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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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913 records · Page 51

Flexible and Effective Object Tiering for Heterogeneous Memory Systems

Computing platforms that package multiple types of memory, each with their own performance characteristics, are quickly becoming mainstream. To operate efficiently, heterogeneous memory architectures require new data management solutions that are able to match the needs of each application with an appropriate type of memory. As the primary generators of memory usage, applications create a great deal of information that can be useful for guiding memory management, but the community still lacks tools to collect, organize, and leverage this information effectively. To address this gap, this work introduces a novel software framework that collects and analyzes object-level information to guide memory tiering. The framework includes tools to monitor the capacity and usage of individual data objects, routines that aggregate and convert this information into tier recommendations for the host platform, and mechanisms to enforce these recommendations according to user-selected policies. Moreover, the developed tools and techniques are fully automatic, work on standard Linux systems, and do not require modification or recompilation of existing software. Using this framework, this study evaluates and compares the impact of a variety of design choices for memory tiering, including different policies for prioritizing objects for the fast memory tier as well as the frequency and timing of migration events. In conclusion, the results, collected on a modern Intel platform with conventional DDR4 SDRAM as well as Intel Optane NVRAM, show that guiding data tiering with object-level information can enable significant performance and efficiency benefits compared with standard hardware- and software-directed data-tiering strategies for a diverse set of memory-intensive workloads.

97 MATHEMATICS AND COMPUTING↗

REBOUND: Reverse Engineering Bidirectional Outflow Under Non-Equilibrium Diffusion

Rare-earth elements (REEs) are essential for electronics, renewable energy, and defense technologies. However, the current supply of REEs relies on mining concentrated in a few countries and energy-intensive separations. DOE’s Basic Energy Sciences (BES) program has launched a grand challenge which aims to ensure a sustainable supply of critical REEs by developing innovative and environmentally friendly separation methods. As an alternative to costly and harmful traditional methods, the Non-Equilibrium Transport Driven Separations (NETS) initiative has created a microfluidic Y-channel co-flow method that applies external fields to exploit magneto- and electrohydrodynamic effects for separating dilute REE ions from complex feedstocks. Computational fluid dynamics (CFD) studies have identified a few operating conditions with promising ion selectivity and separation efficiency. However, challenges remain regarding Y-channel versatility across feedstocks and accurate incorporation of physical phenomena into CFD models. In this work, we develop a multi-fidelity modelling approach which integrates experimental results with CFD simulation to build a surrogate model for the dependence of separation efficiency to variation of design parameters. The surrogate model enables a reinforcement learning (RL) method to adaptively launch CFD and experimental runs, improving model fidelity around optimal Y-channel parameters.

36 MATERIALS SCIENCE↗

Quantum Software Engineering (Dagstuhl Seminar 24512)

The Dagstuhl Seminar 24512 on "Quantum Software Engineering" was held from December 15 to 20, 2024. It brought together 26 participants from industry and academia from 13 different countries, including senior and junior researchers as well as practitioners in the field of Quantum Software Engineering. The aim of the seminar was to advance software engineering methods and tools for the engineering of hybrid quantum systems by promoting personal interaction and open discussion among researchers who are already working in this emerging area of knowledge. The first day of the seminar was devoted to the topic "When software engineering meets quantum mechanics", while the second day focused on "Quantum software engineering and its challenges." During both days, 16 invited presentations were given. The rest of the seminar was organized into three working groups to address the topics "Quantum Software Design, Modelling and Architecturing", "Adaptive Hybrid Quantum Systems", and "Quantum Software Quality Assurance". The seminar was a very fruitful experience for all participants both in terms of scientific outcomes and in terms of the personal relationships that were generated to jointly address future experiences.

97 MATHEMATICS AND COMPUTING↗

Maintaining the Health of Software Monitors

Software health management (SWHM) techniques complement the rigorous verification and validation processes that are applied to safety-critical systems prior to their deployment. These techniques are used to monitor deployed software in its execution environment, serving as the last line of defense against the effects of a critical fault. SWHM monitors use information from the specification and implementation of the monitored software to detect violations, predict possible failures, and help the system recover from faults. Changes to the monitored software, such as adding new functionality or fixing defects, therefore, have the potential to impact the correctness of both the monitored software and the SWHM monitor. In this work, we describe how the results of a software change impact analysis technique, Directed Incremental Symbolic Execution (DiSE), can be applied to monitored software to identify the potential impact of the changes on the SWHM monitor software. The results of DiSE can then be used by other analysis techniques, e.g., testing, debugging, to help preserve and improve the integrity of the SWHM monitor as the monitored software evolves.

Runtime Monitor↗

Monitoring with Data Automata

We present a form of automaton, referred to as data automata, suited for monitoring sequences of data-carrying events, for example emitted by an executing software system. This form of automata allows states to be parameterized with data, forming named records, which are stored in an efficiently indexed data structure, a form of database. This very explicit approach differs from other automaton-based monitoring approaches. Data automata are also characterized by allowing transition conditions to refer to other parameterized states, and by allowing transitions sequences. The presented automaton concept is inspired by rule-based systems, especially the Rete algorithm, which is one of the well-established algorithms for executing rule-based systems. We present an optimized external DSL for data automata, as well as a comparable unoptimized internal DSL (API) in the Scala programming language, in order to compare the two solutions. An evaluation compares these two solutions to several other monitoring systems.

log analysis↗

Establishing the Assurance Efficacy of Automated Risk Mitigation Strategies

Verification and validation of increasingly autonomous aviation systems is a major challenge. Traditional techniques for the assurance of high-confidence, safety-critical systems are not equipped to handle the complexity, uncertainty, and lack of predictability inherent in non-deterministic systems. Techniques such as run time monitoring, formal methods, and testing and simulation have been applied to some effect, but it is difficult to properly assess the success of such measures. The authors propose the concept of Assurance Efficacy to address this gap. Assurance Efficacy is seen as a parameter, criteria, or perspective by which to evaluate, identify and explore safety risk mitigation strategies and operational assurance architectures. Validation of the utility of this concept through flight testing is a first step in determining its potential role in assessing the overall safety of complex, increasingly autonomous systems that cannot be fully assured in the design phase.

system safety↗

Dynamic Assurance of Autonomous Systems through Ground Control Software∗

Assurance cases are being increasingly acknowledged as a way to build trust in complex systems with autonomous capabilities [1]. An assurance case is a comprehensive, defensible, and valid justification that a system will function as intended for the specific mission and operating environment. Such justifications for systems with autonomous capabilities are often based on various probabilistic quantifications [2]. Due to the dynamic nature of the environmental conditions in which these systems operate, as well as the changing nature of the autonomous systems themselves, these probabilistic quantifications cannot be simply estimated once during design time. Rather, they need to be continually evaluated during systems operations to ensure that the assurance case justifications are valid. We refer to the assurance case that combines both the static and dynamic elements as a Dynamic Assurance Case (DAC).

dynamic assurance case↗

Wildfire-fighting Use Case Requirements to Monitor

In this technical report, we provide requirements for a wildfire-fighting use-case, towards the Safety Demonstrator 1. The use case will incorporate ground and airborne assets operating in a coordinated fashion, and will comprise five activities, from detection to the execution of the initial attack. Depending on the activity and the data involved, the requirements identified may be non-probabilistic or probabilistic. In both cases, we first identify some of the requirements we wish to monitor, and then present a formalization using the language of requirements of the NASA requirements elicitation tool FRET. To formalize probabilistic requirements, we use a novel extension to FRET’s requirements language that incorporates notions of probability, and discuss how requirements can be translated into existing probabilistic temporal logics like PCTL. We exemplify how some of the requirements presented can be monitored using the existing tools Ogma and Copilot. We close with a summary and future directions.

Requirements↗

Dynamic Assurance of Autonomous Systems Through Ground Control Software

Assurance cases have emerged as a way to build trust in complex autonomous systems. Many assurance case justifications for such systems need to be constantly reevaluated based on the current system context and performance. Autonomous systems, especially those deployed in remote environments, often have a ground control system that enables monitoring and remote operations. In this paper, we propose a dynamic assurance framework that aims at connecting the assurance case with the ground control system. We use the ground control system to facilitate dynamic evaluation of quantitative assurance measures that support various justifications in the assurance case. We demonstrate the proposed dynamic assurance framework on the NASA Ames Research Center project Troupe. We use a combination of in-house and external tools to identify the assurance measures, formalize the related requirements, and generate monitors that feed the data to the external ground control system.

dynamic assurance case↗

Assuring and Securing Machine Learning

A short presentation highlighting using machine learning and topological data analysis to address the challenges of assuring and securing machine learning enabled systems.

Machine Learning↗