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How to handle 6GBytes a night and not get swamped

The Macho Project has undertaken a 5 year effort to search for dark matter in the halo of the Galaxy by scanning the Magellanic Clouds for micro-lensing events. Each evening's raw image data will be reduced in real-time into the observed stars' photometric measurements. The actual search for micro-lensing events will be a post-processing operation. The theoretical prediction of the rate of such events necessitates the collection of a large number of repeated exposures. The project designed camera subsystem delivers 64 Mbytes per exposure with exposures typically occurring every 500 seconds. An ideal evening's observing will provide 6 Gbytes of raw image data and 40 Mbytes of reduced photometric measurements. Recognizing the difficulty of digging out from a snowballing cascade of raw data, the project requires the real-time reduction of each evening's data. The software team's implementation strategy centered on this non-negotiable mandate. Accepting the reality that 2 full time people needed to implement the core real-time control and data management system within 6 months, off-the-shelf vendor components were explored to provide quick solutions to the classic needs for file management, data management, and process control. Where vendor solutions were lacking, state-of-the-art models were used for hand tailored subsystems. In particular, petri nets manage process control, memory mapped bulletin boards provide interprocess communication between the multi-tasked processes, and C++ class libraries provide memory mapped, disk resident databases. The differences between the implementation strategy and the final implementation reality are presented. The necessity of validating vendor product claims are explored. Both the successful and hindsight decisions enabling the collection and processing of the nightly data barrage are reviewed.

Allsman, R.↗

The ALEXIS data processing package: An IDL based system

The Array of Low Energy X-ray Imaging Sensors (ALEXIS) experiment consists of a mini-satellite containing six wide angle EUV/ultrasoft x-ray telescopes. Its purpose is to map out the sky in three narrow (approximately 5 percent) bandpasses around 66, 71, and 93 eV. The 66 and 71 eV bandpasses are centered on intense Fe emission lines which are characteristic of million degree plasmas such as the one thought to produce the soft x-ray background. The 93 eV bandpass is not near any strong emission lines and is more sensitive to continuum sources. The mission will be launched on the Pegasus Air Launched Vehicle in the second half of 1992 into a 400-nautical-mile, high inclination orbit and will be controlled entirely from a small ground station located at Los Alamos. The project is a collaborative effort between Los Alamos National Laboratory, Sandia National Laboratory, and the University of California-Berkeley Space Sciences Laboratory. The six telescopes are arranged in three pairs. As the satellite spins twice a minute they scan the entire anti-solar hemisphere. Each f/1 telescope consists of a spherical, multilayer-coated mirror with a curved, microchannel plate detector located at the prime focus. The multilayer coatings determine the bandpasses of the telescopes. The field of view of each telescope is 30 degrees with a spatial resolution of 0.5 degree, limited by spherical aberration. The data processing requirements for ALEXIS are large. Each event is one of the six telescopes is telemetered to the ground with its time of arrival and position on the detector. This information must be folded with the aspect solution for the satellite to reconstruct the direction on the sky from which the photon came. Because of the way the six telescopes scan the sky, the effective exposure calculation is also very computationally intensive. ALEXIS may generate up to 100 megabytes of raw data per day, which are converted into a gigabyte per day of processed data. While the processing job for ALEXIS is sizable, the programming staff is small. To maximize programming efficiency, and to make the best use of tools available in the public domain, we chose IDL as our software development platform. IDL was used from the start of instrument development through flight. We use IDL as a top-level executive for the processing tasks (replacing Unix shell scripts), as a device independent graphics engine, as a database manager, and as a final data manipulator. IDL routines spawn special purpose C programs to perform detailed telemetry deconvolution and other specialized functions. We discuss the use of IDL and C within the processing and archiving strategy for the ALEXIS data anlaysis system as implemented on a SPARCstation platform. We also show results from our End-to-End software simulation capability as processed by our analysis codes.

Bloch, J. J.↗

Validation of automated payload experiment tool

The System Management and Production Laboratory, Research Institute, The University of Alabama in Huntsville (UAH), was tasked by the Microgravity Experiment Projects (MEP) Office of the Payload projects Office (PPO) at Marshall Space Flight Center (MSFC) to conduct research in the current methods of written documentation control and retrieval. The goals of this research were to determine the logical interrelationships within selected NASA documentation, and to expand on a previously developed prototype system to deliver a distributable, electronic knowledge-based system. This computer application would then be used to provide a 'paperless' interface between the appropriate parties for the required NASA documentation.

Maddux, Gary A.↗

Introduction of the Space Shuttle Columbia Accident, Investigation Details, Findings and Crew Survival Investigation Report

As the Space Shuttle Program comes to an end, it is important that the lessons learned from the Columbia accident be captured and understood by those who will be developing future aerospace programs and supporting current programs. Aeromedical lessons learned from the Accident were presented at AsMA in 2005. This Panel will update that information, closeout the lessons learned, provide additional information on the accident and provide suggestions for the future. To set the stage, an overview of the accident is required. The Space Shuttle Columbia was returning to Earth with a crew of seven astronauts on 1Feb, 2003. It disintegrated along a track extending from California to Louisiana and observers along part of the track filmed the breakup of Columbia. Debris was recovered from Littlefield, Texas to Fort Polk, Louisiana, along a 567 statute mile track; the largest ever recorded debris field. The Columbia Accident Investigation Board (CAIB) concluded its investigation in August 2003, and released their findings in a report published in February 2004. NASA recognized the importance of capturing the lessons learned from the loss of Columbia and her crew and the Space Shuttle Program managers commissioned the Spacecraft Crew Survival Integrated Investigation Team (SCSIIT) to accomplish this. Their task was to perform a comprehensive analysis of the accident, focusing on factors and events affecting crew survival, and to develop recommendations for improving crew survival, including the design features, equipment, training and procedures intended to protect the crew. NASA released the Columbia Crew Survival Investigation Report in December 2008. Key personnel have been assembled to give you an overview of the Space Shuttle Columbia accident, the medical response, the medico-legal issues, the SCSIIT findings and recommendations and future NASA flight surgeon spacecraft accident response training. Educational Objectives: Set the stage for the Panel to address the investigation, medico-legal issues, the Spacecraft Crew Survival Integrated Investigation Team report and training for accident response.

Chandler, Michael↗

Urban Air Mobility Fleet Manager Gap Analysis and System Design

NASA’s Urban Air Mobility (UAM) Sub-Project is engaged in re-search to facilitate the introduction of air taxis into the US National Airspace System. Given the history of conventional aircraft operations, it is clear that dispatcher support will be required for UAM. This paper presents a gap analysis, system requirements, and a workstation design concept for the UAM dispatcher or Fleet Manager (FM) position. The gap analysis focuses on the differences be-tween the tasks of the airline dispatcher and those projected for the FM. FM system capabilities and data requirements are then presented as foundations for soft-ware development. An initial user interface concept is provided. The FM software uses a single, large display. The system supports prediction, monitoring, and task execution. This paper is intended to support FM software design for future air taxi systems.

Richard Mogford↗

SafeAeroBERT: Towards a Safety-Informed Aerospace-Specific Language Model

As aviation systems continue to operate with high traffic, large amounts of documents containing safety-relevant data continue to be generated via reporting systems such as the Aviation Safety Reporting System (ASRS). Advanced natural language processing techniques, specifically pre-trained language models, have shown great success in domain-specific applications; however, the text in aviation safety reports is inundated with jargon and thus not fully utilized by general pre-trained models. In this research, we work towards developing a safety-informed aerospace-specific language model by pre-training a Bidirectional Encoder Representations from Transformer (BERT) model on reports from the Aviation Safety Reporting System and the National Transportation Safety Board. The resulting model, called SafeAeroBERT, is fine-tuned for the specific task of document classification, and can be further tuned for named-entity recognition, relation detection, information retrieval, and summarization. Results from the classification task are compared between SafeAeroBERT, the base BERT, and SciBERT models and show SafeAeroBERT outperforms the general BERT and SciBERT on classifying reports about weather and procedure. SafeAeroBERT can be used on custom tasks, not limited to document classification, and is intended to aid an intelligent knowledge manager for safety report repositories.

Aviation↗

SafeAeroBERT: Towards a Safety-Informed Aerospace-Specific Language Model

As aviation systems continue to operate with high traffic, large amounts of documents containing safety-relevant data continue to be generated via reporting systems such as the ASRS. Advanced natural language processing techniques, specifically pre-trained language models, have shown great success in domain-specific applications; however, the text in aviation safety reports is inundated with jargon and thus not fully utilized by general pre-trained models. In this research, we work towards developing a safety-informed aerospace-specific language model by pre-training a Bidirectional Encoder Representations from Transformer (BERT) model on reports from the Aviation Safety Reporting System and the National Transportation Safety Board. The resulting model, called SafeAeroBERT, is fine-tuned for the specific task of document classification, and can be further tuned for named-entity recognition, relation detection, information retrieval, and summarization. Results from the classification task are compared between SafeAeroBERT, the base BERT, and SciBERT models and show SafeAeroBERT outperforms the general BERT and SciBERT on classifying reports about human factors, aircraft, and procedure. SafeAeroBERT can be used on custom tasks, not limited to document classification, and is intended to aid an intelligent knowledge manager for safety report repositories.

Aviation↗

Unsupervised Learning for Equitable DER Control: Preprint

In the context of managing distributed energy resources (DERs) within distribution networks (DNs), this work focuses on the task of developing local controllers. We propose an unsupervised learning framework to train functions that can closely approximate optimal power flow (OPF) solutions. The primary aim is to establish specific conditions under which these learned functions can collectively guide the network towards desired configurations asymptotically, leveraging an incremental control approach. The flexibility of the proposed methodology allows to integrate fairness-driven components into the cost function associated with the OPF problem. This addition seeks to mitigate power curtailment disparities among DERs, thereby promoting equitable power injections across the network. To demonstrate the effectiveness of the proposed approach, power flow simulations are conducted using the IEEE 37-bus feeder. The findings not only showcase the guaranteed system stability but also underscore its improved overall performance.

asymptotic stability↗

Complexity Management Using Metrics for Trajectory Flexibility Preservation and Constraint Minimization

The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectory-based rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2)Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.

Idris, Husni↗

Integrating and Characterizing HPC Task Runtime Systems for hybrid AI-HPC workloads

Scientific workflows increasingly involve both HPC and machine-learning tasks, combining MPI-based simulations, training, and inference in a single execution. Launchers such as Slurm’s srun constrain concurrency and throughput, making them unsuitable for dynamic and heterogeneous workloads. We present a performance study of RADICAL-Pilot (RP) integrated with Flux and Dragon, two complementary runtime systems that enable hierarchical resource management and high-throughput function execution. Using synthetic and production-scale workloads on Frontier, we characterize the task execution properties of RP across runtime configurations. RP+Flux sustains up to 930 tasks/s, and RP+Flux+Dragon exceeds 1,500 tasks/s with over 99.6% utilization. In contrast, srun peaks at 152 tasks/s and degrades with scale, with utilization below 50%. For IMPECCABLE.v2 drug discovery campaign, RP+Flux reduces makespan by 30–60% relative to srun/Slurm and increases throughput more than four times on up to 1,024. These results demonstrate hybrid runtime integration in RP as a scalable approach for hybrid AI-HPC workloads.

HPC-AI↗

Waste Compliance and Tracking System (WCATS) Version 3 Requirements Document

This document describes the end-user requirements for the Waste Compliance and Tracking System (WCATS) project in accordance with the WCATS Software Quality Management Plan, EPC-WMP-WCATSPLAN-001. The WCATS application shall support the generation, characterization, processing, and shipment of LANL radioactive, hazardous, and industrial waste. Regulatory drivers include RCRA hazardous waste, DOT shipping, NNSA nuclear material control and accountability, DOE nuclear safety, TSDF permit, and transuranic waste certification requirements. The system will utilize a task-based architecture that supports the spectrum of treatment, storage, disposal, administrative, and characterization based unit operations necessary to manage waste from cradle to grave. The application design shall readily accommodate new facilities, processes, workflow, signature requirements, and so forth, via end-user established metadata. WCATS will provide support for representing waste storage and disposal facilities, buildings, rooms, and grid layouts (x, y, z) to support waste and radioactive material inventory management. Nuclear material at risk (MAR), DOE hazard rating (e.g., Category II facility) compliance per DOE-STD-1027, and permit inventory requirements will be configurable for any storage or disposal facility, or waste operation, and the system will automatically evaluate and enforce those requirements. In addition, the application will support the characterization and management of the entire range of hazardous and radioactive wastes (TRU, MTRU, LLW, MLLW, hazardous waste, etc.) that might be colocated or processed at a permitted facility. Some capabilities not found in traditional systems include user-defined tank systems for liquid waste, user-defined work paths (i.e., sequence of operations), and an equipment subsystem for tracking the calibration, maintenance, and inspection of tools used to process waste, such as torque wrenches, scales, pH probes, etc. The application incorporates a desktop and mobile user interface as shown in Figure 1. The mobile interface supports field operations, such as waste item characterization, intra-facility transfers, internal and external audits, and shipment preparation and receipt.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Integrating External Resources with a Task-Based Programming Model

Accessing external resources (e.g., loading input data, checkpointing snapshots, and out-of-core processing) can have a significant impact on the performance of supercomputer applications. However, no existing programming systems for high-performance computing directly manage and optimize these external accesses. As a result, users must explicitly manage external accesses alongside their computation at the application level, which can result in both correctness and performance issues. We address this limitation by introducing Iris, a task-based programming model with semantics for external resources. Iris allows applications to describe their access requirements to external resources and the relationship of those accesses to the computation. Iris incorporates external I/O into a deferred execution model, reschedules external I/O to overlap I/O with computation, and reduces external I/O when possible. We evaluate Iris on three microbenchmarks representative of important workloads in HPC and a full combustion simulation, S3D. We demonstrate that the Iris implementation of S3D reduces the external I/O overhead by up to 20×, compared to the Legion and the Fortran implementations.

97 MATHEMATICS AND COMPUTING↗

The Planning Execution Monitoring Architecture

The Planning Execution Monitoring (PEM) architecture is a design concept for developing autonomous cockpit command and control software. The PEM architecture is designed to reduce the operations costs in the space transportation system through the use of automation while improving safety and operability of the system. Specifically, the PEM autonomous framework enables automatic performance of many vehicle operations that would typically be performed by a human. Also, this framework supports varying levels of autonomous control, ranging from fully automatic to fully manual control. The PEM autonomous framework interfaces with the core flight software to perform flight procedures. It can either assist human operators in performing procedures or autonomously execute routine cockpit procedures based on the operational context. Most importantly, the PEM autonomous framework promotes and simplifies the capture, verification, and validation of the flight operations knowledge. Through a hierarchical decomposition of the domain knowledge, the vehicle command and control capabilities are divided into manageable functional "chunks" that can be captured and verified separately. These functional units, each of which has the responsibility to manage part of the vehicle command and control, are modular, re-usable, and extensible. Also, the functional units are self-contained and have the ability to plan and execute the necessary steps for accomplishing a task based upon the current mission state and available resources. The PEM architecture has potential for application outside the realm of spaceflight, including management of complex industrial processes, nuclear control, and control of complex vehicles such as submarines or unmanned air vehicles.

Wang, Lui↗

Exploration Studies Technical Report - Volume 1: Technical Summary

The Office of Exploration (OEXP) at NASA Headquarters has been tasked with defining and recommending alternatives for an early 1990's national decision on a focused program of human exploration of the solar system. The Mission Analysis and System Engineering (MASE) group, which is managed by the Exploration Studies Office at the Lyndon B. Johnson Space Center, is responsible for coordinating the technical studies necessary for accomplishing such a task. This technical report, produced by the MASE, describes the process that has been developed in a case study approach. The four case studies developed in FY88 include: 1. Human Expedition to Phobos 2. Human Expedition to Mars 3. Lunar Observatory 4. Lunar Outpost to Early Mars Evolution The final outcome of this effort is a set of programmatic and technical conclusions and recommendations for the following year's work.

Lunar Mining & Oxygen Production↗

MatRIS: Addressing the Challenges for Portability and Heterogeneity Using Tasking for Matrix Decomposition (Cholesky)

The ubiquitous in-node heterogeneity of HPC and cloud computing platforms makes software portability and performance optimization extremely challenging. Described here, the MatRIS multilevel math library abstraction framework employs tasking to alleviate these difficulties. MatRIS includes the IRIS task-based runtime on the bottom level and exposes different layers of abstraction to render algorithms architecturally agnostic. MatRIS ensures the decomposition and creation of tasks that represent the necessary encapsulation of the optimized kernels from both vendor and open-source math libraries. Once built, MatRIS can select different combinations of accelerators at runtime, making it portable even on diverse heterogeneous architectures. By leveraging the IRIS runtime’s features for managing heterogeneity, MatRIS deploys algorithms that remove the need to specify orchestration and data transfer. This study describes how the serial task abstraction of a tiled Cholesky factorization is made portable and scalable in the case of multi-device and multi-vendor heterogeneity on a node with NVIDIA and AMD GPUs by using MatRIS. First, we demonstrate that Cholesky in MatRIS provides multi-GPU scalability that offers competitive performance versus cuSolverMG. Then, we present the challenges and opportunities for heterogeneous execution.

Monil, M. A. H.↗

Scalable Data Management of the Uintah Simulation Framework for Next-Generation Engineering Problems with Radiation

The need to scale next-generation industrial engineering problems to the largest computational platforms presents unique challenges. This paper focuses on data management related problems faced by the Uintah simulation framework at a production scale of 260K processes. Uintah provides a highly scalable asynchronous many-task runtime system, which in this work is used for the modeling of a 1000 megawatt electric (MWe) ultra-supercritical (USC) coal boiler. At 260K processes, we faced both parallel I/O and visualization related challenges, e.g., the default file-per-process I/O approach of Uintah did not scale on Mira. In this paper we present a simple to implement, restructuring based parallel I/O technique. We impose a restructuring step that alters the distribution of data among processes. The goal is to distribute the dataset such that each process holds a larger chunk of data, which is then written to a file independently. This approach finds a middle ground between two of the most common parallel I/O schemes–file per process I/O and shared file I/O–in terms of both the total number of generated files, and the extent of communication involved during the data aggregation phase. To address scalability issues when visualizing the simulation data, we developed a lightweight renderer using OSPRay, which allows scientists to visualize the data interactively at high quality and make production movies. Finally, this work presents a highly efficient and scalable radiation model based on the sweeping method, which significantly outperforms previous approaches in Uintah, like discrete ordinates. The integrated approach allowed the USC boiler problem to run on 260K CPU cores on Mira.

97 MATHEMATICS AND COMPUTING↗

OMS FDIR: Initial prototyping

The Space Station Freedom Program (SSFP) Operations Management System (OMS) will automate major management functions which coordinate the operations of onboard systems, elements and payloads. The objectives of OMS are to improve safety, reliability and productivity while reducing maintenance and operations cost. This will be accomplished by using advanced automation techniques to automate much of the activity currently performed by the flight crew and ground personnel. OMS requirements have been organized into five task groups: (1) Planning, Execution and Replanning; (2) Data Gathering, Preprocessing and Storage; (3) Testing and Training; (4) Resource Management; and (5) Caution and Warning and Fault Management for onboard subsystems. The scope of this prototyping effort falls within the Fault Management requirements group. The prototyping will be performed in two phases. Phase 1 is the development of an onboard communications network fault detection, isolation, and reconfiguration (FDIR) system. Phase 2 will incorporate global FDIR for onboard systems. Research into the applicability of expert systems, object-oriented programming, fuzzy sets, neural networks and other advanced techniques will be conducted. The goals and technical approach for this new SSFP research project are discussed here.

Taylor, Eric W.↗

A robotic system for automation of logistics functions on the Space Station

Spacecraft inventory management is currently performed by the crew and as systems become more complex, increased crew time will be required to perform routine logistics activities. If future spacecraft are to function effectively as research labs and production facilities, the efficient use of crew time as a limited resource for performing mission functions must be employed. The use of automation and robotics technology, such as automated warehouse and materials handling functions, can free the crew from many logistics tasks and provide more efficient use of crew time. Design criteria for a Space Station Automated Logistics Inventory Management System is focused on through the design and demonstration of a mobile two armed terrestrial robot. The system functionally represents a 0 gravity automated inventory management system and the problems associated with operating in such an environment. Features of the system include automated storage and retrieval, item recognition, two armed robotic manipulation, and software control of all inventory item transitions and queries.

Martin, J. C.↗