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At least 343 records · Page 19

Particle simulation in a multiprocessor environment

A parallel implementation of a particle simulation method that is portable between a wide class of multiprocessor computers is presented. A fine grain spatial decomposition is utilized where several subdomains having a regular structure are computed at each processing node. This leads directly to an efficient and straightforward load balancing scheme if the number of subdomains at each processor is permitted to vary in an appropriate manner. Three dimensional simulations incorporating full thermochemical nonequilibrium are possible using the resulting code. Vectorizable algorithms are retained from earlier work allowing efficient use of deeply pipelined node processors where available. Performance results are presented from three different machine architectures demonstrating the portability of the code. On a 128-node Intel iPSC/860, performance is twice that of a single Cray-Y/MP CPU running a highly vectorized simulation code. Speedup is linear over the full range of number of processors on all target machines, indicating scalability of the method to higher degrees of parallelism.

Mcdonald, Jeffrey D.↗

A Detect and Avoid System in the Context of Multiple-Unmanned Aircraft Systems Operations

NASA's Unmanned Aircraft Systems Integration into the National Airspace System (UAS in the NAS) project examines the technical barriers associated with the operation of UAS in civil airspace. For UAS, the removal of the pilot from onboard the aircraft has eliminated the ability of the ground-based pilot in command (PIC) to use out-the-window visual information to make judgements about a potential threat of a loss of well clear with another aircraft. NASA's Phase 1 research supported the development of a Detect and Avoid (DAA) system that supports the ground-based pilot's ability to detect potential traffic conflicts and determine a resolution maneuver, but existing display/alerting requirements did not account for multiple UAS control (1:N). Demands for increased scalability of UAS in the NAS operations are expected to create a need for simultaneous control of UAs, and thus, a new DAA HMI design will likely be necessary. Previous research, however, has found performance degradations as the number of vehicles under operator control has increased. The purpose of the current human-in-the-loop (HITL) simulation was to examine the viability of 1:N operations with the Phase 1 DAA alerting and guidance. Sixteen UAS pilots flew three scenarios with varying number of UAs under their control (1:1, 1:3, 1:5). In addition to their supervisory and sensor mission responsibilities, pilots were to utilize the DAA system to remain DAA well clear (DWC) during scripted conflicts of mixed severity. Measured response times, separation performance, mission task data, and subjective feedback were collected to assess how the multi-UAS control configuration impacted pilots' ability to maintain DAA well clear and perform the mission tasks. Overall, the DAA system proved surprisingly adaptive to multi-UAS control for preventing losses of DAA well clear (LoDWC). The findings suggest that, while multi-UAS operators are able to maintain safe separation (DWC) from other traffic, their ability to efficiently perform missions drastically decreases with their number of controlled vehicles. Pilot feedback indicated that, for this context, the use of automation support tools for completing and managing mission tasks would be appropriate and desired, especially for ensuring efficient use of assets. Finally, human-machine interface (HMI) design considerations for multi-UAS operations are discussed.

Monk, Kevin J.↗

Parallel Conjugate Gradient: Effects of Ordering Strategies, Programming Paradigms, and Architectural Platforms

The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse linear systems that are symmetric and positive definite. A sparse matrix-vector multiply (SPMV) usually accounts for most of the floating-point operations within a CG iteration. In this paper, we investigate the effects of various ordering and partitioning strategies on the performance of parallel CG and SPMV using different programming paradigms and architectures. Results show that for this class of applications, ordering significantly improves overall performance, that cache reuse may be more important than reducing communication, and that it is possible to achieve message passing performance using shared memory constructs through careful data ordering and distribution. However, a multi-threaded implementation of CG on the Tera MTA does not require special ordering or partitioning to obtain high efficiency and scalability.

Oliker, Leonid↗

Technology Advancement for Active Remote Sensing of Carbon Dioxide from Space Using the ASCENDS CarbonHawk Experiment Simulator: First Results

The ASCENDS CarbonHawk Experiment Simulator (ACES) is a newly developed lidar developed at NASA Langley Research Center and funded by NASA's Earth Science Technology Office (ESTO) Instrument Incubator Program (IIP) that seeks to advance technologies critical to measuring atmospheric column carbon dioxide (CO2) mixing ratios in support of the NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission. The technology advancements targeted include: (1) increasing the power-aperture product to approach ASCENDS mission requirements by implementing multi-aperture telescopes and multiple co-aligned laser transmitters; (2) incorporating high-efficiency, high-power Erbium-Doped Fiber Amplifiers (EDFAs); (3) developing and incorporating a high-bandwidth, low-noise HgCdTe detector and transimpedence amplifier (TIA) subsystem capable of long-duration autonomous operation on Global Hawk aircraft, and (4) advancing algorithms for cloud and aerosol discrimination. The ACES instrument architecture is being developed for operation on high-altitude aircraft and will be directly scalable to meet the ASCENDS mission requirements. These technologies are critical towards developing not only spaceborne instruments but also their airborne simulators, with lower platform requirements for size, mass, and power, and with improved instrument performance for the ASCENDS mission. ACES transmits five laser beams: three from commercial EDFAs operating near 1.57 microns, and two from the Exelis oxygen (O2) Raman fiber laser amplifier system operating near 1.26 microns. The three EDFAs are capable of transmitting up to 10 watts average optical output power each and are seeded by compact, low noise, stable, narrow-linewidth laser sources stabilized with respect to a CO2 absorption line using a multi-pass gas absorption cell. The Integrated-Path Differential Absorption (IPDA) lidar approach is used at both wavelengths to independently measure the CO2 and O2 column number densities and retrieve the average column CO2 mixing ratio. The ACES receiver uses three fiber-coupled 17.8-cm diameter athermal telescopes. The transmitter assembly consists of five fiber-coupled laser collimators and an associated Risley prism pair for each laser to co-align the outgoing laser beams and to align them with the telescope field of view. The backscattered return signals collected by the three telescopes are combined in a fiber bundle and sent to a single low noise detector. The detector/TIA development has improved the existing detector subsystem by increasing its bandwidth to 4.7 MHz from 500 kHz and increasing the duration of autonomous, service-free operation periods from 4 hours to >24 hours. The new detector subsystem enables the utilization of higher laser modulation rates, which provides greater flexibility for implementing advanced thin-cloud discrimination algorithms as well as improving range-determination resolution and error reduction. The cloud/aerosol discrimination algorithm development by Langley and Exelis features a new suite of algorithms for the minimization/elimination of bias errors in the return signal induced by the presence of intervening thin clouds. Multiple laser modulation schemes are being tested in an effort to significantly mitigate the effects of thin clouds on the retrieved CO2 column amounts. Full instrument development concluded in the spring of 2014. After ground range tests of the instrument, ACES successfully completed six test flights on the Langley Hu-25 aircraft in July, 2014, and recorded data at multiple altitudes over land and ocean surfaces with and without intervening clouds. Preliminary results from these test flights will be presented in this paper.

Obland, Michael D.↗

Structural Design Exploration of an Electric Powered Multi-Propulsor Wing Configuration

Advancements in aircraft electric propulsion may enable an expanded operational envelope for electrically powered vehicles compared to their internal combustion engine counterparts. High aspect ratio wings provide additional lift and drag reduction for a proposed multi-propulsor design, however, the challenge is to reduce the weight of wing structures while maintaining adequate structural and aeroelastic margins. Design exploration using a conventional design-and-build philosophy coupled with a finite element method (FEM)-based design of experiments (DOE) strategy are presented to examine high aspect ratio wing structures that have spanwise distributed electric motors. Multiple leading-edge-mounted engine masses presented a challenge to design a wing within acceptable limits for dynamic and aeroelastic stability. Because the first four primary bending eigenmodes of the proposed wing structure are very sensitive to outboard motor placement, safety-of-flight requirements drove the need for multiple spars, rib attachments, and outboard structural reinforcements in the design. Global aeroelasticity became an increasingly important design constraint during the on-going design process, with outboard motor pod flutter ultimately becoming a primary design constraint. Designers successively generated models to examine stress, dynamics, and aeroelasticity concurrently. This research specifically addressed satisfying multi-disciplinary design criteria to generate fluid-structure interaction solution sets, and produced high aspect ratio primary structure designs for the NASA Scalable Convergent Electric Propulsion Technology and Operations Research (SCEPTOR) project in the Aeronautic Research Mission Directorate at NASA. In this paper, a dynamics-driven, quasi-inverse design methodology is presented to address aerodynamic performance goals and structural challenges encountered for the SCEPTOR demonstrator vehicle. These results are compared with a traditional computer aided design based approach.

Moore, James B.↗

Development of a High-Propellant Throughput Small Spacecraft Electric Propulsion System to Enable Lower Cost NASA Science Missions

This paper describes recent progress at the NASA Glenn Research Center (GRC) in the development and demonstration of an integrated high-propellant throughput small spacecraft electric propulsion (HT-SSEP) system based on a Hall-effect thruster. A center-mounted cathode and an innovative magnetic circuit topology were implemented in the design of the Hall-effect thruster to achieve high-propellant throughput, high performance, and efficient packaging. To minimize technical risk, the HT-SSEP development approach sought to limit design features and materials to those with a clear path-to-flight. A propellant throughput capability of greater than 100 kg at a minimum thruster efficiency of 50% was targeted. The proof-of-concept NASA-H64M laboratory model (LM) thruster was designed, fabricated, and tested at GRC in fiscal year 2018. The thruster development leveraged heritage Hall-effect thruster design and manufacturing processes wherever appropriate. Recent NASA advances in Hall-effect thruster technology were also leveraged. A scalable discharge power supply (DPS) capable of powering the H64M-LM was developed, then demonstrated as part of an integrated system test. The DPS uses commercial off-the-shelf components with spaceflight equivalents. A keeper supply with DC ignitor was breadboarded, then demonstrated with a laboratory cathode. Finally, feed system trade studies were performed to ascertain what feed system architecture might be appropriate for an HT-SSEP system. This paper details the motivations for the project, the development approach, the chosen sub-system architectures, design considerations, and test results.

Benavides, Gabriel F.↗

Development of a High-Propellant Throughput Small Spacecraft Electric Propulsion System to Enable Lower Cost NASA Science Missions

This paper describes recent progress at the NASA Glenn Research Center (GRC) in the development and demonstration of an integrated high-propellant throughput small spacecraft electric propulsion (HT-SSEP) system based on a Hall-effect thruster. A center-mounted cathode and an innovative magnetic circuit topology were implemented in the design of the Hall-effect thruster to achieve high-propellant throughput, high performance, and efficient packaging. To minimize technical risk, the HT-SSEP development approach sought to limit design features and materials to those with a clear path-to-flight. A propellant throughput capability of greater than 100 kg at a minimum thruster efficiency of 50% was targeted. The proof-of-concept NASA-H64M laboratory model (LM) thruster was designed, fabricated, and tested at GRC in fiscal year 2018. The thruster development leveraged heritage Hall-effect thruster design and manufacturing processes wherever appropriate. Recent NASA advances in Hall-effect thruster technology were also leveraged. A scalable discharge power supply (DPS) capable of powering the H64M-LM was developed, then demonstrated as part of an integrated system test. The DPS uses commercial off-the-shelf components with spaceflight equivalents. A keeper supply with DC ignitor was breadboarded, then demonstrated with a laboratory cathode. Finally, feed system trade studies were performed to ascertain what feed system architecture might be appropriate for an HT-SSEP system. This paper details the motivations for the project, the development approach, the chosen sub-system architectures, design considerations, and test results.

Benavides, Gabriel F.↗

Development of a High-Propellant Throughput Small Spacecraft Electric Propulsion System (HT-SSEP) to Enable Lower Cost NASA Science Missions

Discusses progress at the NASA Glenn Research Center (GRC) in the development and demonstration of an integrated high-propellant throughput small spacecraft electric propulsion (HT-SSEP) system based on a Hall-effect thruster. A center-mounted cathode and an innovative magnetic circuit topology were implemented in the design of the Hall-effect thruster to achieve high-propellant throughput, high performance, and efficient packaging. To minimize technical risk, the HT-SSEP development approach sought to limit design features and materials to those with a clear path-to-flight. A propellant throughput capability of greater than 100 kilograms at a minimum thruster efficiency of 50 percent was targeted. The proof-of-concept NASA-H64M laboratory model (LM) thruster was designed, fabricated, and tested at GRC in fiscal year 2018. The thruster development leveraged heritage Hall-effect thruster design and manufacturing processes wherever appropriate. Recent NASA advances in Hall-effect thruster technology were also leveraged. A scalable discharge power supply (DPS) capable of powering the H64M-LM was developed, then demonstrated as part of an integrated system test. The DPS uses commercial off-the-shelf components with spaceflight equivalents. A keeper supply with DC ignitor was breadboarded, then demonstrated with a laboratory cathode. Finally, feed system trade studies were performed to ascertain what feed system architecture might be appropriate for an HT-SSEP system. This paper details the motivations for the project, the development approach, the chosen sub-system architectures, design considerations, and test results.

Benavides, Gabriel↗

Optimization of Elastodynamic Finite Integration Technique on Intel Xeon Phi Knights Landing Processors

This work describes the development and optimization of an implementation of an isotropic elastodynamic finite integration technique (EFIT) code for parallelized computation on Intel Knights Landing (KNL) hardware. EFIT is a numerical approach resulting in standard staggered-grid finite difference equations for the elastodynamic equations of motion to simulate bulk waves is solids. The computationally efficient simulation of elastodynamic wave propagation and interactions in aerospace materials is of high-interest in the fields of nondestructive evaluation (NDE) and structural health monitoring (SHM). Ultrasonic inspection uses an ultrasonic signal, generated at the surface of the material/structure via use of a piezoelectric transducer, to propagate sound waves into the material where it interacts with any existing defects, as well as with structural boundaries and any material inhomogeneity. Reflections from defects and boundaries are then measured by a transducer. Realistic ultrasound simulation tools can significantly aid the development and optimization of inspection techniques and can assist in the interpretation of experimental data. The optimization of an elastodynamics simulation code for the KNL Many Integrated Core processor was performed. The optimization focused on data locality and vectorization. Results show that tiling of the data to exploit the cache behavior and allow for significant utilization of the KNL hardware. The MPI implementation allows for a scalable implementation enabling large problems to be simulated. The model results were validated against theoretical dispersion curves to within 2% of the group velocity, and within 0.5% of the phase velocity of the A0 mode. Aggressive use of tiling, threading, and vectorization techniques allowed for dramatically improved time to solution.

William C. Schneck↗

Human-Autonomy Teaming Research in Support of m:N Operations

Since 2019, the NASA and industry partners have been involved in research focused on a novel paradigm for operations of remotely piloted aircraft. This paradigm involves multiple people sharing a fleet of multiple vehicles between them. Referred to as m:N (pronounced “em-to-en”), this configuration describes a ratio where m is the number of operators and N is the number of vehicles. Through force and asset multiplication, the m:N concept seeks to enable a scalable and resilient operation of remotely crewed vehicles. The primary means of obtaining such a robust operation is through allowing a flexible crew of variable size to dynamically attend to the needs of assets in while performing real-time operator workload management. It is in that sense that assets are shared between operators: as needed (such as in events of elevated workload) an operator in an m:N context can “handoff” the responsibility for some amount of assets, nh < N, to be absorbed by the m – 1 crew members on staff. At some time later, these nh assets could be returned to their original owner or they may be further distributed to other crew if called for by the mission. During this panel, I will elaborate on the research activity undertaken by the Human-Autonomy Teaming (HAT) Laboratory at NASA Ames Research Center over the previous three years. The studies conducted by the HAT Lab range from interviews with subject matter experts, a cognitive walkthrough, a task analysis, and two simulation experiments to-date. During experimentation, pilots made use of an advanced Ground Control Station developed by the HAT Lab and industry partners to simulate m:N operations in two large, metropolitan areas of Southern California: Los Angeles and San Diego. Further experimentation planned over the next few years. Results from our research to-date indicates that pilots of a moderately sized fleet of about a dozen remotely crewed aircraft adequately maintained safety performance and situation awareness of their aircraft, even when presented with unexpected situations of heightened workload.

multi-vehicle control↗

Interactive Display of Scenes with Annotations

ThreeDView is a computer program that enables high-performance interactive display of real-world scenes with annotations. ThreeDView was developed primarily as a component of the Science Activity Planner (SAP) software, wherein it is to be used to display annotated images of terrain acquired by exploratory robots on Mars and possibly other remote planets. The images can be generated from sets of multiple-texture image data in the Visible Scalable Terrain (ViSTa) format, which was described in "Format for Interchange and Display of 3D Terrain Data" (NPO-30600) NASA Tech Briefs, Vol. 28, No. 12 (December 2004), page 25. In ThreeDView, terrain data can be loaded rapidly, the geometric level of detail and texture resolution can be selected, false colors can be used to represent scientific data mapped onto terrain, and the user can select among navigation modes. ThreeDView consists largely of modular Java software components that can easily be reused and extended to produce new high-performance, application-specific software systems for displaying images of three-dimensional real-world scenes.

Vona, Marsette↗

Networked Array Recorder (NeAR) Microphones for Field-Deployed Phased Arrays

An innovative edge-computing concept known as NeAR (Networked Array Recorder) has been developed to provide enhancements to existing field-deployable microphone phased arrays utilized for aeroacoustic flyover measurements of airframe and propulsive noise sources. The proposed system allows for the elimination of multiple miles of sensor wiring in an array installation, thereby improving the scalability of the overall system, increasing the fault-tolerance of the hardware, and reducing the effort needed to build-up and tear-down an array in the field. A demonstration of the NeAR concept was performed at Edwards Air Force Base in California in March – April, 2018, where twelve individual NeAR microphones were deployed as a piggyback on a conventional phased array system deployed for airframe noise flyover testing. The microphones operated successfully during the demonstration with good time history and spectral correlations shown between the NeAR units and conventional microphones located nearby in the array. The NeAR concept has spinoffs beyond its use for phased arrays, including applications in remote environmental sensing and noise monitoring.

Cull.iton, William G.↗

AI-Enhanced Computational Tools for Entry Systems Modeling

To advance the understanding of complex atmospheric entry phenomena, NASA’s Entry Systems Modeling (ESM) team [1] has developed high-fidelity computational tools addressing multiscale challenges, from material microstructures to full-scale heatshield response. This abstract highlights a subset of ESM tools, focusing on AI integration to enhance workflows and predictive modeling. - PuMA [2] computes effective material properties from high-resolution micro-CT scans, supporting TPS analysis for NASA missions. - TomoSAM [3] automates 3D tomography dataset segmentation for PuMA using the Segment Anything Model, reducing manual effort and improving accuracy. - PATO [4] models porous reactive materials under extreme conditions, with advancements such as unified solvers, mechanical erosion, and TPS coatings for NASA missions. - arcjetCV [5] employs deep learning to analyze arc jet test footage, measuring recession rates, shape changes, and shock standoff distances, bridging simulations, and experiments to reveal TPS ablation behavior. - ARCHeS [6] simulates arc heater plasma flows, modeling turbulence, radiation, and electromagnetic interactions to optimize arc heater performance, validate TPS under extreme conditions, and serve as a foundation for developing digital twins of arc heater facilities. - SPARTA [7] simulates rarefied hypersonic flows and gas-surface interactions for planetary entry missions, leveraging GPU architectures for scalable and efficient aerothermal and ablation analyses. AI-driven solutions, such as deep learning segmentation, have streamlined workflows in ESM tools and still hold significant potential to further accelerate processes and enhance automation in entry systems modeling. [1] Haskins, J.B. (2023), [2] Ferguson, J.C. (2018), [3] Meurisse, J.B.E. (2018), [4] Semeraro, F. (2023), [5] Quintart, A. (2024) [6] Meurisse, J.B.E. (2022), [7] Plimpton, S.J. (2019)

Predictive Modeling↗

A Scalable Nonuniform Pointer Analysis for Embedded Program

In this paper we present a scalable pointer analysis for embedded applications that is able to distinguish between instances of recursively defined data structures and elements of arrays. The main contribution consists of an efficient yet precise algorithm that can handle multithreaded programs. We first perform an inexpensive flow-sensitive analysis of each function in the program that generates semantic equations describing the effect of the function on the memory graph. These equations bear numerical constraints that describe nonuniform points-to relationships. We then iteratively solve these equations in order to obtain an abstract storage graph that describes the shape of data structures at every point of the program for all possible thread interleavings. We bring experimental evidence that this approach is tractable and precise for real-size embedded applications.

Venet, Arnaud↗

Autonomous Mission Manager for Rendezvous, Inspection and Mating

To meet cost and safety objectives, space missions that involve proximity operations between two vehicles require a high level of autonomy to successfully complete their missions. The need for autonomy is primarily driven by the need to conduct complex operations outside of communication windows, and the communication time delays inherent in space missions. Autonomy also supports the goals of both NASA and the DOD to make space operations more routine, and lower operational costs by reducing the requirement for ground personnel. NASA and the DoD have several programs underway that require a much higher level of autonomy for space vehicles. NASA's Space Launch Initiative (SLI) program has ambitious goals of reducing costs by a factor or 10 and improving safety by a factor of 100. DARPA has recently begun its Orbital Express to demonstrate key technologies to make satellite servicing routine. The Air Force's XSS-ll program is developing a protoflight demonstration of an autonomous satellite inspector. A common element in space operations for many NASA and DOD missions is the ability to rendezvous, inspect anclJor dock with another spacecraft. For DARPA, this is required to service or refuel military satellites. For the Air Force, this is required to inspect un-cooperative resident space objects. For NASA, this is needed to meet the primary SLI design reference mission of International Space Station re-supply. A common aspect for each of these programs is an Autonomous Mission Manager that provides highly autonomous planning, execution and monitoring of the rendezvous, inspection and docking operations. This paper provides an overview of the Autonomous Mission Manager (AMM) design being incorporated into many of these technology programs. This AMM provides a highly scalable level of autonomous operations, ranging from automatic execution of ground-derived plans to highly autonomous onboard planning to meet ground developed mission goals. The AMM provides the capability to automatically execute the plans and monitor the system performance. In the event of system dispersions or failures the AMM can modify plans or abort to assure overall system safety. This paper describes the design and functionality of Draper's AMM framework, presents concept of operations associated with the use of the AMM, and outlines the relevant features of the flight demonstrations.

Zimpfer, Douglas J.↗

Advanced Deployable Shell-Based Composite Booms for Small Satellite Structural Applications Including Solar Sails

State of the art deployable structures are mainly being designed for medium to large size satellites. The lack of reliable deployable structural systems for low cost, small volume, rideshare-class spacecraft severely constrains the potential for using small satellite platforms for affordable deep space science and exploration precursor missions that could be realized with solar sails. There is thus a need for reliable, lightweight, high packaging efficiency deployable booms that can serve as the supporting structure for a wide range of small satellite systems including solar sails for propulsion. The National Air and Space Administration (NASA) is currently investing in the development of a new class of advanced deployable shell-based composite booms to support future deep space small satellite missions using solar sails. The concepts are being designed to: meet the unique requirements of small satellites, maximize ground testability, permit the use of low-cost manufacturing processes that will benefit scalability, be scalable for use as elements of hierarchical structures (e.g. trusses), allow long duration storage, have high deployment reliability, and have controlled deployment behavior and predictable deployed dynamics. This paper will present the various rollable boom concepts that are being developed for 5-20 m class size deployable structures that include solar sails with the so-called High Strain Composites (HSC) materials. The deployable composite booms to be presented are being developed to expand the portfolio of available rollable booms for small satellites and maximize their length for a given packaged volume. Given that solar sails are a great example of volume and mass optimization, the booms were designed to comply with nominal solar sail system requirements for 6U CubeSats, which are a good compromise between those of smaller form factors (1U, 2U and 3U CubeSats) and larger ones (12 U and 27 U future CubeSats, and ESPA-class microsatellites). Solar sail missions for such composite boom systems are already under consideration and development at NASA, as well as mission studies that will benefit from planned scaled-up versions of the composite boom technologies to be introduced. The paper presents ongoing research and development of thin-shell rollable composite booms designed under the particular stringent and challenging system requirements of relatively large solar sails housed on small satellites. These requirements will be derived and listed. Several new boom concepts are proposed and other existing ones are improved upon using thin-ply composite materials to yield unprecedented compact deployable structures. Some of these booms are shown in Fig. 1. For every boom to be introduced the scalable fabrication process developed to keep the overall boom system cost down will be shown. Finally, the initial results of purposely designed boom structural characterization test methods with gravity off-loading will be presented to compare their structural performance under expected and general load cases.

Fernandez, Juan M.↗

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗

Airborne simulation of a satellite based Doppler lidar

Results of a study assessing the feasibility of a satellite-based Doppler lidar for global wind measurements are reported. In particular, attention is given to the feasibility of simulating such measurements from an airborne platform. A brief discussion of the proposed Doppler lidar system is presented along with a description of the computer simulation and airborne measurements. The measurements will be performed using a pulsed CO2 Doppler lidar in a scan configuration similar to that expected for the satellite system. Computer simulations will be used in addition to measurements to assess the accuracy of the scan technique and to determine the scalability of the measurements.

Bilbro, J. W.↗