential to improve retrievals of temperature and emissions from active fires, yet these applications need more investigation over more fires to verify consistency over space and time, and overcome sensor saturation issues. Furthermore, hyperspectral information and structural data from, for example, light detection and ranging (LiDAR) sensors are highly complementary. Finally, their combined use has demonstrated advantages for fuel mapping, yet its potential for post-fire severity and combustion retrievals remains largely unexplored.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1983

Hot spot heat transfer - Its application to Venus and implications to Venus and earth

Using a model that gives a relationship between surface elevation, lithospheric thickness, and heat flux, the hot spot heat loss mechanism is tested for Venus. The mechanism is found to readily explain the predicted heat loss of the planet with a modest number of hot spots (of the order of 35). Lithospheric thickness variations can explain approximately 93 percent of the mapped topography of Venus. Above a radius of 6053 km, additional compensation is required, and this can be effected by incorporating a variable thickness crust into the model. If it is assumed that the crust is generated on the crests of the hot spots, probably by processes associated with volcanism, the model is consistent with nearly 99 percent of the mapped topography of Venus. In addition, the model is basically consistent with available gravity data and interpretations that suggest compensated topography and great depths of compensation (100-1000 km) for the midlatitudes of the planet. It is thought that the approximately 1 percent of the topography not explained by hot spot crustal generation is compensated at a shallower depth primarily by variations in crustal thickness that are not directly related to hot spot volcanism.

Morgan, P.↗

NASA NTRS1993

Maximum a posteriori classification of multifrequency, multilook, synthetic aperture radar intensity data

We present a maximum a posteriori (MAP) classifier for classifying multifrequency, multilook, single polarization SAR intensity data into regions or ensembles of pixels of homogeneous and similar radar backscatter characteristics. A model for the prior joint distribution of the multifrequency SAR intensity data is combined with a Markov random field for representing the interactions between region labels to obtain an expression for the posterior distribution of the region labels given the multifrequency SAR observations. The maximization of the posterior distribution yields Bayes's optimum region labeling or classification of the SAR data or its MAP estimate. The performance of the MAP classifier is evaluated by using computer-simulated multilook SAR intensity data as a function of the parameters in the classification process. Multilook SAR intensity data are shown to yield higher classification accuracies than one-look SAR complex amplitude data. The MAP classifier is extended to the case in which the radar backscatter from the remotely sensed surface varies within the SAR image because of incidence angle effects. The results obtained illustrate the practicality of the method for combining SAR intensity observations acquired at two different frequencies and for improving classification accuracy of SAR data.

Rignot, E.↗

DOE OSTI2022

Physics-Informed Sparse Gaussian Process for Probabilistic Stability Analysis of Large-Scale Power System with Dynamic PVs and Loads

This work proposes a physics-informed sparse Gaussian process (SGP) for probabilistic stability assessment of large-scale power systems in the presence of uncertain dynamic PVs and loads. The differential and algebraic equations considering uncertainties from dynamic PVs and loads are reformulated to a nonlinear mapping relationship that allows the application of SGP. Thanks to the nonparametric characteristic of Gaussian process, the proposed framework does not require distributions of uncertain inputs and this distinguishes it from existing approaches. As the original Gaussian process is not scalable to large-scale systems with high dimensional uncertain inputs, this paper develops the SGP with a stochastic variational inference technique. It leads to approximately two orders of complex reduction. A data pre-processing step is also introduced to tackle the coexistence of stable and unstable cases by sample clustering and constructing separate SGPs. The probabilistic transient stability index is analyzed to assess system stability under different uncertain dynamics loads and PVs. Comparisons are performed with the sampling-based, the polynomial chaos expansion-based, and traditional Gaussian process-based methods on the modified IEEE 118-bus and Texas 2000-bus systems under various scenarios, including different levels of uncertainties and the existence of nonlinear correlations among dynamic PVs. The impacts of data quality and quantity issues are also investigated. It is shown that the proposed SGP achieves significantly improved computational efficiency while maintaining high accuracy with a limited number of data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1984

Automatic terrain elevation mapping and registration

Optimum radar illumination geometries for stereoscopic analysis of surface topography are determined. Correlation and image processing experiments on synthetic aperture radar (SAR) data for improved information extraction are conducted. Model of the geometry of the multiple SIR-B views of the Earth are developed the sensitivity of the derived terrain altitude data to the various system parameters is established. The limits of accuracy of terrain data achievable with shuttle imaging radar (SIR-B) are derived. Algorithms for matching multiple SIR-B images to generate digital terrain maps are developed. Finally, the use of such terrain maps in geometric correction and registration of SIR-B and LANDSAT Thematic Mapper data is demonstrated.

Ramapriyan, H. K.↗

DOE OSTI2021

Pro‐ L * ‐ A Probabilistic L * Mapping Tool for Ground Observations

Abstract Both ground and space observations are used extensively in the modeling of space weather processes within the Earth’s magnetosphere. In radiation belt physics modeling, one of the key phase‐space coordinates is L *, which indicates the location of the drift paths of energetic electrons. Global magnetic field models allow a subset of locations on the ground (mainly subauroral) to be mapped along field lines to a location in space and transformed into L *, provided that the initial ground location maps to a closed drift path. This allows observations from ground, or low‐altitude space‐based platforms to be mapped into space in order to inform radiation belt modeling. Many data‐based magnetic field models exist; however, these models can significantly disagree on mapped L * values for a single point on the ground, during both quiet times and storms. We present a state of the art probabilistic L * mapping tool, Pro‐ L *, which produces probability distributions for L * corresponding to a given ground location. Pro‐ L * has been calculated for a high resolution magnetic latitude by magnetic local time grid in the Earth’s Northern Hemisphere. We have developed the probabilistic model using 11 years of L * calculations for seven widely used magnetic field models. Usage of the tool is highlighted for both event studies and statistical models, and we demonstrate a number of potential applications.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1973

Optical data processing and projected applications of the ERTS-1 imagery covering the 1973 Mississippi River Valley floods

Flooding along the Mississippi River and some of its tributaries was imaged by the multispectral scanner (MSS) on the Earth Resources Technology Satellite (ERTS-1) on at least three orbits during the spring of 1973. The ERTS data provided the first opportunity for mapping the regional extent of flooding at the time the imagery was acquired. Special optical data processing techniques were used to produce a variety of multispectral color composites which enhanced floodplain details. One of these, a two-color composite of near infrared bands 6 and 7, was enlarged and registered to 1:250,0OO-scale topographic maps and used as the basis for preparation of flood image maps. Two specially filtered three-color composites of MSS bands 5, 6, and 7 and 4, 5, and 7 were prepared to aid in the interpretation of the data. The extent of the flooding was vividly depicted on a single image by two-color temporal composites produced on the additive-color viewer using band 7 flood data superimposed on pre-flood band 7 images. On May 24, when the floodwaters at St. Louis receded to bankfull stage, imagery was again obtained by ERTS. Analysis of temporal data composites of the pre-flood and post-flood band 7 images indicate that changes in surface reflectance characteristics caused by the flooding can be delineated, thus making it possible to map the overall area flooded without the necessity of a real-time system to track and image the peak flood waves. Regional planning and disaster relief agencies such as the Corps of Engineers, Office of Emergency Preparedness, Soil Conservation Service, interstate river basin commissions and state agencies, as well as private lending and insurance institutions, have indicated strong potential applications for ERTS image-maps of flood-prone areas.

Morris Deutsch↗

NASA NTRS2010

Real-Time Feature Tracking Using Homography

This software finds feature point correspondences in sequences of images. It is designed for feature matching in aerial imagery. Feature matching is a fundamental step in a number of important image processing operations: calibrating the cameras in a camera array, stabilizing images in aerial movies, geo-registration of images, and generating high-fidelity surface maps from aerial movies. The method uses a Shi-Tomasi corner detector and normalized cross-correlation. This process is likely to result in the production of some mismatches. The feature set is cleaned up using the assumption that there is a large planar patch visible in both images. At high altitude, this assumption is often reasonable. A mathematical transformation, called an homography, is developed that allows us to predict the position in image 2 of any point on the plane in image 1. Any feature pair that is inconsistent with the homography is thrown out. The output of the process is a set of feature pairs, and the homography. The algorithms in this innovation are well known, but the new implementation improves the process in several ways. It runs in real-time at 2 Hz on 64-megapixel imagery. The new Shi-Tomasi corner detector tries to produce the requested number of features by automatically adjusting the minimum distance between found features. The homography-finding code now uses an implementation of the RANSAC algorithm that adjusts the number of iterations automatically to achieve a pre-set probability of missing a set of inliers. The new interface allows the caller to pass in a set of predetermined points in one of the images. This allows the ability to track the same set of points through multiple frames.

Clouse, Daniel S.↗

DOE OSTI2019

Replays of spatial memories suppress topological fluctuations in cognitive map

The spiking activity of the hippocampal place cells plays a key role in producing and sustaining an internalized representation of the ambient space—a cognitive map. These cells do not only exhibit location-specific spiking during navigation, but also may rapidly replay the navigated routs through endogenous dynamics of the hippocampal network. Physiologically, such reactivations are viewed as manifestations of “memory replays” that help to learn new information and to consolidate previously acquired memories by reinforcing synapses in the parahippocampal networks. Below we propose a computational model of these processes that allows assessing the effect of replays on acquiring a robust topological map of the environment and demonstrate that replays may play a key role in stabilizing the hippocampal representation of space.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1993

Automated System for Early Breast Cancer Detection in Mammograms

The increasing demand on mammographic screening for early breast cancer detection, and the subtlety of early breast cancer signs on mammograms, suggest an automated image processing system that can serve as a diagnostic aid in radiology clinics. We present a fully automated algorithm for detecting clusters of microcalcifications that are the most common signs of early, potentially curable breast cancer. By using the contour map of the mammogram, the algorithm circumvents some of the difficulties encountered with standard image processing methods. The clinical implementation of an automated instrument based on this algorithm is also discussed.

Bankman, Isaac N.↗

NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 20

The topics include: 1) Virtual Reality Technology as a Tool to Enhance Collaboration Between Space Exploration and Public Outreach: The Case Using the Mars Exploration Rover Images; 2) Atmospheric Electron-induced X-Ray Spectrometer (AEXS) Instrument Development; 3) Impact of Low Thermal Conductivity Layers on the Bulk Conductivity of a Martian Crustal Column; 4) Impacting Classroom Teachers Through Long-Term Professional Development; 5) Oxygen, Ca, and Ti Isotopic Compositions of Hibonite-bearing Inclusions; 6) Phenomenological Excitation Functions of Xe Isotopes with Protons on Nuclei of Cs, La and Ce; 7) Double-Diffusive Convection and Other Modes of Salinity-modulated Heat and Material Transport in Europa s Ocean; 8) Slope Morphologies of the Hellas Mensae Constructs, Eastern Hellas Planitia, Mars; 9) Development of Polygonal Thermal Contraction Patterns in a South Polar Trough, Mars 3 Years of Observations; 10) Martian Relevance of Dehydration and Rehydration in the Mg-Sulfate System; 11) Formation of Martian Volcanic Provinces by Lower Mantle Flushing? 12) Can Glasses Help Us to Unravel the Origin of Barred Olivine Chondrules? 13) Loki Patera: A Magma Sea Story; 14) Compositions of Partly Altered Olivine and Replacement Serpentine in the CM2 Chondrite QUE93005; 15) Model of Light Scattering by Lunar Regolith at Moderate Phase Angles: New Results; 16) Radiation Resistance of a Silicone Polymer Grease Based Regolith Collector for the HERA Near-Earth Asteroid Sample Return Mission; 17) Analysis of the Tectonic Lineaments in the Ganiki Planitia (V14) Quadrangle, Venus; 18) Nanometer-sized Diamonds from AGB Stars; 19) Quantifying Exact Motions Along Lineaments on Europa; 20) Geometry of Thrust Faults Beneath Amenthes Rupes, Mars; 21) Mapping of the Physical Characteristics and Mineral Composition of a Superficial Layer of the Moon or Mars and Ultra-Violet Polarimetry from the Orbital Station; 22) Negative Searches for Evidence of Aqueous Alteration on Asteroid Surfaces; 23) What Processes Have Shaped Basalt Boulders on Earth and Mars? Studies of Feature Persistence Using Facet Mapping and Fractal Analysis; 24) The Popigai Fluidizites: Dense Water Inclusions in Lechatelierite; Evidence for Shock-generated Carbonate and Hydrous Silicate Melts; 25) Missing Xenon Problem and Climate of the Early Earth; and 26) More on Magnetic Spectra from Correlated Crustal Sources on Mars

Source record↗

NASA NTRS2000

Incremental Parallelization of Non-Data-Parallel Programs Using the Charon Message-Passing Library

Message passing is among the most popular techniques for parallelizing scientific programs on distributed-memory architectures. The reasons for its success are wide availability (MPI), efficiency, and full tuning control provided to the programmer. A major drawback, however, is that incremental parallelization, as offered by compiler directives, is not generally possible, because all data structures have to be changed throughout the program simultaneously. Charon remedies this situation through mappings between distributed and non-distributed data. It allows breaking up the parallelization into small steps, guaranteeing correctness at every stage. Several tools are available to help convert legacy codes into high-performance message-passing programs. They usually target data-parallel applications, whose loops carrying most of the work can be distributed among all processors without much dependency analysis. Others do a full dependency analysis and then convert the code virtually automatically. Even more toolkits are available that aid construction from scratch of message passing programs. None, however, allows piecemeal translation of codes with complex data dependencies (i.e. non-data-parallel programs) into message passing codes. The Charon library (available in both C and Fortran) provides incremental parallelization capabilities by linking legacy code arrays with distributed arrays. During the conversion process, non-distributed and distributed arrays exist side by side, and simple mapping functions allow the programmer to switch between the two in any location in the program. Charon also provides wrapper functions that leave the structure of the legacy code intact, but that allow execution on truly distributed data. Finally, the library provides a rich set of communication functions that support virtually all patterns of remote data demands in realistic structured grid scientific programs, including transposition, nearest-neighbor communication, pipelining, gather/scatter, and redistribution. At the end of the conversion process most intermediate Charon function calls will have been removed, the non-distributed arrays will have been deleted, and virtually the only remaining Charon functions calls are the high-level, highly optimized communications. Distribution of the data is under complete control of the programmer, although a wide range of useful distributions is easily available through predefined functions. A crucial aspect of the library is that it does not allocate space for distributed arrays, but accepts programmer-specified memory. This has two major consequences. First, codes parallelized using Charon do not suffer from encapsulation; user data is always directly accessible. This provides high efficiency, and also retains the possibility of using message passing directly for highly irregular communications. Second, non-distributed arrays can be interpreted as (trivial) distributions in the Charon sense, which allows them to be mapped to truly distributed arrays, and vice versa. This is the mechanism that enables incremental parallelization. In this paper we provide a brief introduction of the library and then focus on the actual steps in the parallelization process, using some representative examples from, among others, the NAS Parallel Benchmarks. We show how a complicated two-dimensional pipeline-the prototypical non-data-parallel algorithm- can be constructed with ease. To demonstrate the flexibility of the library, we give examples of the stepwise, efficient parallel implementation of nonlocal boundary conditions common in aircraft simulations, as well as the construction of the sequence of grids required for multigrid.

VanderWijngaart, Rob F.↗