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At least 361 records · Page 20

Scatter gather using key-value store

Scatter gather operation(s) are performed by accessing a shared memory that is shared amongst nodes interconnected through network(s) and having a CNS shared amongst the nodes. Data is gathered from multiple processes at corresponding multiple nodes into location(s) in the CNS, and tuple(s) having a same tuple name are created in the CNS. The tuple(s) have information referencing the gathered data in the location(s). Alternatively, data that has been gathered using the same tuple name is scattered to multiple processes participating in the CNS. The scattering uses the tuple(s) in the CNS, and is performed from the location(s) into other location(s) at one or multiple nodes for one or multiple processes at the corresponding one or multiple nodes. Both the gathering data and the scattering data may also be performed.

Jacob, Philip↗

Hybrid feature-driven learning system for abnormality detection and localization

A cyber-physical system may have a plurality of monitoring nodes each generating a series of current monitoring node values over time representing current operation of the system. A data-driven features extraction computer platform may receive the series of current monitoring node values and generate current data-driven feature vectors based on the series of current monitoring node values. A residual features extraction computer platform may receive the series of current monitoring node values, execute a system model and utilize a stochastic filter to determine current residual values, and generate current residual-driven feature vectors based on the current residual values. An abnormal detection platform may then receive the current data-driven and residual-driven feature vectors and compare the current data-driven and residual-driven feature vectors with at least one decision boundary associated with an abnormal detection model. An abnormal alert signal may then be transmitted when appropriate based on a result of said comparison.

Abbaszadeh, Masoud↗

Scalable access to shared files in a distributed system

Logic may pre-populate cache of compute nodes allocated to a user's session. Logic may access an image file of a global filesystem, the image file to comprise a first set of one or more files associated with a user session and a second set of one or more files upon which execution of the first set will depend. Logic may store the image file in local data storage of each compute node of a spanning tree of compute nodes allocated for the user session. Logic may unpack the image file based on the data. Logic may configure the local environment of each compute node in the spanning tree to identify a location in local memory of each of the files. And logic may initiate execution of a local filesystem service in each of the compute nodes of the spanning tree.

Oganezov, Alexander↗

Resilient Observer Design for Cyber-Physical Systems with Data-Driven Measurement Pruning

Resilient observer design for Cyber-Physical Systems (CPS) in the presence of adversarial false data injection attacks (FDIA) is an active area of research. The existing state-of-the-art algorithms tend to break down as more and more knowledge of the system is built into the attack model; also as the percentage of attacked nodes increases. From the view of optimization theory, the problem is often cast as a classical error correction problem for which a theoretical limit of has been established as the maximum percentage attacked nodes for which state recovery is guaranteed. Beyond this limit, the performance of -minimization based schemes, for instance, deteriorates rapidly. Similar performance degradation occurs for other types of resilient observers beyond certain percentages of attacked nodes. In order to increase the corresponding percentage of attacked nodes for which state recoveries can be guaranteed, researchers have begun to incorporate prior information into the underlying resilient observer design framework. For the most pragmatic cases, this prior information is often obtained through a data-driven machine learning process. Existing results have shown a strong positive correlation between the maximum attacked percentages that can be tolerated and the accuracy of the data-driven model. Motivated by these results, this chapter examines the case for pruning algorithms designed to improve the Positive Prediction Value (PPV) of the resulting prior information, given stochastic uncertainty characteristics of the underlying machine learning model. Theoretical quantification of the achievable improvement is given. Simulation results show that the pruning algorithm significantly increases the maximum correctable percentage of attacked nodes, even for machine learning model whose prediction power is comparable to the random flip of a coin.

Resilient Observer, Cyber-physical Systems, Data-D↗

Explainable Graph Learning for Particle Accelerator Operations

Particle accelerators are vital tools in physics, medicine, and industry, requiring precise tuning to ensure optimal beam performance. However, real-world deviations from idealized simulations make beam tuning a time-consuming and error-prone process. In this work, we propose an explanation-driven framework for providing actionable insight into beamline operations, with a focus on the injector beamline at the Continuous Electron Beam Accelerator Facility (CEBAF). We represent beamline configurations as heterogeneous graphs, where setting nodes represent elements that human operators can actively adjust during beam tuning, and reading nodes passively provide diagnostic feedback. To identify the most influential setting nodes responsible for differences between any two beamline configurations, our approach first predicts the resulting changes in reading nodes caused by variations in settings, and then learns importance scores that capture the joint influence of multiple setting nodes. Experimental results on real-world CEBAF injector data demonstrate the framework’s ability to generate interpretable insights that can assist human operators in beamline tuning and reduce operational overhead.

Wang, Song [Univ. of Virginia, Charlottesville, VA↗

$\mathrm{RADICAL}$-Pilot and $\mathrm{PMIx}$/$\mathrm{PRRTE}$: Executing Heterogeneous Workloads at Large Scale on Partitioned $\mathrm{HPC}$ Resources

Execution of heterogeneous workflows on high-performance computing (HPC) platforms present unprecedented resource management and execution coordination challenges for runtime systems. Task heterogeneity increases the complexity of resource and execution management, limiting the scalability and efficiency of workflow execution. Re-source partitioning and distribution of tasks execution over portioned re-sources promises to address those problems but we lack an experimental evaluation of its performance at scale. Here this paper provides a performance evaluation of the Process Management Interface for Exascale (PMIx) and its reference implementation PRRTE on the leadership-class HPC plat-form Summit, when integrated into a pilot-based runtime system called RADICAL-Pilot. We partition resources across multiple PRRTE Distributed Virtual Machine (DVM) environments, responsible for launching tasks via the PMIx interface. We experimentally measure the work-load execution performance in terms of task scheduling/launching rate and distribution of DVM task placement times, DVM startup and termination overheads on the Summit leadership-class HPC platform. Integrated solution with PMIx/PRRTE enables using an abstracted, standardized set of interfaces for orchestrating the launch process, dynamic process management and monitoring capabilities. It extends scaling capabilities allowing to overcome a limitation of other launching mechanisms (e.g., JSM/LSF). Explored different DVM setup configurations provide insights on DVM performance and a layout to leverage it. Our experimental results show that heterogeneous workload of 65,500 tasks on 2048 nodes, and partitioned across 32 DVMs, runs steady with resource utilization not lower than 52%. While having less concurrently executed tasks resource utilization is able to reach up to 85%, based on results of heterogeneous workload of 8200 tasks on 256 nodes and 2 DVMs.

97 MATHEMATICS AND COMPUTING↗

Distributed out-of-memory NMF on CPU/GPU architectures

We propose an efficient distributed out-of-memory implementation of the non-negative matrix factorization (NMF) algorithm for heterogeneous high-performance-computing systems. The proposed implementation is based on prior work on NMFk, which can perform automatic model selection and extract latent variables and patterns from data. In this work, we extend NMFk by adding support for dense and sparse matrix operation on multi-node, multi-GPU systems. The resulting algorithm is optimized for out-of-memory problems where the memory required to factorize a given matrix is greater than the available GPU memory. Memory complexity is reduced by batching/tiling strategies, and sparse and dense matrix operations are significantly accelerated with GPU cores (or tensor cores when available). Input/output latency associated with batch copies between host and device is hidden using CUDA streams to overlap data transfers and compute asynchronously, and latency associated with collective communications (both intra-node and inter-node) is reduced using optimized NVIDIA Collective Communication Library (NCCL) based communicators. Benchmark results show significant improvement, from 32X to 76x speedup, with the new implementation using GPUs over the CPU-based NMFk. Good weak scaling was demonstrated on up to 4096 multi-GPU cluster nodes with approximately 25,000 GPUs when decomposing a dense 340 Terabyte-size matrix and an 11 Exabyte-size sparse matrix of density 10 -6 .

97 MATHEMATICS AND COMPUTING↗

Retracted Article: Distributed energy management for networked microgrids in a three-phase unbalanced distribution network

Owing to increased penetration of three-phase and single-phase microgrids, distributed energy resources (DERs), and responsive loads, the maintenance of a three-phase balance by distribution networks is a significant challenge. Existing literature on distributed energy management for networked microgrids generally neglects the distribution network or employs a simplified phase balanced distribution network; thus, these evaluations are not applicable. Further, the underlying mutual coupling between the different phases of distribution feeders results in a more challenging situation. Here, to solve this issue, this study sought to propose distributed energy management based on a three-phase unbalanced distribution network. Various three-phase or single-phase microgrids, utility-owned DERs, and responsive loads were coordinated through iteratively adjusted price signals. Based on the price signals received, the microgrid controllers (MCs) and distribution management system (DMS) updated the schedules of the DERs and responsive loads under their jurisdiction separately. The price signals were then updated according to the generation-load mismatch at each node and distributed to the corresponding MCs and DMS for the next iteration. The iteration continued until a sufficiently small generation-load mismatch was achieved at all nodes, that is, a balanced generation and load at all nodes under the agreed price signals. Considering a three-phase unbalanced distribution network, the price signals were determined per phase per node. Overall, the proposed distributed energy management coordinates microgrids, utility-owned DERs, responsive loads with guaranteed network constraints, and preserves the privacy of microgrid customers. This distributed energy management method was further demonstrated through various case studies on a three-phase networked microgrid test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Intersection-distribution-based remapping between arbitrary meshes for staggered multi-material arbitrary Lagrangian-Eulerian hydrodynamics

In this paper, we present a new intersection-distribution-based remapping method between arbitrary polygonal meshes for indirect staggered multi-material arbitrary Lagrangian-Eulerian hydrodynamics. All cell-centered material quantities are conservatively remapped using intersections between the Lagrangian (old, source) mesh and the rezoned (new, target) mesh. The new nodal masses are obtained by conservative distribution of all material masses in each new cell to the cell's corners and then collecting those corner masses at new nodes. This distribution is done using a local constrained optimization approach for each cell in the new mesh. In order to remap nodal momentum we first define cell-centered momentum for each cell in the old mesh, conservatively remap this to the new mesh and then conservatively distribute the new zonal momentum to each cell's bounding nodes, again using local constrained optimization. Our method also conserves total energy by applying a new nodal kinetic energy correction that relies on a process similar to that used for remapping nodal mass and momentum. Cell-centered kinetic energy is computed, conservatively remapped and then distributed to nodes. The discrepancy between this conservatively remapped and actual nodal kinetic energy is then conservatively distributed to the internal energies of the materials in the cells surrounding each node. Unlike conventional cell-based corrections of this type, this new nodal kinetic energy correction has not been observed to drive material internal energy negative in any of our testing. Unlike flux based remapping, our new intersection-distribution method can be applied to remapping between source and target meshes that are arbitrarily different, which provides superior flexibility in the rezoning strategy. Our method is accurate, essentially conservative and essentially bounds preserving.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Structural Features of Zirconium-Based Metal–Organic Frameworks Affecting Radiolytic Stability

Metal–organic frameworks (MOFs) NU-1000 and UiO-66 are herein exposed to two different gamma irradiation doses and dose rates and analyzed to determine the structural features that affect their stability in these environments. MOFs have shown promise for the capture and sensing of off-gases at civilian nuclear energy reprocessing sites, nuclear waste repositories, and nuclear accident locations. However, little is understood about the structural features of MOFs that contribute to their stability levels under the ionizing radiation conditions present at such sites. This study is the first of its kind to explore the structural features of MOFs that contribute to their radiolytic stability. Both NU-1000 and UiO-66 are MOFs that contain Zr metal-centers with the same metal absorption cross section. However, the two MOFs exhibit different linker connectivities, linker aromaticities, node densities, node connectivities, and interligand separations. In this study, NU-1000 and UiO-66 were exposed to high (423.3 Gy/min, 23 min, and 37 s) and low (0.78 Gy/min, 4320 min) dose rates of 60 Co gamma irradiation. NU-1000 displayed insignificant radiation damage under both dose rates due to its high linker connectivity, low node density, and low node connectivity. However, low radiation dose rates caused considerable damage to UiO-66, a framework with lower aromaticity and smaller interligand separation. Finally, results suggest that chronic, low-radiation environments are more detrimental to Zr MOF stability than acute, high-radiation conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental Investigation of Thermodynamic Stabilization in Boron Imidazolate Frameworks (BIFs) Synthesized by Mechanochemistry

This study experimentally explores the energetics for the formation of boron–imidazolate frameworks (BIFs), which are synthesized by mechanochemistry. The topologically similar frameworks employ the same tetratopic linker based on tetrakis(imidazolyl)boric acid but differ in the monovalent cation metal nodes. This permits assessment of the stabilizing effect of metal nodes in frameworks with sodalite (SOD) and diamondoid (dia) topologies. The enthalpy of formation from endmembers (metal oxide and linker), which define thermodynamic stability of the structures, has been determined by use of acid solution calorimetry. The results show that heavier metal atoms in the node promote greater energetic stabilization of denser structures. Overall, in BIFs the relation between cation descriptors (ionic radius and electronegativity) and thermodynamic stability depends on framework topology. Thermodynamic stability increases with the metallic character of the cation employed as the metal node, independent of the framework topology. In conclusion, the results suggest unifying aspects for thermodynamic stabilization across MOF systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photooxidation of Organic Sulfide Enhanced by Heavy Atom Effect in Porphyrin Metal–Organic Frameworks with a Sea Topology

The photoactivity of three porphyrin-based metal-organic frameworks (PMOFs) incorporating Al, Ga, and In nodes was systematically evaluated using the photooxidation of an organic sulfide (2-chloroethyl ethyl sulfide, or CEES; a mustard gas simulant). Faster photodegradation of CEES was observed for PMOFs with heavier metal nodes, placing In-PMOF as the most efficient photocatalyst in the series. Guided by this insight, we developed CSLA-10, a MOF integrating In nodes and Sn-doped porphyrin linker to synergistically amplify heavy-atom effects at both the nodes and ligand levels. CSLA-10 exhibited the fastest reported CEES photooxidation to date, achieving a half-life of 38 s in methanol under blue LED irradiation. When grafted onto textiles, CSLA-10 enabled solvent-free CEES degradation in air/O 2 with a half-life of 2.7 min and complete conversion within 7 min, representing the most rapid full degradation reported under solvent-free conditions. Furthermore, this work establishes a dual heavy-atom strategy for enhancing intersystem crossing and singlet oxygen generation in porphyrin MOFs, providing a rational design principle for next-generation photocatalysts for the degradation of toxic organic sulfides.

Metal-organic frameworks↗

Unexpected “Spontaneous” Evolution of Catalytic, MOF-Supported Single Cu(II) Cations to Catalytic, MOF-Supported Cu(0) Nanoparticles

A desirable feature of metal–organic frameworks (MOFs) is their well-defined structural periodicity and the presence of well-defined catalyst grafting sites (e.g., reactive –OH and –OH 2 groups) that can support single-site heterogeneous catalysts. However, one should not overlook the potential role of residual organic moieties, specifically formate ions that can occupy the catalyst anchoring sites during MOF synthesis. Here we show how these residual formate species in a Zr-based MOF, NU-1000, critically alter the structure, redox capability, and catalytic activity of postsynthetically incorporated Cu(II) ions. Single-crystal X-ray diffraction measurements established that there are two structurally distinct types of Cu(II) ions in NU-1000: one type with residual formate and one without. In NU-1000 with formate, Cu(II) solely binds to the node via the formate-unoccupied, bridging μ 3 –OH, whereas in the formate-free case, it displaces protons from two node hydroxo ligands and resides close to the terminal –OH 2 . Under an inert atmosphere, node-bound formate facilitates the unanticipated reduction of isolated Cu(II) to nanoparticulate Cu(0)—a behavior which is essentially absent in the formate-free analogue because no other sacrificial reductant is present. When the two MOFs were tested as benzyl alcohol oxidation catalysts, we observed that residual formate boosts the catalytic turnover frequency. Density functional calculations showed that node-bound formate acts as a sacrificial two-electron donor and assists in reducing Cu(II) to Cu(0) by a nonradical pathway. The negative Gibbs free energy of reaction (ΔG) and enthalpy of reaction (ΔH) indicate that the reduction is thermodynamically favorable. Here, the work presented here highlights how the often-neglected residual formate prevalent in nearly all zirconium-based MOFs can significantly modulate the properties of supported catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing Fermi surface evolution and Berry curvature in an ideal type-II Weyl semimetal

Abstract In type-II Weyl semimetals (WSMs), the tilting of the Weyl cones leads to the coexistence of electron and hole pockets that touch at the Weyl nodes. These electrons and holes experience the Berry curvature generated by the Weyl nodes, leading to an anomalous Hall effect that is highly sensitive to the Fermi level position. Here we have identified field-induced ferromagnetic MnBi 2-x Sb x Te 4 as an ideal type-II WSM with a single pair of Weyl nodes. By employing a combination of quantum oscillations and high-field Hall measurements, we have resolved the evolution of Fermi-surface sections as the Fermi level is tuned across the charge neutrality point, precisely matching the band structure of an ideal type-II WSM. Furthermore, the anomalous Hall conductivity exhibits a heartbeat-like behavior as the Fermi level is tuned across the Weyl nodes, a feature of type-II WSMs that was long predicted by theory. Our work uncovers a large free carrier contribution to the anomalous Hall effect resulting from the unique interplay between the Fermi surface and diverging Berry curvature in magnetic type-II WSMs.

36 MATERIALS SCIENCE↗

On-demand directional microwave photon emission using waveguide quantum electrodynamics

Routing quantum information between non-local computational nodes is a foundation for extensible networks of quantum processors. Quantum information transfer between arbitrary nodes is generally mediated either by photons that propagate between them or by resonantly coupling nearby nodes. The utility is determined by the type of emitter, propagation channel and receiver. Conventional approaches involving propagating microwave photons have limited fidelity due to photon loss and are often unidirectional, whereas architectures that use direct resonant coupling are bidirectional in principle but can generally accommodate only a few local nodes. Here we demonstrate high-fidelity, on-demand, directional, microwave photon emission. We do this using an artificial molecule comprising two superconducting qubits strongly coupled to a bidirectional waveguide, effectively creating a chiral microwave waveguide. Quantum interference between the photon emission pathways from the molecule generates single photons that selectively propagate in a chosen direction. This circuit will also be capable of photon absorption, making it suitable for building interconnects within extensible quantum networks.

42 ENGINEERING↗

Topologically distinct Weyl fermion pairs

Abstract A Weyl semimetal has Weyl nodes that always come in pairs with opposite chiralities. Notably, different ways of connection between nodes are possible and would lead to distinct topologies. Here we identify their differences in many respects from two proposed models with different vorticities. One prominent feature is the behaviour of zeroth Landau levels (LLs) under magnetic field. We demonstrate that the magnetic tunneling does not always expel LLs from zero energy because the number of zero-energy modes is protected by the vorticity of the Weyl nodes, instead of the chirality. Other respects in disorder effects for weak (anti-)localization, surface Fermi arcs, and Weyl-node annihilation, are interesting consequences that await more investigation in the future.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Strikingly high amount of tricin-lignin observed from vanilla (Vanilla planifolia) aerial roots

Lignin has attracted tremendous interest as a renewable resource for biofuels, biomaterials, and chemicals especially in the era of bio-based refineries. The structural studies of lignin play an essential role in both understanding the nature and biosynthesis of these polymers and optimizing their valorization values. In this study, we have investigated the structures of lignin from different tissues—aerial roots, nodes, internodes, and seeds, from vanilla (Vanilla planifolia) by using gel permeation chromatography (GPC), heteronuclear single-quantum coherence (HSQC) nuclear magnetic resonance (NMR), and 31P NMR. An unusual tricin-lignin was observed in the aerial roots of vanilla with an strikingly high level of tricin unit, whereas the lignin from the nodes and internodes displayed traditional S/G type lignin with only 4–10% tricin abundance. The aerial roots lignin is primarily composed of β-O-4' alkyl-aryl ether substructures (96% of linkages) in comparison to 65 and 73% in the nodes and internodes lignin, respectively. Additionally, thioacidolysis quantification results showed that lignin from aerial roots has 29.1 mg g -1 tricin, about 3- to 5-fold higher than the lignins isolated from nodes (10.1 mg g -1 ) and internodes (6.9 mg g -1 ). This communication of a particularly high level of tricin-lignin in vanilla plant has important impacts including: (1) the presence of the high amount of tricin as part of lignin from aerial roots could play a vital role for the valorization of lignin, even tricin itself, as a feedstock for value-added chemicals and commodities; and (2) it could open new ways to scientists to design and engineer the structure of tricin-lignin, or lignin in general, to confer plants with new or improved properties due to the plasticity of lignification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗