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1,142 records · Page 64

Lustre Unveiled: Evolution, Design, Advancements, and Current Trends

The Lustre filesystem serves as a vital element in high-performance parallel storage, meeting the rising demands of scientific, research, and enterprise environments. Widely deployed across HPC environments, ranging from small-scale applications in AI/ML, to domains like oil and gas, drug discovery, and meteorology, and manufacturing, Lustre addresses the universal challenge of efficiently accessing vast and ever-increasing volumes of data. Lustre is the filesystem of choice on six out of the top 10 fastest supercomputers in the world today, over 65% of the top 100, and also for over 60% of the top 500. Despite its widespread popularity, there is a lack of a complete and up-to-date reference, covering Lustre’s evolution, design, and various advancements made over the years. In this journal, we aim to fill this gap by providing a comprehensive journey of Lustre, including its history with significant contributions to HPC, detailed architecture and design elements, exploration of advancements added through its evolution, and future directions. Additionally, we present a comparison of Lustre with other prominent storage technologies of the era. To illustrate the current state of Lustre, we analyze several filesystem trends, including utilization, performance, and usage patterns on Orion, the Lustre filesystem on the first exascale supercomputer Frontier. We hope that this journal serves as a comprehensive educational reference for the current and future generations interested in HPC filesystem storage aspects.

97 MATHEMATICS AND COMPUTING↗

NASA’s Moon Trek Portal: New Capabilities Supporting Mission Planning and Engagement

Introduction: NASA’s Moon Trek (https://trek.nasa.gov/moon/) is one of a growing number of interactive, browser-based, online portals for planetary data visualization and analysis produced by NASA’s Solar System Treks Project (SSTP). Moon Trek continues to be enhanced with new data and new capabilities enabling it to facilitate the planning and conducting of upcoming lunar missions by NASA, its commercial partners, and its international partners, as well as advancing its role as a valuable outreach tool. A Comprehensive Online Web Portal: Developed at NASA’s Jet Propulsion Laboratory (JPL) and managed as a project of NASA’s Solar System Exploration Research Virtual Institute (SSERVI) at NASA Ames Research Center, Moon Trek is a browser-based web portal. The portal provides easy-to-use tools for browsing, data layering, data product blending, and feature search among thousands of data products covering topography, mineralogy, elemental abundance, geology, and much more. Visualizations are provided in var-ious map projections, interactive 3D viewing, and in virtual reality. Using an in-house stereo workflow, SSTP is able to produce new NAC-based high-resolution mosaics and DEMs. Diverse Applications for Lunar Exploration: Baseline analytic tools available to all users include dis-tance measurement, elevation profiling, sun angle calculation, and 3D print file generation. More advanced account-level tools allow users to perform more computationally intensive analyses. These include ray-traced lighting analysis for user-specified areas over user-specified time/date ranges and time intervals, electro-static surface potential analysis, subsetting of large data products, slope analysis, and Lunar Laser Ranging geometry calculation. Artificial intelligence (AI) and ma-chine learning (ML) based tools have been implemented for crater detection and hazard analysis, boulder detection and hazard analysis, and rockfall detection. New Tools Facilitating Exploration: Additional, new tools have recently been added and others are in development, offering even greater functionality in con-ducting analyses of potential landing sites and areas of surface operations. The new Line-of-Sight tool facilitates communications planning between locations on the lunar surface, between any given site on the lunar surface and a specified ground station on the Earth, and between a site on the lunar surface and a relay asset in lunar orbit, all taking into account local lunar topography. The new Data Plotter tool provides both tabular and graphical representations of pixel values along a user specified path for a growing number of data products. The new NAC Finder tool will identify and pro-vide access to NAC images that intersect a user-defined path or bounded area. The SSTP development team is looking to leverage the capabilities of its existing AI and ML crater, boulder, and rockfall detection and analysis tools, and extend that technology to a generalized feature detector that can be trained on instances of specific types of landforms and then search the lunar surface for more examples of such features. New traverse planning tools are being developed with use cases in generalized concept studies and specific mission planning in mind. These will facilitate finding optimal traverse paths based on constraints such as slope, lighting, hazard avoidance, and communications. These will be complemented by new traverse visualization capabilities. Users will be able to interactively ride along with a rover, examining 3D views of the terrain while adjusting camera height and viewing angle along with selecting different data layer overlays to drape across the terrain. Engaging the Public: The capabilities being developed for mission planning are being leveraged to further enhance Moon Trek’s proven utility as a valuable public outreach resource. This includes providing multiple lev-els of engagement with different points of entry. At its simplest level, promoting understanding through visualization, media and the public will be able to easily visualize and conduct their own exploration of lunar sites targeted by NASA and its partners. For a more in-depth experience, we are working with our stakeholders to promote understanding through interaction by extend-ing our current landing site and traverse analysis capabilities, making simplified access to these tools available to those who want to explore more deeply key factors in planning a mission through interactive and possibly even gamified experiences. The highest degree of public outreach, focusing on engagement through scientific participation, could be achieved through our work with missions and the NASA Office of the Chief Scientist on Moon Trek’s extension as a tool with specialized capabilities for facilitating citizen science. In such scenarios, participants become members of extended mis-sion science teams, using dedicated and integrated interfaces to analyze mission data to help answer questions key to lunar science and exploration. We are work-ing with NASA’s Office of Communications, museums, planetariums, and the media to help them easily integrate accurate, detailed visualizations of NASA’s lunar destinations and exploration into their content/productions and to engage diverse audiences in diverse venues.

Moon Trek↗

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

XXVIIth International Conference on Supersymmetry and Unification of Fundamental Interactions (SUSY 2019) (Final Report)

Supersymmetry (SUSY) is one of most elegant extensions of the Standard Model (SM) and explains the puzzles of the SM by providing a candidate to explain the dark matter content of the universe, allowing scientists to understand the origin of the electroweak scale requiring the top mass to be around 170 GeV and leading to the unification of forces at a grand unified scale. Further the minimal supersymmetric standard model (MSSM) predicts the Higgs boson mass to be less than 135 GeV. The discovery of the Higgs Boson with mass around 125 GeV at the LHC has provided a major support to SUSY ideas. Searches for SUSY are ongoing at the Large Hadron Collider (LHC). Direct and indirect dark matter experiments are searching for a particle dark matter candidate which arises most naturally in SUSY models. Proton decay predicted by SUSY grand unified theories is being searched for at deep underground experiments. In addition, recent advances in neutrino and dark matter physics, observational astrophysics, precision cosmology and the promising new window into the cosmos opened by the direct detection of gravitational waves, have brought new ideas on the potential connections between new fundamental particles and our understanding of their impact on the early universe and its evolution. At present, the major questions include: Is SUSY still the best candidate for models beyond the SM? Do we have any well motivated alternative to SUSY? Have we exhausted all possibilities to search for new physics at high and low energy scales? XXVIIth International Conference on Supersymmetry and Unification of Fundamental Interactions (SUSY 2019), hosted by Texas A&M University – Corpus Christi during May 20-24, 2019, provided a unique venue to discus and understand the status of SUSY, connection between particle physics and cosmology, supersymmetry and its alternative, Higgs sector, neutrino sector, flavor sector, dark matter, electroweak phase transition, astroparticle physics, gravitational waves and string theory. Discussion of results from the LHC, recent neutrino experiments and observations, direct and indirect dark matter detection experiments, detection of gravitational waves, data from particle colliders, as well as measurements of the CMB and Large Scale Structure were an integral part of SUSY 2019. To ensure the younger participants will benefit from the conference the most, the conference was preceded by the 4 day long pre-SUSY summer school for graduate students and postdocs. The invited speakers were leading scientists in the fields of SUSY interest. The school took place on Texas A&M University – Corpus Christi campus during the week prior the SUSY 2019 conference (May 15 – 18, 2019). Since its inception in 1993, SUSY has become one of the most important and widely attended international meetings in high energy physics, devoted to new ideas in fundamental particle physics. SUSY 2019 brought together approximately 250 scientists, theorists, phenomenologists, experimentalists and cosmologists, (including over 60 graduate students and 70 postdocs) representing 22 nations: Australia, Belgium, Canada, Chile, China, Colombia, France, Germany, India, Italy, Japan, Mexico, Peru, Portugal, Romania, South Korea, Spain, Sweden, Switzerland, Taiwan, United Kingdom and United States. SUSY 2019 provided a stimulating venue for the exchange of scientific ideas among experts in dark matter, neutrino physics, particle physics, astrophysics and cosmology. The following scientific topics were delivered during SUSY 2019 in form of 44 plenary talks and over 200 parallel talks: Unification of Forces; Electroweak, Top and Higgs Physics; Precision Calculations and MC tools; BSM in Flavor Physics; Neutrino Masses: Models and Phenomenology; Cosmology and Gravitational Waves; Dark Matter, Astroparticle Physics; Formal Field Theory and Strings; Alternatives to Supersymmetry; Quantum Information: Machine Learning/Big Data. 28 talks were given during the pre-SUSY program related to the following topics: Neutrino Physics; Big Data; Collider Physics & SUSY; String Phenomenology; Cosmology; Dark Matter; SUSY Models and Phenomenology

43 PARTICLE ACCELERATORS↗

Machine learning-driven predictive resource management in complex science workflows

Here, the collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. Recently, advanced and complex data processing has gained increasing importance in science experiments. Data processing workflows typically consist of multiple intricate steps, and the precise specification of resource requirements is crucial for each step to allocate optimal resources for effective processing. Estimating resource requirements in advance is challenging due to a wide range of analysis scenarios, varying skill levels among community members, and the continuously increasing spectrum of computing options. One practical approach to mitigate these challenges involves initially processing a subset of each step to measure precise resource utilization from actual processing profiles before completing the entire step. While this two-staged approach enables processing on optimal resources for most of the workflow, it has drawbacks such as initial inaccuracies leading to potential failures and suboptimal resource usage, along with overhead from waiting for initial processing completion, which is critical for fast-turnaround analyses. In this context, our study introduces a novel pipeline of machine learning models within a comprehensive workflow management system, the Production and Distributed Analysis (PanDA) system. These models employ advanced machine learning techniques to predict key resource requirements, overcoming challenges posed by limited upfront knowledge of characteristics at each step. Accurate forecasts of resource requirements enable informed and proactive decision-making in workflow management, enhancing the efficiency of handling diverse, complex workflows across heterogeneous resources.

97 MATHEMATICS AND COMPUTING↗

Search for solar axions produced through the axion-electron coupling gae using a new GridPix detector at CAST

We present a search for solar axions produced through the axion-electron coupling (g ae ) using data from a novel 7-GridPix detector installed at the CERN Axion Solar Telescope (CAST). The detector, featuring ultra-thin silicon nitride windows and multiple veto systems, collected approximately 160 hours of solar tracking data between 2017–2018. Using machine learning techniques and the veto systems, we achieved a background rate of 1.06 × 10 −5 keV −1 cm −2 s −1 at a signal efficiency of about 80% in the 0.2 to 8 keV range. Analysis of the data yielded no significant excess above background, allowing us to set a new upper limit on the product of the axion-electron and axion-photon couplings of g ae · g aγ < 7.35 × 10 −23 GeV −1 at 95% confidence level for axion masses below 10 meV. This result improves upon the previous best helioscope limit and demonstrates the potential of GridPix technology for rare event searches. Additionally, we derived a limit on the axion-photon coupling of g aγ < 9.0 × 10 −11 GeV −1 at 95% CL, which, while not surpassing CAST’s best limit, provides complementary constraints on axion models.

Beyond Standard Model↗

MIBiG 4.0: advancing biosynthetic gene cluster curation through global collaboration

Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in agriculture, engineering and medicine. Usually, the biosynthesis of these natural products is governed by sets of co-regulated and physically clustered genes known as biosynthetic gene clusters (BGCs). To share information about BGCs in a standardized and machine-readable way, the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard and repository was initiated in 2015. Since its conception, MIBiG has been regularly updated to expand data coverage and remain up to date with innovations in natural product research. Here, we describe MIBiG version 4.0, an extensive update to the data repository and the underlying data standard. In a massive community annotation effort, 267 contributors performed 8304 edits, creating 557 new entries and modifying 590 existing entries, resulting in a new total of 3059 curated entries in MIBiG. Particular attention was paid to ensuring high data quality, with automated data validation using a newly developed custom submission portal prototype, paired with a novel peer-reviewing model. MIBiG 4.0 also takes steps towards a rolling release model and a broader involvement of the scientific community. MIBiG 4.0 is accessible online at https://mibig.secondarymetabolites.org/.

59 BASIC BIOLOGICAL SCIENCES↗

Quantitative Characterization of Impacts of Coupled Geomechanics and Flow on Safe and Permanent Geological Storage of CO 2 in Fractured Aquifers

This is the final scientific report for the award DE-FE0023305, entitled “Quantitative Characterization of Impacts of Coupled Geomechanics and Flow on Safe and Permanent Geological Storage of CO 2 in Fractured Aquifers.” The work has been divided into six tasks. In Task 2, we characterized rock properties, which are important when developing a quantitative approach for understanding and predicting geomechanical effects on large-scale CO 2 injection and long-term storage in the subsurface. Rock properties of interest for this characterization include porosity, permeability, elastic constants, strength, and heat capacity. We measured rock properties for three different rock types: concrete, sandstone and shale. These properties were obtained from the acoustic measurement, permeability and porosity measurement, Brazilian test, the uniaxial compressive test, and heat capacity measurement. Then, using the Brazilian technique to fracture samples, we measured their permeability under brine injection for varying effective stresses, followed by similar measurements of permeability under sc-CO 2 injection. Permeability to brine and sc-CO 2 decreased as the effective stress increased. The apparent permeability to sc-CO 2 was an order of magnitude less than that for brine, a consequence of CO 2 being the non-wetting fluid. In Task 3, we developed understandings and correlations for CO 2 injection pressure induced fracturing. We initially fractured four eight inch cubes of concrete with brine to establish a standard test procedure. Then, additional concrete samples were fractured using brine. Confining stresses were exerted on the samples and brine was injected at a constant rate into a borehole that was previously drilled into the concrete cube. The borehole pressure was measured and fracture initiation was identified as a peak in the pressure profile. That was followed by fracture propagation, which was identified as a plateau in the pressure profile, and finally the fracture reached the sample surface. The sample surfaces were photographed before and after fracturing, which enabled determination of where the fracture reached the sample surface. Afterwards, aqueous food dye solution was injected into the fractured concrete samples to color the fracture planes. The borehole was filled with food dye solution in advance, a gas pulse was transmitted to the borehole, and the borehole was then shut in to allow the food dye to be driven into existing fractures. Then, the concrete samples were broken down by high-pressure gas injection to reveal the geometry and morphology of the hydraulic fractures. In addition, acoustic measurements were conducted on multiple locations on each face of the concrete samples before and after injection for comparison. This comparison was used to confirm changes in the internal structure of the concrete sample, namely the formation of fractures. There were six concrete samples fractured with brine. Afterwards, concrete samples were fracture using sc-CO 2 . The main change in experimental procedure was the inclusion of temperature control, since in the field, we mostly encounter temperature and pressure conditions above the supercritical point of CO 2 . The concrete samples were pre-heated in an oven to elevate their temperature, and thermal tape was used to heat the CO 2 to a temperature above its supercritical temperature. Two concrete samples were fractured using liquid CO 2 , four concrete samples were fractured using gaseous CO 2 , and twenty two concrete samples were fractured using sc-CO 2 . For the concrete samples fractured using sc-CO 2 , three had pre-existing hydraulic fractures on the surface near the wellbore, and two were water saturated (as opposed to containing only air). Two concrete samples were composite samples, with a high permeability ball in the center, in order to represent CO 2 injection into a high permeability zone surrounded by a low permeability sealing formation. Later, we fractured five shale samples, obtained from the Niobrara shale outcrop, with sc-CO 2 . The injection rate was constant, confining stresses were applied, the shale samples were pre-heated in an oven to the desired temperature, and the sample was then fractured. An analysis of the failure type was done for many of the concrete samples, based on the predicted break down pressure for tensile and shear failure, and it was found that most samples fractured due to shear failure. Also, the presence of induced fractures has little to no effect on the fracture initiation pressure, but significantly changes the fracture morphology. The CO 2 fracturing in water saturated samples behaved much similar to brine induced fracturing. There was a significant difference of breakdown pressure for injection of CO 2 and brine, where the breakdown pressure for CO 2 induced fracturing is generally around the minimum horizontal stress and that for brine is much higher. Finally, the fracture orientation for most samples with large confining stress differential was perpendicular to the minimum horizontal stress. When the stress differential, especially the difference between the two directions with the smallest stresses was small, the fracture orientation was determined not only by the minimum stress direction, but also the magnitude of the confining stress, the tensile strength of the rock, and the breakdown pressure. In Task 4, we modified our coupled flow-geomechanical models to model fracture growth and propagation in storage formations and caprocks. These flow-geomechanical models are TOUGH2-CSM and TOUGH2-FLAC. The TOUGH2-CSM fluid and heat flow formulation is based on the TOUGH2 formulation of mass and energy conservation equations that govern fluid and heat flow in general multiphase, multicomponent, multi-porosity systems. The TOUGH2-CSM simplified geomechanical formulation is based on the linear theory of elasticity applied to multi-porosity non-isothermal (thermo-multi-poroelastic) media. We previously derived, from the fundamental relations of the linear theory of elasticity, an equation relating mean stress, pore pressures, temperatures, and body force (the Mean Stress equation) that we added to the TOUGH2-CSM fluid and heat flow equations. We extended the TOUGH2-CSM simplified geomechanical formulation to calculate the entire stress tensor by deriving equations for stress tensor components from derivatives of the Cartesian thermo-multi-poroelastic Navier equation components. In addition, we derived equations for stress tensor components in rz-coordinates. We solved these geomechanical equations using the integral finite difference method. This method utilizes momentum fluxes obtained by “factoring” a divergence operator out of each geomechanical equation. In Task 5, we did a literature survey to determine suitable correlations for fracture initiation, growth, and propagation. After surveying numerous papers, we modified TOUGH2-CSM to model stress dependent fracture initiation and growth using the Mohr-Coulomb criterion for shear failure in faults and caprock and the condition of negative minimum effective stress for tensile failure. Tensile failure results in a fracture whose width depends on the difference between fracture pressure and minimum stress and whose propagation is based on the difference between the stress intensity factor at the fracture tip and the rock toughness. The TOUGH-FLAC model is based on the FLAC3D ubiquitous joint model, extended for the modeling of permeability changes induced by changes in effective normal stress across fractures as well permeability changes caused by shearing along fractures. In Task 6, we validated our coupled flow-geomechanical models using analytical solutions and problems from the literature. We validated the TOUGH2-CSM modifications using analytical solutions to the displacement from a uniform load on a semi-infinite elastic medium and the two-dimensional Mandel-Cryer effect. Those were followed by a sample problem to test our stress tensor calculations, which was for injection into a single-phase reservoir with constant properties. Comparisons of our simulator to published results were done on for the depletion of a single-phase reservoir with stress dependent porosity, two examples from the In Salah gas project, an axisymmetric baserock–reservoir–caprock system with a normal faulting stress regime that had thermally induced shear stresses, simulations of CO 2 leakage through caprock in a two-dimensional reservoir in Cartesian coordinates, and predictions of caprock failure from CO 2 injection into an axisymmetric reservoir. Finally, we simulated CO 2 injection pressure-induced fracturing from one of our laboratory studies, Sample 39, and obtained a fracture profile. We also validated the TOUGH2-FLAC model for fluid driven fracture growth against solutions based on the KGD model and a case with an inclined fracture that was loaded from the boundaries to achieve wing-crack propagation. The strain softening tensile behavior and softening of modulus considering a simple damage approach was verified by a simulation representing hydraulic fracturing stress measurement around a vertical well. Finally, the model was validated against deep fracture zone opening and surface uplift at In Salah with inverses analysis used to improve the match of simulation with field data. In Task 7, we developed a scheme based on inverse modeling that can be used to identify caprock leakage. Injection of fluid into a reservoir results in a time varying pressure profile that depends on the properties of the rock and the fluid. The presence of significant caprock leakage would effect this pressure profile and we used inverse modeling, namely the Levenberg-Marquardt method, to determine the leakage location from the pressure profile. A two-dimensional and a three-dimensional example based on published data were presented. The published simulation was run and its results were considered as “field” data. In the two-dimensional example, a simulation of CO 2 injection into a two-dimensional aquifer-caprock system, the caprock had a vertical fault through which leakage could occur. The location of this leakage was obtained from our inverse modeling scheme. In the three-dimensional example, the simulation domain had four geological layers, one of which was the injection zone that contained a horizontal injection well. We simulated fractures as high permeability gridblocks, introduced a fracture that spanned the caprock depth, and ran a simulation to obtain “field” data. Then, using our inverse modeling scheme, we obtained the location of that fracture.

58 GEOSCIENCES↗