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DOE OSTI2025

ATLAS HL-LHC Demonstrators with Data Carousel: Dataon-Demand and Tape Smart Writing

The High Luminosity upgrade to the LHC (HL-LHC) is expected to deliver scientific data at the multi-exabyte scale. To tackle this unprecedented data storage challenge, the ATLAS experiment initiated the Data Carousel project in 2018. Data Carousel is a tape-driven workflow in which bulk production campaigns with input data resident on tape are executed by staging and promptly processing a sliding window to disk buffer such that only a small fraction of inputs are pinned on disk at any one time. Put in ATLAS production before Run3, Data Carousel continues to be our focus for seeking new opportunities in disk space savings, and enhancing tape usage throughout the ATLAS Distributed Computing (ADC) environment. These efforts are highlighted by two recent ATLAS HL-LHC demonstrator projects: data-on-demand and tape smart writing. In this paper, we will discuss the recent studies and outcomes from these projects. The research was conducted together with site experts at CERN and Tier-1 centers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

MSD CoP Webinar: Quantum Computing Futures through a Multisector Lens

Context: This webinar featured two presentations examining quantum computing and its complex implications across the energy, water, and materials sectors. Olivier Ezratty introduced quantum computing, its anticipated applications and added value, and the hardware required to support these systems. He also discussed their energy demands and the role of the Quantum Energy Initiative in developing an interdisciplinary research field focused on these challenges. David McCollum then explored the opportunities and multisectoral challenges associated with next-generation, quantum-accelerated data centers, including their potential energy and resource impacts and the infrastructure chokepoints that could emerge. Together, the presentations emphasized the need for long-term planning and cross-cutting research collaboration as quantum computing technologies continue to develop. Presenters: Olivier Ezratty (Quantum Energy Initiative); David McCollum (Oak Ridge National Laboratory) Moderator: Patrick M. Reed (MSD CoP Facilitation Team); Gokul Iyer (Pacific Northwest National Laboratory) This webinar was held on: July 9th, 2026 from 1:00–2:30 PM EDT.

Quantum Computing↗

NASA NTRS2016

Pressure Loss Predictions of the Reactor Simulator Subsystem at NASA Glenn Research Center

Testing of the Fission Power System (FPS) Technology Demonstration Unit (TDU) is being conducted at NASA Glenn Research Center. The TDU consists of three subsystems: the reactor simulator (RxSim), the Stirling Power Conversion Unit (PCU), and the heat exchanger manifold (HXM). An annular linear induction pump (ALIP) is used to drive the working fluid. A preliminary version of the TDU system (which excludes the PCU for now) is referred to as the "RxSim subsystem" and was used to conduct flow tests in Vacuum Facility 6 (VF 6). In parallel, a computational model of the RxSim subsystem was created based on the computer-aided-design (CAD) model and was used to predict loop pressure losses over a range of mass flows. This was done to assess the ability of the pump to meet the design intent mass flow demand. Measured data indicates that the pump can produce 2.333 kg/sec of flow, which is enough to supply the RxSim subsystem with a nominal flow of 1.75 kg/sec. Computational predictions indicated that the pump could provide 2.157 kg/sec (using the Spalart-Allmaras (S‒A) turbulence model) and 2.223 kg/sec (using the k- turbulence model). The computational error of the predictions for the available mass flow is ‒0.176 kg/sec (with the S-A turbulence model) and -0.110 kg/sec (with the k- turbulence model) when compared to measured data.

Mass Flow↗

DOE OSTI2022

Future Trends in Nuclear Physics Computing

In nuclear physics (NP) today the study of quarks, gluons and their strong interactions extends across a broad research program at a varied range of collaborative scales, from a few collaborators up to large experiments at scales comparable to those typical of high energy physics (HEP). Overall, the software and computing efforts vary accordingly, from pragmatic do-it-yourself approaches among a few, to substantial organized software and computing activities within large experiments. With new experiments starting up and on the horizon [1], and rapidly increasing data volumes [2, 3] and processing demands even at small experiments, the NP community has in recent years been thinking about the next generation of data processing and analysis workflows that will maximize the science output. One context for this discussion has been a series of workshops, “Future Trends in Nuclear Physics Computing” [4]. The most recent in this series took place in Fall 2020, organized by the authors together with colleagues. The workshop focused on identifying the unique aspects of software and computing in NP, and discussing how the NP community could strengthen common efforts and chart a path forward for the next decade, sure to be an exciting one with rich ongoing scientific programs at Brookhaven National Laboratory (BNL), Jefferson Lab (JLab), and other NP facilities, and culminating in datataking at the Electron-Ion Collider (EIC) [5,6,7] in the early 2030s. Without claiming to present a collective view from the workshop and discussions since—fortunately this is not expected of us in this opinion editorial—we offer here our reflections on the topic, informed by the workshop and the summary we authored with our colleagues [8], as well as discussions and developments in the eventful time since.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Leakage Reduces Device Coherence Demands for Pulse-Level Molecular Simulations

Quantum simulation on noisy intermediate-scale quantum devices is severely limited by short qubit coherence times. A variational pulse-shaping algorithm known as ctrl-VQE was recently proposed to address this issue by eliminating the need for parameterized quantum circuits, which lead to long state preparation times. Here, in this study, we find the fastest possible pulses that prepare target molecular wave functions for a given device Hamiltonian describing coupled transmon qubits using simulations. We find that the resulting time-optimal pulses develop a bang-bang form consistent with Pontryagin’s maximum principle. We further investigate how the minimal state preparation time is impacted by the number of energy levels active in the transmon simulations. We find that leakage outside the computational subspace (something that is usually considered problematic) speeds up the state preparation, further reducing device coherence-time demands. Our analysis reveals that this speedup is due to both an enlarged solution space of target wave functions and the appearance of additional channels connecting initial and target states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1997

Application-Controlled Demand Paging for Out-of-Core Visualization

In the area of scientific visualization, input data sets are often very large. In visualization of Computational Fluid Dynamics (CFD) in particular, input data sets today can surpass 100 Gbytes, and are expected to scale with the ability of supercomputers to generate them. Some visualization tools already partition large data sets into segments, and load appropriate segments as they are needed. However, this does not remove the problem for two reasons: 1) there are data sets for which even the individual segments are too large for the largest graphics workstations, 2) many practitioners do not have access to workstations with the memory capacity required to load even a segment, especially since the state-of-the-art visualization tools tend to be developed by researchers with much more powerful machines. When the size of the data that must be accessed is larger than the size of memory, some form of virtual memory is simply required. This may be by segmentation, paging, or by paged segments. In this paper we demonstrate that complete reliance on operating system virtual memory for out-of-core visualization leads to poor performance. We then describe a paged segment system that we have implemented, and explore the principles of memory management that can be employed by the application for out-of-core visualization. We show that application control over some of these can significantly improve performance. We show that sparse traversal can be exploited by loading only those data actually required. We show also that application control over data loading can be exploited by 1) loading data from alternative storage format (in particular 3-dimensional data stored in sub-cubes), 2) controlling the page size. Both of these techniques effectively reduce the total memory required by visualization at run-time. We also describe experiments we have done on remote out-of-core visualization (when pages are read by demand from remote disk) whose results are promising.

Cox, Michael↗

DOE OSTI2020

Dynamic load balancing with enhanced shared-memory parallelism for particle-in-cell codes

Furthering our understanding of many of today’s interesting problems in plasma physics – including plasma based acceleration and magnetic reconnection with pair production due to quantum electrodynamic effects – requires large-scale kinetic simulations using particle-in-cell (PIC) codes. However, these simulations are extremely demanding, requiring that contemporary PIC codes be designed to efficiently use a new fleet of exascale computing architectures. To this end, the key issue of parallel load balance across computational nodes must be addressed. We discuss the implementation of dynamic load balancing by dividing the simulation space into many small, self-contained regions or ‘‘tiles,’’ along with shared-memory (e.g., OpenMP) parallelism both over many tiles and within single tiles. The load balancing algorithm can be used with three different topologies, including two space-filling curves. Here, we tested this implementation in the code Osiris and show low overhead and improved scalability with OpenMP thread number on simulations with both uniform load and severe load imbalance. Compared to other load-balancing techniques, our algorithm gives order-of-magnitude improvement in parallel scalability for simulations with severe load imbalance issues.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Forecast-based stochastic optimization for a load powered by wave energy

Not Available

Dillon, Trent (ORCID:0000000201036449)↗

DOE OSTI2023

Exploring Future Storage Options for ATLAS at the BNL/SDCC facility

The ATLAS experiment is expected to deliver an unprecedented amount of scientific data in the High Luminosity(HL-LHC) era. As the demand for disk storage capacity in ATLAS continues to rise steadily, the BNL Scientific Data and Computing Center (SDCC) faces challenges in terms of cost implications for maintaining multiple disk copies and adapting to the coming ATLAS storage requirements. To address these challenges, the SDCC Storage team has undertaken a thorough analysis of the ATLAS experiment's requirements, matching them to suitable storage options and strategies, and has explored alternatives to enhance or replace the current storage solution. This paper aims to present the main challenges encountered while supporting big data experiments such as ATLAS. We describe the experiment's specific requirements and priorities, particularly focusing on the critical storage system characteristics of the high-luminosity run and how the key storage components provided by the Storage team work together: the dCache disk storage system; its archival back-end, HPSS; and its OS-level backend Storage. Specifically, we investigate a novel approach to integrate Lustre and XRootD. In this setup, Lustre serves as backend storage and XRootD acts as an access layer frontend, supporting various grid access protocols. Additionally, we also describe the validation and commissioning tests, including the performance comparison between dCache and XRootd. Furthermore, we provide a performance and cost analysis comparing OpenZFS and LINUX MD RAID, evaluate different storage software stacks, and showcase stress tests conducted to validate Third Party Copy (TPC) functionality.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Simulations of future particle accelerators: issues and mitigations

The ever increasing demands placed upon machine performance have resulted in the need for more comprehensive particle accelerator modeling. Computer simulations are key to the success of particle accelerators. Many aspects of particle accelerators rely on computer modeling at some point, sometimes requiring complex simulation tools and massively parallel supercomputing. Examples include the modeling of beams at extreme intensities and densities (toward the quantum degeneracy limit), and with ultra-fine control (down to the level of individual particles). In the future, adaptively tuned models might also be relied upon to provide beam measurements beyond the resolution of existing diagnostics. Much time and effort has been put into creating accelerator software tools, some of which are highly successful. However, there are also shortcomings such as the general inability of existing software to be easily modified to meet changing simulation needs. In this paper possible mitigating strategies are discussed for issues faced by the accelerator community as it endeavors to produce better and more comprehensive modeling tools. This includes lack of coordination between code developers, lack of standards to make codes portable and/or reusable, lack of documentation, among others.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

HPC-PATTERNS

This repository consists of various code examples demonstrating common patterns used in High-Performance Computing (HPC). Indeed, examples showcasing innovative usage of newly developed capabilities of HPC libraries are highly demanded by the HPC community. This repository's goal is to fulfill those requests.

APPLENCOURT, THOMAS↗

DOE OSTI2026

Simplifying Geospatial Workflows with GeoGridFusion

Growing demands to understand PV deployment and reliability across an expanding range of climates, along with increasing computational power, are driving the need for simplified computing tools that support large-scale analysis and geospatial workflows. While existing open-source libraries and PV system modeling tools offer extensive collections of empirical and physical models, they often lack the ability to scale to large geospatial datasets. The tool presented here, GeoGridFusion, enables PV modelers to store and utilize gridded geospatial data from sources such as NSRDB, PVGIS, and others. GeoGridFusion harmonizes diverse datasets, taxonomies, and nomenclatures, and includes utilities that support intuitive geospatial area selection.

14 SOLAR ENERGY↗

NASA NTRS1983

Influence of sampling rate on the calculated fidelity of an aircraft simulation

One of the factors that influences the fidelity of an aircraft digital simulation is the sampling rate. As the sampling rate is increased, the calculated response of the discrete representation tends to coincide with the response of the corresponding continuous system. Because of computer limitations, however, the sampling rate cannot be increased indefinitely. Moreover, real-time simulation requirements demand that a finite sampling rate be adopted. In view of these restrictions, a study was undertaken to determine the influence of sampling rate on the response characteristics of a simulated aircraft describing short-period oscillations. Changes in the calculated response characteristics of the simulated aircraft degrade the fidelity of the simulation. In the present context, fidelity degradation is defined as the percentage change in those characteristics that have the greatest influence on pilot opinion: short period frequency omega, short period damping ratio zeta, and the product omega zeta. To determine the influence of the sampling period on these characteristics, the equations describing the response of a DC-8 aircraft to elevator control inputs were used. The results indicate that if the sampling period is too large, the fidelity of the simulation can be degraded.

Howard, J. C.↗

NASA NTRS1983

Influence of sampling rate on the calculated fidelity of an aircraft simulation

Howard, J. C.↗

NASA NTRS1985

Expanding role for autonomy in military space

The Jet Propulsion Laboratory is currently transferring satellite on-board autonomy technology to the USAF for use in military spacecraft as a means of lowering the ground support requirements. The techniques were proven on the Viking and Voyager spacecraft and permitted on-board fault detection and correction. New military satellites will incorporate an autonomous redundancy and maintenance management subsystem in an on-board computer, while the system will still be subject to ground-based safing commands for situations demanding deeper analyses. A level 5 autonomy will need 256 kb memory, 10 Mb nonvolatile data storage and 50 W power and will weigh 20 kg. Systems will be periodically checked and compared with an ideal in the data base. Deviations detected will result in a rollback and redundant examination by two microprocessors, which can initiate correction commands until operational criteria are met. The development of the expert systems to the point that they satisfy military specifications is expected to take 10 yr.

Evans, D. D.↗

NASA NTRS1993

Superfluid Helium On-Orbit Transfer (SHOOT) flight demonstration

The Superfluid Helium On-Orbit Transfer (SHOOT) Flight Demonstration was an attached Shuttle payload mounted on a Hitchhiker cross-bay carrier which flew on STS-57 in June of 1993. SHOOT successfully demonstrated the handling and transfer of superfluid helium between two containers, called dewars, in low gravity. SHOOT was a class C payload and for the STS-57 mission was termed a complex secondary payload. The primaries were the retrieval of the EURECA carrier and a collection of modular experiments contained in SPACEHAB. Because the liquid helium was continuously boiling off, SHOOT's activities were scheduled for the first three days of the mission, concurrent with some SPACEHAB experiments, but well before the EURECA retrieval. Control of the SHOOT experiment was highly interactive and originated primarily from the Goddard Payload Operations and Control Center (POCC). Transfer and calibration activities required continuous command windows of up to 50 minutes duration and up to 80 minutes out of each orbit. Occasionally the crew controlled the experiment using the Payload General Support Computer (PGSC) when near-real time control and monitoring was required. SHOOT also placed considerable demands on the orbiter, including a pitch rotation of 3 deg./sec for 15 minutes, and translational burns using both the aft and forward RCS jets to generate accelerations up to 7 milli-g. The basis for these and other requirements are discussed. Interacion with the crew and timing of crew activity during the mission will be detailed. The processing flow of SHOOT at KSC is described with emphasis on the tradeoffs for vertical, as opposed to horizontal, installation in the orbiter. Finally, some lessons learned are presented that are relevant to future cryogenic and Hitchhiker payloads.

Shirron, Peter↗

NASA NTRS2000

Autonomy for Constellation

The newer types of space systems, which are planned for the future, are placing challenging demands for newer autonomy concepts and techniques. Motivating these challenges are resource constraints. Even though onboard computing power will surely increase in the coming years, the resource constraints associated with space-based processes will continue to be a major factor that needs to be considered when dealing with, for example, agent-based spacecraft autonomy. To realize "economical intelligence", i.e., constrained computational intelligence that can reside within a process under severe resource constraints (time, power, space, etc.), is a major goal for such space systems as the Nanosat constellations. To begin to address the new challenges, we are developing approaches to constellation autonomy with constraints in mind. Within the Agent Concepts Testbed (ACT) at the Goddard Space Flight Center we are currently developing a Nanosat-related prototype for the first of the two-step program.

Truszkowski, Walt↗

NASA NTRS2011

System Identification Applied to Dynamic CFD Simulation and Wind Tunnel Data

Demanding aerodynamic modeling requirements for military and civilian aircraft have provided impetus for researchers to improve computational and experimental techniques. Model validation is a key component for these research endeavors so this study is an initial effort to extend conventional time history comparisons by comparing model parameter estimates and their standard errors using system identification methods. An aerodynamic model of an aircraft performing one-degree-of-freedom roll oscillatory motion about its body axes is developed. The model includes linear aerodynamics and deficiency function parameters characterizing an unsteady effect. For estimation of unknown parameters two techniques, harmonic analysis and two-step linear regression, were applied to roll-oscillatory wind tunnel data and to computational fluid dynamics (CFD) simulated data. The model used for this study is a highly swept wing unmanned aerial combat vehicle. Differences in response prediction, parameters estimates, and standard errors are compared and discussed

Murphy, Patrick C.↗