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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

DISTRI: Distributed Multi-Facility HPC Simulator (DISTRI) v2.1

DISTRI is an advanced network simulator designed for multi-facility computational infrastructures with agentic behavior. It simulates HPC facilities where computational resources act as autonomous agents, making intelligent decisions about job scheduling, load balancing, and resource allocation. The simulator focuses on developing and testing decentralized algorithms that promote resilience and efficiency in multi-facility environments. Key Features: - Agentic Resource Behavior: Processors and DTNs act as autonomous agents with decision-making capabilities - Pheromone-Based Load Balancing: Decentralized load balancing inspired by ant colony optimization - Dual Topology Support: Mesh (normal operations) and Dumbell (network testing) topologies - Comprehensive TCP Simulation: Realistic TCP implementations with multiple congestion control algorithms - Failure Resilience Testing: Processor failure simulation with automatic job reassignment - Extensive Visualization: Detailed performance analysis and metrics collection - Research-Ready: Designed for algorithm development and benchmarking

Bez, Jean Luca [Lawrence Berkeley National Laborat↗
NASA NTRS2006

Conflict-Aware Scheduling Algorithm

conflict-aware scheduling algorithm is being developed to help automate the allocation of NASA s Deep Space Network (DSN) antennas and equipment that are used to communicate with interplanetary scientific spacecraft. The current approach for scheduling DSN ground resources seeks to provide an equitable distribution of tracking services among the multiple scientific missions and is very labor intensive. Due to the large (and increasing) number of mission requests for DSN services, combined with technical and geometric constraints, the DSN is highly oversubscribed. To help automate the process, and reduce the DSN and spaceflight project labor effort required for initiating, maintaining, and negotiating schedules, a new scheduling algorithm is being developed. The scheduling algorithm generates a "conflict-aware" schedule, where all requests are scheduled based on a dynamic priority scheme. The conflict-aware scheduling algorithm allocates all requests for DSN tracking services while identifying and maintaining the conflicts to facilitate collaboration and negotiation between spaceflight missions. These contrast with traditional "conflict-free" scheduling algorithms that assign tracks that are not in conflict and mark the remainder as unscheduled. In the case where full schedule automation is desired (based on mission/event priorities, fairness, allocation rules, geometric constraints, and ground system capabilities/ constraints), a conflict-free schedule can easily be created from the conflict-aware schedule by removing lower priority items that are in conflict.

Wang, Yeou-Fang↗
NASA NTRS2000

Message Mode Operations for Spacecraft: A Proposal for Operating Spacecraft During Cruise and Mitigating the Network Loading Crunch

The NASA Deep Space Network (DSN) is a world-class spacecraft tracking facility with stations located in Spain, Australia and USA, servicing Deep Space Missions of many space agencies. The current system of scheduling spacecraft during cruise for multiple 8 hour tracking sessions per week currently leads to an overcommitted DSN. Studies indicate that future projected mission demands upon the Network will only make the loading problem worse. Therefore, a more efficient scheduling of DSN resources is necessary in order to support the additional network loading envisioned in the next few years: The number of missions is projected to increase from 25 in 1998 to 34 by 2001. In fact given the challenge of the NASA administrator, Dan Goldin, of launching 12 spacecraft per year, the DSN would be tracking approximately 90 spacecraft by 2010. Currently a large amount of antenna time and network resources are subscribed by a project in order to have their mission supported during the cruise phase. The recently completed Mars Pathfinder mission was tracked 3 times a week (8 hours/day) during the majority of its cruise to Mars. This paper proposes an innovative approach called Message Mode Operations (MMO) for mitigating the Network loading problem while continuing to meet the tracking, reporting, time management, and scheduling requirements of these missions during Cruise while occupying very short tracking times. MMO satisfies these requirements by providing the following services: Spacecraft Health and Welfare Monitoring Service Command Delivery Service Adaptive Spacecraft Scheduling Service Orbit Determination Service Time Calibration Service Utilizing more efficient engineering telemetry summarization and filtering techniques on-board the spacecraft and collapsing the navigation requirements for Doppler and Range into shorter tracks, we believe spacecraft can be adequately serviced using short 10 to 30 minute tracking sessions. This claim assumes that certain changes would have to he made in the way the Network traditionally services missions in Cruise. Furthermore, limiting spacecraft to short sessions will free up larger blocks of time in the tracking schedule to help accommodate future tracking demands soon to be placed upon the Network. This paper describes the key characteristics and benefits of MMO, the operational scenarios for its use, the required changes to the ground system in order to make this approach feasible and the results of two simulations: 1) to determine the effects of MMO on projected mission loading on the DSN and, 2) to determine the effect MMO has on spacecraft orbit determination.

Greenberg, Ed↗
DOE OSTI2020

Characterizing the Performance of Executing Many-tasks on Summit

Many scientific workloads are comprised of many tasks, where each task is an independent simulation or analysis of data. The execution of millions of tasks on heterogeneous HPC platforms requires scalable dynamic resource management and multi-level scheduling. RADICAL-Pilot (RP) -- an implementation of the Pilot abstraction, addresses these challenges and serves as an effective runtime system to execute workloads comprised of many tasks. In this paper, we characterize the performance of executing many tasks using RP when interfaced with JSM and PRRTE on Summit: RP is responsible for resource management and task scheduling on acquired resource; JSM or PRRTE enact the placement of launching of scheduled tasks. Our experiments provide lower bounds on the performance of RP when integrated with JSM and PRRTE. Specifically, for workloads comprised of homogeneous single-core, 15 minutes-long tasks we find that: PRRTE scales better than JSM for > O(1000) tasks; PRRTE overheads are negligible; and PRRTE supports optimizations that lower the impact of overheads and enable resource utilization of 63% when executing O(16K), 1-core tasks over 404 compute nodes.

Matteo, Turilli↗
NASA NTRS2004

Optimizing Mars Airplane Trajectory with the Application Navigation System

Planning complex missions requires a number of programs to be executed in concert. The Application Navigation System (ANS), developed in the NAS Division, can execute many interdependent programs in a distributed environment. We show that the ANS simplifies user effort and reduces time in optimization of the trajectory of a martian airplane. We use a software package, Cart3D, to evaluate trajectories and a shortest path algorithm to determine the optimal trajectory. ANS employs the GridScape to represent the dynamic state of the available computer resources. Then, ANS uses a scheduler to dynamically assign ready task to machine resources and the GridScape for tracking available resources and forecasting completion time of running tasks. We demonstrate system capability to schedule and run the trajectory optimization application with efficiency exceeding 60% on 64 processors.

Frumkin, Michael↗
NASA NTRS1997

Using Common Graphics Paradigms Implemented in a Java Applet to Represent Complex Scheduling Requirements

The experiments planned for the International Space Station promise to be complex, lengthy and diverse. The scarcity of the space station resources will cause significant competition for resources between experiments. The scheduling job facing the Space Station mission planning software requires a concise and comprehensive description of the experiments' requirements (to ensure a valid schedule) and a good description of the experiments' flexibility (to effectively utilize available resources). In addition, the continuous operation of the station, the wide geographic dispersion of station users, and the budgetary pressure to reduce operations manpower make a low-cost solution mandatory. A graphical representation of the scheduling requirements for station payloads implemented via an Internet-based application promises to be an elegant solution that addresses all of these issues. The graphical representation of experiment requirements permits a station user to describe his experiment by defining "activities" and "sequences of activities". Activities define the resource requirements (with alternatives) and other quantitative constraints of tasks to be performed. Activities definitions use an "outline" graphics paradigm. Sequences define the time relationships between activities. Sequences may also define time relationships with activities of other payloads or space station systems. Sequences of activities are described by a "network" graphics paradigm. The bulk of this paper will describe the graphical approach to representing requirements and provide examples that show the ease and clarity with which complex requirements can be represented. A Java applet, to run in a web browser, is being developed to support the graphical representation of payload scheduling requirements. Implementing the entry and editing of requirements via the web solves the problems introduced by the geographic dispersion of users. Reducing manpower is accomplished by developing a concise representation which eliminates the misunderstanding possible with verbose representations and which captures the complete requirements and flexibility of the experiments.

Jaap, John↗
DOE OSTI2024

Improving I/O-aware Workflow Scheduling via Data Flow Characterization and trade-off Analysis

The scientific computing paradigm has transitioned from compute-intensive to I/O-intensive and memory-intensive in the past decade, especially when data-driven science has become common practice. Numerous empirical I/O-aware scheduling optimizations have been developed by incorporating I/O capacity and bandwidth as constraints into scheduling. Unfortunately, there is a lack of data flow (I/O) characterization tool and an understanding of trade-offs between concurrency, locality, and I/O bandwidth. To bridge the gap, this work 1) presents a set of descriptors to characterize, organize, and visualize I/O profiles, including flow size, I/O bandwidth, and operation count, which group data flows by I/O types, tasks, and files; 2) proposes an I/O Roofline model-based trade-off analysis to find the optimal trade-off between flow operational intensity, concurrency, and flow performance. The I/O descriptors generate useful insights into complicated I/O behaviors, suggesting distinct concurrency, storage, and scheduling to be used by types, tasks, and files. The proposed trade-off analysis guides scheduling decisions that generate resource assignment with the best flow parallelism. We evaluate our I/O-aware scheduling methodology on a highly I/O-intensive workflow–1000 Genomes. The experimental results demonstrate speedups of up to 2.4× compared to the state-of-the- art methods.

Guo, Luanzheng [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2016

Time-Series Forecast Modeling on High-Bandwidth Network Measurements

With the increasing number of geographically distributed scientific collaborations and the growing sizes of scientific data, it has become challenging for users to achieve the best possible network performance on a shared network. In this paper, we have developed a model to forecast expected bandwidth utilization on high-bandwidth wide area networks. The forecast model can improve the efficiency of the resource utilization and scheduling of data movements on high-bandwidth networks to accommodate ever increasing data volume for large-scale scientific data applications. A univariate time-series forecast model is developed with the Seasonal decomposition of Time series by Loess (STL) and the AutoRegressive Integrated Moving Average (ARIMA) on Simple Network Management Protocol (SNMP) path utilization measurement data. Compared with the traditional approach such as Box-Jenkins methodology to train the ARIMA model, our forecast model reduces computation time up to 92.6 %. It also shows resilience against abrupt network usage changes. Finally, our forecast model conducts the large number of multi-step forecast, and the forecast errors are within the mean absolute deviation (MAD) of the monitored measurements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Distributed ADMM Using Private Blockchain for Power Flow Optimization in Distribution Network With Coupled and Mixed-Integer Constraints

The optimization problem for scheduling distributed energy resources (DERs) and battery energy storage systems (BESS) integrated with the power grid is important to minimize energy consumption from conventional sources in response to demand. Conventionally this optimization problem is solved in a centralized manner, limiting the size of the problem that can be solved and creating a high communication overhead because all the data is transferred to the central controller. These limitations are addressed by the proposed distributed consensus-based alternating direction method of multiplier (DC-ADMM) optimization algorithm, which decomposes the optimization problem into subproblems with private cost function and constraints. The distribution feeder is partitioned into low coupling subnetworks/regions, which solves the private subproblem locally and exchanges information with the neighboring regions to reach consensus. The relaxation strategy is employed for mixed-integer and coupled constraints introduced in the optimal power flow (OPF) problem by stationary and transportable BESS because DC-ADMM convergence is only guaranteed for strict convex problems. The information exchange and synchronization between subnetworks/regions are vital for distributed optimization. In this work, both of these aspects are addressed by the blockchain. The smart contract deployed on the blockchain network acts as a mediator for secure data exchange and synchronization in distributed computation. The blockchain-based distributed optimization problem’s effectiveness is tested for a 0.5-MW laboratory microgrid for one hour ahead and day-ahead for the IEEE 123-bus and EPRI J1 test feeders, and results are compared with a centralized solution.

25 ENERGY STORAGE↗
DOE OSTI2018

Coupling Exascale Multiphysics Applications: Methods and Lessons Learned

With the growing computational complexity of science and the complexity of new and emerging hardware, it is time to re-evaluate the traditional monolithic design of computational codes. One new paradigm is constructing larger scientific computational experiments from the coupling of multiple individual scientific applications, each targeting their own physics, characteristic lengths, and/or scales. We present a framework constructed by leveraging capabilities such as in-memory communications, workflow scheduling on HPC resources, and continuous performance monitoring. This code coupling capability is demonstrated by a fusion science scenario, where differences between the plasma at the edges and at the core of a device have different physical descriptions. This infrastructure not only enables the coupling of the physics components, but it also connects in situ or online analysis, compression, and visualization that accelerate the time between a run and the analysis of the science content. Results from runs on Titan and Cori are presented as a demonstration.

Choi, Jong Youl↗
DOE OSTI2015

Network bandwidth utilization forecast model on high bandwidth networks

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2%. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Post-Disturbance Dynamic Distribution System Restoration with DGs and Mobile Resources

Distributed generations (DGs) can act as emergency power supplies when distribution systems suffer from outages. However, the generation capabilities of DGs are generally limited by a number of factors including weather conditions, fuel limitations, etc. In this context, mobile resources that are able to reallocate resources to desired locations are regarded as important complements to conventional fixed DGs in assisting distribution system restoration. In this paper, a distribution system restoration model with DGs and mobile resources is proposed. Firstly, the dispatch and allocation of mobile resources are modeled with respect to the characteristics of the traffic network. Then the developed mobile resource models are integrated into the distribution system restoration model to co-optimize the scheduling of DGs and mobile resources. Uncertainty factors are managed by a model predictive control approach so that system operators can dynamically adjust the restoration strategy with the up-to-date information. The effectiveness of the proposed method is validated through an IEEE 13-bus test system.

distributed generations (DGs)↗
DOE OSTI2025

A Digital Twin of Scalable Quantum Clouds

Quantum computing has emerged as a transformative technology capable of solving complex problems beyond the limit of classical systems. The rapid development of quantum processors has led to the proliferation of cloud-based quantum computing services offered by platforms such as IBM, Google, and Amazon. These platforms introduce unique challenges in resource allocation, job scheduling, and multi-device orchestration as quantum workloads become increasingly complex. In this work, we present a digital twin of quantum cloud infrastructures: a framework designed to model and simulate the behavior of real quantum cloud systems. Developed in Python using the SimPy discrete-event simulation library, the framework replicates key aspects of quantum cloud environments, including detailed quantum device modeling, job lifecycle management, and job fidelity. It incorporates noise-aware fidelity estimation, making it the first of its kind to simulate superconducting gate-based quantum cloud systems at an administrative level with job fidelity. We present use cases as proof of concept, demonstrating that our quantum cloud simulation framework can act as a digital twin of a quantum cloud and support the modeling and implementation of practical systems.

Luo, Waylon [Kent State University]↗
DOE OSTI2014

Network Bandwidth Utilization Forecast Model on High Bandwidth Network

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Generating HPC Job Profiles and Expectations with Time-Series Data - Showcase Presentation

Summary: Job Profiles and Expectations provide important insights into workloads (Job Profile: window into how a job is running; Job Expectation: Is that job behaving as expected; Provides us with actionable information). Machine learning can be used to group job runs into workload types (Identified groups can then be used for generate expectations); Profiles and Expectations also enable the study of: System-wide events, tracking system changes; System resource utilization and scheduling; Marking log data for further investigation or failures/anomalies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Integral Experiment Request 230 CED-3a (Summary Report)

During CED-3a, the following information is required, as specified in the April 1,2016 revision of the CEdT process manual: A detailed cost estimate; and, A resource loaded(baseline) schedule for execution of the experiment, data analysis, and publication. Appendix I is a Gantt chart or various phases of the project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Area V: Waste Management and Subsurface Science (FY21-23 Final Report)

The objective of the Waste Management and Subsurface Science Topic Area V project is to evaluate the feasibility and safety of an intermediate-depth borehole for disposal of Israel Atomic Energy Commission (IAEC) nuclear waste. The IAEC nuclear waste is currently stored in above ground and/or in near-surface facilities that provide short-term radiological worker safety but do not provide long-term, full security and safeguards protection for the nuclear material. Disposal of the IAEC nuclear waste several hundred meters below the surface in a sealed borehole would provide long-term security and safeguards due to its depth underground, as well as long-term radiological safety, due to its isolation in a stable geological formation. This project supports the nuclear security and safeguards initiatives of the Science and Technology Working Group of the NNSA/IAEC Memorandum of Understanding (MOU) and addresses the Topic Area V objective and associated goals. The goals for Topic Area V are: (1) Assess the suitability of the vadose zone in the Yamin Plain of the northern Negev Desert, Israel as a host location for intermediate-depth borehole disposal of radioactive waste, (2) Define and refine the necessary characterization needs to better understand the regional climate, structure, and stratigraphy, geomechanics, geochemistry, hydrogeology, and seismicity of the stratigraphic sequence from the surface to the water table in the vicinity of the proposed host location for the disposal borehole(s), and (3) Develop a preliminary plan and schedule, including necessary resources and costs, for a borehole disposal concept and robust and transparent pre-closure and post-closure safety assessments. The safety assessments will require iteration with process level models at both site and regional scales. Upon completion, the information collected by this effort will allow the IAEC to make decisions regarding the viability and applicability of an intermediate depth (<500m) borehole for disposal in the vadose zone of the Yamin Plain. This FY21-23 final report is provided in lieu of a workshop report that was originally planned for delivery in January, 2024. Due to the conflict in Israel and associated delays, the workshop has been delayed to April 2024. The workshop will be held at LLNL but offsite and will switch to hybrid if travel restrictions remain in place. The associated workshop report will be provided as part of a new FY24-26 LCP.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1971

Spaceborne computer executive routine functional design specification. Volume 2: Computer executive design for space station/base

The computer executive functional system design concepts derived from study of the Space Station/Base are presented. Information Management System hardware configuration as directly influencing the executive design is reviewed. The hardware configuration and generic executive design requirements are considered in detail in a previous report (System Configuration and Executive Requirements Specifications for Reusable Shuttle and Space Station/Base, 9/25/70). This report defines basic system primitives and delineates processes and process control. Supervisor states are considered for describing basic multiprogramming and multiprocessing systems. A high-level computer executive including control of scheduling, allocation of resources, system interactions, and real-time supervisory functions is defined. The description is oriented to provide a baseline for a functional simulation of the computer executive system.

Kennedy, J. R.↗