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NASA NTRSDate not supplied

Document Classification Techniques for Aviation Letters of Agreement

Often when working with historic air traffic management (ATM) documents, it is helpful to classify them into specific categories. In this paper, we conduct a thorough review of natural language processing techniques to perform this classification task on Letters of Agreement (LOAs), technical aviation documents outlining rules for utilizing US airspace. We evaluate multiple techniques for representing the text in the documents as embeddings: unigram and bigram Term Frequency Inverse Document Frequency (TFIDF), Word2Vec, Doc2Vec, GloVe and RoBERTa. We investigate a wide range of classification models: K-Nearest Neighbors, Random Forest, Support Vector Machines (SVM), Logistic Regression, Naive Bayes, Feed-Forward Neural Network, Convolutional Neural Networks (CNNs) and Long-Short Term Memory (LSTM). By comparing the different methods, we found the best overall approach for our task was to use unigram TFIDF representations with SVM while also gaining insight into how the other methodologies performed on a small technical datasets.

ATM↗
NASA NTRS1990

Multi-processing on supercomputers for computational aerodynamics

The MIMD concept is applied, through multitasking, with relatively minor modifications to an existing code for a single processor. This approach maps the available memory to multiple processors, exploiting the C-FORTRAN-Unix interface. An existing single processor algorithm is mapped without the need for developing a new algorithm. The procedure of designing a code utilizing this approach is automated with the Unix stream editor. A Multiple Processor Multiple Grid (MPMG) code is developed as a demonstration of this approach. This code solves the three-dimensional, Reynolds-averaged, thin-layer and slender-layer Navier-Stokes equations with an implicit, approximately factored and diagonalized method. This solver is applied to a generic, oblique-wing aircraft problem on a four-processor computer using one process for data management and nonparallel computations and three processes for pseudotime advance on three different grid systems.

Yarrow, Maurice↗
NASA NTRS2000

Free-Flying Magnetometer Data System

The Free-Flying Magnetometer (FFM) is an autonomous "sensorcraft" developed at the Jet Propulsion Laboratory (JPL) for the Enstrophy sounding rocket mission. This mission was a collaborative project between the University of New Hampshire, Cornell University and JPL. The science goal of the mission was the study of current filamentation phenomena in the northern auroral region through multipoint measurements of magnetic field. The technical objective of the mission was the proof of concept of the JPL FFM design and the demonstration of an in-situ multipoint measurement technique employing many free-flying spacecraft. Four FFMs were successfully deployed from a sounding rocket launched from Poker Flats, Alaska on February 11, 1999. These hockey-puck-sized (80 mm diameter, 38 mm. height, 250 gram mass) free flyers each carry a miniature 3-axis flux-gate magnetometer that output +/- 2 V signals corresponding to a +/- 60,000 nT measurement range for each axis. The FFM uses a synchronized four-channel Sigma(Delta) Analog-to-Digital Converter (ADC) having a dynamic range of +/- 2.5V and converting at a rate of 279 samples/second/channel. Three channels are used to digitize the magnetometer signals to 17-bit (1.144 nT/bit) resolution. The fourth ADC channel is multiplexed for system monitoring of four temperature sensors and two battery voltages. The FFM also contains two sun sensors, a laser diode which emits a fan-shaped beam, a miniature S-band transmitter for direct communication to the ground station antennas, an ultra-stable Temperature Compensated Crystal Oscillator (TCXO) clock, an integrated data subsystem implemented in a Field-Programmable Gate Array (FPGA), a 4 Mbit Static Random Access Memory (SRAM) for data storage and Lithium Thionyl Chloride batteries for power. Communicating commands to the FFM prior to deployment is achieved with an infrared (IR) link. The FFM IR receiver responds to 9-bit pulse coded signals that are generated by an IR Light Emitting Diode (LED) in the payload for turning FFM power on or off and placing the FFM in a test mode or flight mode. The IR links are also used to synchronize (zero) the clocks onboard all the FFMs through a reset pulse originating from the payload GPS receiver that is issued when the FFMs are in flight mode. The FPGA based data subsystem manages continuous data collection from the four ADC channels and sun sensors, formatting and storing the data to SRAM, and controlling downlink transmission. The transmitter is powered only after a 2547 frame SRAM buffer has been filled (approx. 5 minutes of data). The data is Viterbi encoded and sent to the S-band transmitter via a First-In-First-Out (FIFO) buffer who's output is clocked at 100 bits/second. After the 26-second transmission, the transmitter is turned off to reduce noise coupling to the sensitive magnetometer. The data subsystem control consists of a master state machine that performs data flow management and is interfaced through a prioritized interrupt scheme to state machines that service the ADC, sun sensors and transmitter FIFO. Continuous data collection prevents the missing of data during transmission and provides implicit time tagging of the data acquired by the ADC because of synchronization with the TCXO clock.

Blaes, B.↗
NASA NTRS2002

An Efficient Scheme for Updating Sparse Cholesky Factors

Raghavan had earlier developed the software package DCSPACK which can be used for solving sparse linear systems where the coefficient matrix is symmetric and positive definite (this project was not funded by NASA but by agencies such as NSF). DSCPACK-S is the serial code and DSCPACK-P is a parallel implementation suitable for multiprocessors or networks-of-workstations with message passing using MCI. The main algorithm used is the Cholesky factorization of a sparse symmetric positive positive definite matrix A = LL(T). The code can also compute the factorization A = LDL(T). The complexity of the software arises from several factors relating to the sparsity of the matrix A. A sparse N x N matrix A has typically less that cN nonzeroes where c is a small constant. If the matrix were dense, it would have O(N2) nonzeroes. The most complicated part of such sparse Cholesky factorization relates to fill-in, i.e., zeroes in the original matrix that become nonzeroes in the factor L. An efficient implementation depends to a large extent on complex data structures and on techniques from graph theory to reduce, identify, and manage fill. DSCPACK is based on an efficient multifrontal implementation with fill-managing algorithms and implementation arising from earlier research by Raghavan and others. Sparse Cholesky factorization is typically a four step process: (1) ordering to compute a fill-reducing numbering, (2) symbolic factorization to determine the nonzero structure of L, (3) numeric factorization to compute L, and, (4) triangular solution to solve L(T)x = y and Ly = b. The first two steps are symbolic and are performed using the graph of the matrix. The numeric factorization step is of dominant cost and there are several schemes for improving performance by exploiting the nested and dense structure of groups of columns in the factor. The latter are aimed at better utilization of the cache-memory hierarchy on modem processors to prevent cache-misses and provide execution rates (operations/second) that are close to the peak rates for dense matrix computations. Currently, EPISCOPACY is being used in an application at NASA directed by J. Newman and M. James. We propose the implementation of efficient schemes for updating the LL(T) or LDL(T) factors computed in DSCPACK-S to meet the computational requirements of their project. A brief description is provided in the next section.

Raghavan, Padma↗
NASA NTRS2007

[Interview Questions]

The Goddard Mission Services Evolution Center, or GMSEC, was started in 2001 to create a new standard approach for managing GSFC missions. Standardized approaches in the past involved selecting and then integrating the most appropriate set of functional tools. Assumptions were made that "one size fits all" and that tool changes would not be necessary for many years. GMSEC took a very different approach and has proven to be very successful. The core of the GMSEC architecture consists of a publish/subscribe message bus, standardized message formats, and an Applications Programming Interface (API). The API supports multiple operating systems, programming languages and messaging middleware products. We use a GMSEC-developed free middleware for low-cost development. A high capacity, robust middleware is used for operations and a messaging system with a very small memory footprint is used for on-board flight software. Software components can use the standard message formats or develop adapters to convert from their native formats to the GMSEC formats. We do not want vendors to modify their core products. Over 50 software components are now available for use with the GMSEC architecture. Most available commercial telemetry and command systems, including the GMV hifly Satellite Control System, have been adapted to run in the GMSEC labs.

Smith, Dan↗
NASA NTRS2011

NASA Tech Briefs, September 2011

Topics covered include: Fused Reality for Enhanced Flight Test Capabilities; Thermography to Inspect Insulation of Large Cryogenic Tanks; Crush Test Abuse Stand; Test Generator for MATLAB Simulations; Dynamic Monitoring of Cleanroom Fallout Using an Air Particle Counter; Enhancement to Non-Contacting Stress Measurement of Blade Vibration Frequency; Positively Verifying Mating of Previously Unverifiable Flight Connectors; Radiation-Tolerant Intelligent Memory Stack - RTIMS; Ultra-Low-Dropout Linear Regulator; Excitation of a Parallel Plate Waveguide by an Array of Rectangular Waveguides; FPGA for Power Control of MSL Avionics; UAVSAR Active Electronically Scanned Array; Lockout/Tagout (LOTO) Simulator; Silicon Carbide Mounts for Fabry-Perot Interferometers; Measuring the In-Process Figure, Final Prescription, and System Alignment of Large; Optics and Segmented Mirrors Using Lidar Metrology; Fiber-Reinforced Reactive Nano-Epoxy Composites; Polymerization Initiated at the Sidewalls of Carbon Nanotubes; Metal-Matrix/Hollow-Ceramic-Sphere Composites; Piezoelectrically Enhanced Photocathodes; Iridium-Doped Ruthenium Oxide Catalyst for Oxygen Evolution; Improved Mo-Re VPS Alloys for High-Temperature Uses; Data Service Provider Cost Estimation Tool; Hybrid Power Management-Based Vehicle Architecture; Force Limit System; Levitated Duct Fan (LDF) Aircraft Auxiliary Generator; Compact, Two-Sided Structural Cold Plate Configuration; AN Fitting Reconditioning Tool; Active Response Gravity Offload System; Method and Apparatus for Forming Nanodroplets; Rapid Detection of the Varicella Zoster Virus in Saliva; Improved Devices for Collecting Sweat for Chemical Analysis; Phase-Controlled Magnetic Mirror for Wavefront Correction; and Frame-Transfer Gating Raman Spectroscopy for Time-Resolved Multiscalar Combustion Diagnostics.

Source record↗
NASA NTRS1990

Galileo spacecraft power management and distribution system

The Galileo PMAD (power management and distribution system) is described, and the design drivers that established the final as-built hardware are discussed. The spacecraft is powered by two general-purpose heat-source-radioisotope thermoelectric generators. Power bus regulation is provided by a shunt regulator. Galileo PMAD distributes a 570-W beginning of mission (BOM) power source to a user complement of some 137 load elements. Extensive use of pyrotechnics requires two pyro switching subassemblies. They initiate 148 squibs which operate the 47 pyro devices on the spacecraft. Detection and correction of faults in the Galileo PMAD is an autonomous feature dictated by requirements for long life and reliability in the absence of ground-based support. Volatile computer memories in the spacecraft command and data system and attitude control system require a continuous source of backup power during all anticipated power bus fault scenarios. Power for the Jupiter Probe is conditioned, isolated, and controlled by a Probe interface subassembly. Flight performance of the spacecraft and the PMAD has been successful to date, with no major anomalies.

Detwiler, R. C.↗
NASA NTRS1996

Report on Alternative Devices to Pyrotechnics on Spacecraft

Pyrotechnics accomplish many functions on today's spacecraft, possessing minimum volume/weight, providing instantaneous operation on demand, and requiring little input energy. However, functional shock, safety, and overall system cost issues, combined with emergence and availability of new technologies question their continued use on space missions. Upon request from the National Aeronautics and Space Administration's (NASA) Program Management Council (PMC), Langley Research Center (LaRC) conducted a survey to identify and evaluate state-of-the-art non-explosively actuated (NEA) alternatives to pyrotechnics, identify NEA devices planned for NASA use, and investigate potential interagency cooperative efforts. In this study, over 135 organizations were contacted, including NASA field centers, Department of Defense (DOD) and other government laboratories, universities, and American and European industrial sources resulting in further detailed discussions with over half, and 18 face-to-face briefings. Unlike their single use pyrotechnic predecessors, NEA mechanisms are typically reusable or refurbishable, allowing flight of actual tested units. NEAs surveyed include spool-based devices, thermal knife, Fast Acting Shockless Separation Nut (FASSN), paraffin actuators, and shape memory alloy (SMA) devices (e.g., Frangibolt). The electro-mechanical spool, paraffin actuator and thermal knife are mature, flight proven technologies, while SMA devices have a limited flight history. There is a relationship between shock, input energy requirements, and mechanism functioning rate. Some devices (e.g., Frangibolt and spool based mechanisms) produce significant levels of functional shock. Paraffin, thermal knife, and SMA devices can provide gentle, shock-free release but cannot perform critically timed, simultaneous functions. The FASSN flywheel-nut release device possesses significant potential for reducing functional shock while activating nearly instantaneously. Specific study recommendations include: (1) development of NEA standards, specifically in areas of material characterization, functioning rates, and test methods; (2) a systems level approach to assure successful NEA technology application; and (3) further investigations into user needs, along with industry/government system-level real spacecraft cost benefit trade studies to determine NEA application foci and performance requirements. Additional survey observations reveal an industry and government desire to establish partnerships to investigate remaining unknowns and formulate NEA standards, specifically those driven by SMAs. Finally, there is increased interest and need to investigate alternative devices for such functions as stage/shroud separation and high pressure valving. This paper summarizes results of the NASA-LaRC survey of pyrotechnic alternatives. State of-the-art devices with their associated weight and cost savings are presented. Additionally, a comparison of functional shock characteristics of several devices are shown, and potentially related technology developments are highlighted.

Lucy, M. H.↗
NASA NTRS2006

Advanced Health Management System for the Space Shuttle Main Engine

Pratt & Whitney Rocketdyne, Inc., in cooperation with NASA-Marshall Space Flight Center (MSFC), has developed a new Advanced Health Management System (AHMS) controller for the Space Shuttle Main Engine (SSME) that will increase the probability of successfully placing the shuttle into the intended orbit and increase the safety of the Space Transportation System (STS) launches. The AHMS is an upgrade o the current Block II engine controller whose primary component is an improved vibration monitoring system called the Real-Time Vibration Monitoring System (RTVMS) that can effectively and reliably monitor the state of the high pressure turbomachinery and provide engine protection through a new synchronous vibration redline which enables engine shutdown if the vibration exceeds predetermined thresholds. The introduction of this system required improvements and modification to the Block II controller such as redesigning the Digital Computer Unit (DCU) memory and the Flight Accelerometer Safety Cut-Off System (FASCOS) circuitry, eliminating the existing memory retention batteries, installation of the Digital Signal Processor (DSP) technology, and installation of a High Speed Serial Interface (HSSI) with accompanying outside world connectors. Test stand hot-fire testing along with lab testing have verified successful implementation and is expected to reduce the probability of catastrophic engine failures during the shuttle ascent phase and improve safely by about 23% according to the Quantitative Risk Assessment System (QRAS), leading to a safer and more reliable SSME.

Davidson, Matt↗
NASA NTRS2004

Accessing FMS Functionality: The Impact of Design on Learning

In modern commercial and military aircraft, the Flight Management System (FMS) lies at the heart of the functionality of the airplane. The nature of the FMS has also caused great difficulties learning and accessing this functionality. This study examines actual Air Force pilots who were qualified on the newly introduced advanced FMS and shows that the design of the system itself is a primary source of difficulty learning the system. Twenty representative tasks were selected which the pilots could be expected to accomplish on an ' actual flight. These tasks were analyzed using the RAFIV stage model (Sherry, Polson, et al. 2002). This analysis demonstrates that a great burden is placed on remembering complex reformulation of the task to function mapping. 65% of the tasks required retaining one access steps in memory to accomplish the task, 20% required two memorized access steps, and 15% required zero memorized access steps. The probability that a participant would make an access error on the tasks was: two memorized access steps - 74%, one memorized access step - 13%, and zero memorized access steps - 6%. Other factors were analyzed as well, including experience with the system and frequency of use. This completed the picture of a system with many memorized steps causing difficulty with the new system, especially when trying to fine where to access the correct function.

Fennell, Karl↗
NASA NTRS1993

RAID 7 disk array

Each RAID level reflects a different design architecture. Associated with each is a backdrop of imposed limitations, as well as possibilities which may be exploited within the architectural constraints of that level. There are three unique features that differentiate RAID 7 from all other levels. RAID 7 is asynchronous with respect to usage of I/O data paths. Each I/O drive (includes all data and one parity drives) as well as each host interface (there may be multiple host interfaces) has independent control and data paths. This means that each can be accessed completely, independently, of the other. This is facilitated by a separate device cache for each device/interface as well. RAID 7 is asynchronous with respect to device hierarchy and data bus utilization. Each drive and each interface is connected to a high speed data bus controlled by the embedded operating system to make independent transfers to and from central cache. RAID 7 is asynchronous with respect to the operation of an embedded real time process oriented operating system. This means that exclusive and independent of the host, or multiple host paths, the embedded OS manages all I/O transfers asynchronously across the data and parity drives. A key factor to consider is that of the RAID 7's ability to anticipate and match host I/O usage patterns. This yields the following benefits over RAID's built around micro-code based architectures. RAID 7 appears to the host as a normally connected Big Fast Disk (BFD). RAID 7 appears, from the perspective of the individual disk devices, to minimize the total number of accesses and optimize read/write transfer requests. RAID 7 smoothly integrates the random demands of independent users with the principles of spatial and temporal locality. This optimizes small, large, and time sequenced I/O requests which results in users having an I/O performance which approaches performance to that of main memory.

Stout, Lloyd↗
NASA NTRS2014

Coupling Damage-Sensing Particles to the Digitial Twin Concept

The research presented herein is a first step toward integrating two emerging structural health management paradigms: digital twin and sensory materials. Digital twin is an emerging life management and certification paradigm whereby models and simulations consist of as-built vehicle state, as-experienced loads and environments, and other vehicle-specific history to enable high-fidelity modeling of individual aerospace vehicles throughout their service lives. The digital twin concept spans many disciplines, and an extensive study on the full domain is out of the scope of this study. Therefore, as it pertains to the digital twin, this research focused on one major concept: modeling specifically the as-manufactured geometry of a component and its microstructure (to the degree possible). The second aspect of this research was to develop the concept of sensory materials such that they can be employed within the digital twin framework. Sensory materials are shape-memory alloys that undergo an audible phase transformation while experiencing sufficient strain. Upon embedding sensory materials with a structural alloy, this audible transformation helps improve the reliability of crack detection especially at the early stages of crack growth. By combining these two early-stage technologies, an automated approach to evidence-based inspection and maintenance of aerospace vehicles is sought.

Hochhalter, Jacob↗
NASA NTRS2024

Evaluation of Machine Learning and Deep Learning Algorithms for Fire Prediction in Southeast Asia

Vegetation fires are prevalent in South/Southeast Asian countries, making fire prediction crucial due to their potential environmental, economic, and social impacts. Accurate predictions of fires facilitate timely interventions, helping to mitigate uncontrolled fires that can lead to biodiversity loss and air quality issues. In this study, we utilize VIIRS satellite-derived fire data alongside six machine learning and deep learning models—Simple Persistence, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), CNN-LSTM, and ConvLSTM—to determine the most effective fire prediction model, using Root Mean Square Error (RMSE) as the metric. Our results indicate that the CNN model is the most reliable in regions with spatial dependencies, such as Brunei, Indonesia, Malaysia, the Philippines, Timor-Leste, and Thailand. Conversely, the ConvLSTM model excels in countries with complex spatiotemporal dynamics like Laos, Myanmar, and Vietnam. The CNN-LSTM hybrid model also performed well in Cambodia, suggesting a need for a balanced approach in areas requiring both spatial and temporal feature extraction. Furthermore, simpler models like Persistence and MLP showed limitations in capturing dynamic patterns and temporal dependencies. Our findings highlight the importance of evaluating models before implementing any decision support systems (DSS) in fire management. By tailoring models to specific regional fire data, we can enhance prediction accuracy and responsiveness, ultimately improving fire risk management in Southeast Asia and beyond.

Deep learning↗
NASA NTRS2020

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term. The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗
NASA NTRS2020

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission TRMM Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗
NASA NTRS1998

The mass storage testing laboratory at GSFC

Industry-wide benchmarks exist for measuring the performance of processors (SPECmarks), and of database systems (Transaction Processing Council). Despite storage having become the dominant item in computing and IT (Information Technology) budgets, no such common benchmark is available in the mass storage field. Vendors and consultants provide services and tools for capacity planning and sizing, but these do not account for the complete set of metrics needed in today's archives. The availability of automated tape libraries, high-capacity RAID systems, and high- bandwidth interconnectivity between processor and peripherals has led to demands for services which traditional file systems cannot provide. File Storage and Management Systems (FSMS), which began to be marketed in the late 80's, have helped to some extent with large tape libraries, but their use has introduced additional parameters affecting performance. The aim of the Mass Storage Test Laboratory (MSTL) at Goddard Space Flight Center is to develop a test suite that includes not only a comprehensive check list to document a mass storage environment but also benchmark code. Benchmark code is being tested which will provide measurements for both baseline systems, i.e. applications interacting with peripherals through the operating system services, and for combinations involving an FSMS. The benchmarks are written in C, and are easily portable. They are initially being aimed at the UNIX Open Systems world. Measurements are being made using a Sun Ultra 170 Sparc with 256MB memory running Solaris 2.5.1 with the following configuration: 4mm tape stacker on SCSI 2 Fast/Wide; 4GB disk device on SCSI 2 Fast/Wide; and Sony Petaserve on Fast/Wide differential SCSI 2.

Venkataraman, Ravi↗
NASA NTRS1997

A Comparison of PETSC Library and HPF Implementations of an Archetypal PDE Computation

Two paradigms for distributed-memory parallel computation that free the application programmer from the details of message passing are compared for an archetypal structured scientific computation a nonlinear, structured-grid partial differential equation boundary value problem using the same algorithm on the same hardware. Both paradigms, parallel libraries represented by Argonne's PETSC, and parallel languages represented by the Portland Group's HPF, are found to be easy to use for this problem class, and both are reasonably effective in exploiting concurrency after a short learning curve. The level of involvement required by the application programmer under either paradigm includes specification of the data partitioning (corresponding to a geometrically simple decomposition of the domain of the PDE). Programming in SPAM style for the PETSC library requires writing the routines that discretize the PDE and its Jacobian, managing subdomain-to-processor mappings (affine global- to-local index mappings), and interfacing to library solver routines. Programming for HPF requires a complete sequential implementation of the same algorithm, introducing concurrency through subdomain blocking (an effort similar to the index mapping), and modest experimentation with rewriting loops to elucidate to the compiler the latent concurrency. Correctness and scalability are cross-validated on up to 32 nodes of an IBM SP2.

Hayder, M. Ehtesham↗
NASA NTRS2019

Using Big Data Technologies with Earth Science Data in HDF5: HDF5 Scalable Solutions

HDF5 (Hierarchical Data Format 5) is open-source, high-performance software that consists of an abstract data model, library, and fileformat used for storing and managing extremely large and/or complex data collections. NASA Earth Observing System (EOS) Data and Information Systems use HDF5 as an archival format to store remote sensing data from EOS satellites. HDF5 is also used to store other types of Geoscience and Strophysical data, e.g., seismic data and data from Low-Frequency Array (LOFAR) radio telescopes. Data stored in HDF5 has reached tens of petabytes and is growing at an accelerated rate.With the growing amout of HDF5 Earth Science data to analyze and process, scientists need to adopt big data technologies including new storage paradigms such as cloud and object storage. To run models and perform data analysis they also need to utilizied efficient and diverse ways to access data, from high-performance computing's (HPC) Message Passing Interface (MPI) I/O and deep memory hierarchies (DMH) to non-HPC frameworks such as Apache Hadoop, Spark, and Drill. The HDF Group continually works to enable usage of big data technologies in HDF software.

Knox, Larry↗