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At least 253 records · Page 14

MatRIS: Addressing the Challenges for Portability and Heterogeneity Using Tasking for Matrix Decomposition (Cholesky)

The ubiquitous in-node heterogeneity of HPC and cloud computing platforms makes software portability and performance optimization extremely challenging. Described here, the MatRIS multilevel math library abstraction framework employs tasking to alleviate these difficulties. MatRIS includes the IRIS task-based runtime on the bottom level and exposes different layers of abstraction to render algorithms architecturally agnostic. MatRIS ensures the decomposition and creation of tasks that represent the necessary encapsulation of the optimized kernels from both vendor and open-source math libraries. Once built, MatRIS can select different combinations of accelerators at runtime, making it portable even on diverse heterogeneous architectures. By leveraging the IRIS runtime’s features for managing heterogeneity, MatRIS deploys algorithms that remove the need to specify orchestration and data transfer. This study describes how the serial task abstraction of a tiled Cholesky factorization is made portable and scalable in the case of multi-device and multi-vendor heterogeneity on a node with NVIDIA and AMD GPUs by using MatRIS. First, we demonstrate that Cholesky in MatRIS provides multi-GPU scalability that offers competitive performance versus cuSolverMG. Then, we present the challenges and opportunities for heterogeneous execution.

Monil, M. A. H.↗

Surrogate-Based Autotuning for Randomized Sketching Algorithms in Regression Problems

Algorithms from Randomized Numerical Linear Algebra (RandNLA) are known to be effective in handling high-dimensional computational problems, providing high-quality empirical performance as well as strong probabilistic guarantees. However, their practical application is complicated by the fact that the user needs to set various algorithm-specific tuning parameters which are different from those used in traditional NLA. This paper demonstrates how a surrogate-based autotuning approach can be used to address fundamental problems of parameter selection in RandNLA algorithms. In particular, we provide a detailed investigation of surrogate-based autotuning for sketch-and-precondition (SAP)-based randomized least squares methods, which have been one of the great success stories in modern RandNLA. Empirical results show that our surrogate-based autotuning approach can achieve near-optimal performance with much less tuning cost than a random search (up to about 7.6x fewer trials of different parameter configurations). Moreover, while our experiments focus on least squares, our results demonstrate a general-purpose autotuning pipeline applicable to any kind of RandNLA algorithm.

Cho, Younghyun↗

Field Emission Analysis in SRF Cavities for PIP-II Using GEANT4

Field emission (FE) remains a key limitation to achieving optimal performance and reliability in superconducting radiofrequency (SRF) cavities used in accelerator cryomodules. Addressing this challenge requires a detailed understanding of the generation and transport of FE-induced radiation; however, the absence of standardized measurement protocols complicates comparisons across different testing stages and facilities. This work presents initial steps toward a quantitative, systematic framework for analyzing FE-induced radiation using Geant4 simulations. We model four cavity types to be deployed in Fermilab’s Proton Improvement Plan-II (PIP-II) linac - HB650, LB650, SSR2, and SSR1 - to investigate radiation signatures and their dependence on emission conditions. By integrating simulation results with radiation diagnostics, our goal is to identify probable emission sites, enhance diagnostic accuracy, and optimize detector placement. Ultimately, this approach seeks to inform cavity preparation, assembly, and testing procedures, enabling the delivery of FE-free SRF cryomodules for PIP-II.

Wijethunga, Sajini [Fermilab] (ORCID:0000000287659↗

Field Emission Analysis in SRF Cavities for PIP-II Using GEANT4

Field emission (FE) remains a key limitation to achieving optimal performance and reliability in superconducting radiofrequency (SRF) cavities used in accelerator cryomodules. Addressing this challenge requires a detailed understanding of the generation and transport of FE-induced radiation; however, the absence of standardized measurement protocols complicates comparisons across different testing stages and facilities. This work presents initial steps toward a quantitative, systematic framework for analyzing FE-induced radiation using Geant4 simulations. We model four cavity types to be deployed in Fermilab’s Proton Improvement Plan-II (PIP-II) linac - HB650, LB650, SSR2, and SSR1 - to investigate radiation signatures and their dependence on emission conditions. By integrating simulation results with radiation diagnostics, our goal is to identify probable emission sites, enhance diagnostic accuracy, and optimize detector placement. Ultimately, this approach seeks to inform cavity preparation, assembly, and testing procedures, enabling the delivery of FE-free SRF cryomodules for PIP-II.

Wijethunga, Sajini [Fermilab] (ORCID:0000000287659↗

Microstructure‐Informed Analysis Framework for Lattice Structures: Guiding Topology‐Material Synergy in Titanium Alloys

In this work we discuss a microstructure‐informed analysis framework for lattice structures that maps the material's microstructural response to guide topology selection and mechanical performance optimization. By coupling geometrical topology with intrinsic material behavior, we demonstrate how anisotropic microstructural response can inform the design of optimized lattice structures. To illustrate this concept, we focus on two distinct classes of titanium alloys: Ti5553 (Ti‐5Al‐5Mo‐5V‐3Cr wt%), which exhibits a predominantly ‐phase microstructure, and Ti64 (Ti‐6Al‐4V wt%), which features a dual‐phase structure. These alloys exhibit markedly different mechanical responses under multiaxial loading in “fully dense” solid form. The strut‐level stress analysis of these alloys reveals how specific microstructural characteristics can guide the selection of appropriate lattice topologies. Two representative lattice configurations, one stretching‐dominated and one bending‐dominated, are evaluated under identical loading conditions to explore how microstructure‐driven design can lead to topology choices that are better suited to accommodate shear or other critical local stress states, thereby enhancing mechanical performance. A strut‐level mechanics‐based analysis is performed to evaluate shear stress distribution and highlight the role of topology‐microstructure synergy and compatibility in determining overall lattice behavior. The findings emphasize the importance of designing structures that are both load‐aware and microstructure‐responsive, enabling more effective material utilization in advanced engineering applications.

36 MATERIALS SCIENCE↗

Tunable high Néel temperature and large anomalous Hall response in antiferromagnetic Weyl semimetal Mn 3 Sn 1− x Ga x thin films

Antiferromagnetic Weyl semimetals based on Mn 3 X(X = Ge, Sn, Ga) kagome compounds exhibit the same ferromagnetic-like responses, including anomalous Hall, Nernst, and magneto-optical effects, as recently discussed for altermagnets. Driven by the Berry curvature due to Weyl fermions, these materials show a disproportionately large magnitude of electromagnetic effects even in the absence of large magnetization. For applications it is crucial to realize these responses in a wide range of temperatures both below and above 300 K. While stoichiometric Mn 3 X materials do not offer optimal performance, we show that Mn 3 Sn 1−x Ga x sputtered films with a variable composition offers a tunable Néel temperature, T N ≈ 425 ± 6–500 ± 15 K, which is crucial for device applications, together with a large tunable anomalous Hall effect. Our thin film growth method enables continuous and precise control over the film composition between x = 0 and x = 1. Through a detailed magnetization and Hall transport, we establish the magnetic phase diagram for the hexagonal Mn 3 Sn 1−x Ga x . Our results reveal an enhanced T N and antichiral magnetic phase in Ga-doped Mn 3 Sn and an enhanced anomalous Hall magnitude in Sn-doped Mn 3 Ga compared to their stoichiometric undoped forms. Our work demonstrates a route to optimize the technologically relevant antiferromagnets for various applications.

Magnetic properties and materials↗

Durable and Versatile Immobilized Carbonic Anhydrase on Textile Structured Packing for CO 2 Capture

High-performance carbon dioxide (CO 2 )-capture technologies with low environmental impact are necessary to combat the current climate change crisis. Durable and versatile “drop-in-ready” textile structured packings with covalently immobilized carbonic anhydrase (CA) were created as efficient, easy to handle catalysts for CO 2 absorption in benign solvents. The hydrophilic textile structure itself contributed high surface area and superior liquid transport properties to promote gas-liquid reactions that were further enhanced by the presence of CA, leading to excellent CO 2 absorption efficiencies in lab-scale tests. Mechanistic investigations revealed that CO 2 capture efficiency depended primarily on immobilized enzymes at or near the surface, whereas polymer entrapped enzymes were more protected from external stressors than those exposed at the surface, providing strategies to optimize performance and durability. Textile packing with covalently attached enzyme aggregates retained 100% of the initial 66.7% CO 2 capture efficiency over 71-day longevity testing and retained 85% of the initial capture efficiency after 1-year of ambient dry storage. Subsequent stable performance in a 500 h continuous liquid flow scrubber test emphasized the material robustness. Biocatalytic textile packings performed well with different desirable solvents and across wide CO 2 concentration ranges that are critical for CO 2 capture from coal and natural gas-fired power plants, from natural gas and biogas for fuel upgrading, and directly from air.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparative life cycle assessment of a modular cross-laminated timber residential building designed for disassembly and reuse versus traditional wood frame construction

There is a need for affordable housing across the U.S., with high-performance modular and prefabricated buildings providing a logical avenue for meeting some of this demand. However, there is a need to balance high performance construction – including low emissions – with affordability. To provide a proof-of-concept in meeting these goals, the Circular Home is a cross-laminated timber (CLT)-based deconstructible and reconfigurable single-family residence that meets high performance targets in moisture, energy, design, economics, and life cycle assessment (LCA). This study focuses on the LCA, presenting a cradle-to-cradle whole-building life cycle assessment (WBLCA) for the Circular Home and a functionally equivalent Baseline Home constructed with traditional materials and methods. The functional unit is 1 m 2 of gross floor area across 60 years. Revit building information models (BIM) provided material quantities and Tally LCA was utilized for impact data (inclusive of biogenic carbon sequestration), supplemented with manufacturer environmental product declarations (EPDs). The Circular Home outperforms the baseline residence in most measured impact categories, including global warming potential (GWP), producing −2.73 kgCO 2 eq/m 2 in embodied emissions, whereas the modeled baseline has an embodied GWP of 428 kgCO 2 eq/m 2 . The careful material selection and advanced building design optimizes performance, with the Circular Home containing only −0.006 times the embodied emissions and −0.02 times the operational emissions of its traditional counterpart. Finally, the unique contribution of this work is in the environmental impact comparison of a high-performance modular CLT structure that can be affordably scaled and mass produced in a U.S. market, compared to typical single family home construction.

Circularity↗

Separation of K + and Bi 3+ displacements in a Pb-free, monoclinic piezoelectric at the morphotropic phase boundary

The best piezoelectric properties of any perovskite oxide known are found in the solid solution of the relaxor Pb (Mg 1/3 Nb 2/3 )O 3 and ferroelectric PbTiO 3 . Despite its impressive properties, this system has limited analogy. We present the compositional exploration of the Pb-free analogue (1-x)(K 1/2 Bi 1/2 )(Mg 1/3 Nb 2/3 )O 3 -x(K 1/2 Bi 1/2 )TiO 3 (KBMN-KBT). We locate the morphotropic phase boundary between x = 0.86 and 0.88 changing from Cm to Pm symmetry and the optimally performing composition at x = 0.88. We report a piezoelectric figure of merit (d 33 *) of 192 pm V —1 from strain measurements. Diffraction methods reveal disordered displacements of K + and Bi 3+ which persist from the KBMN endmember through multiple changes in symmetry. Rearrangement of the Bi 3+ displacements along the uncommon [011] c direction drives the physical response. Ferroelectric, dielectric, and piezoresponse force microscopy are used to study the progression of physical properties through the MPB and attribute the mechanism to a polarization rotation. Taking account for local, short-range, and average structural features yield a balanced perspective on the structure and properties of this system, isolating the driving force within this system to the Bi 3+ bonding configuration. This work yields a strong analogy to the Pb-based analogue, and provides strategies for further optimization.

36 MATERIALS SCIENCE↗

Field Emission Analysis in SRF Cavities for PIP-II Using GEANT4

Field emission (FE) remains a significant hurdle for achieving optimal performance and reliability in superconducting radiofrequency (SRF) cavities used in accelerator cryomodules. A thorough understanding of the generation and propagation of FE-induced radiation is therefore essential to mitigate this problem. The absence of standardized measurement protocols further complicates the comparison of radiation data across different testing phases and facilities. This highlights the need for a precise quantitative method to diagnose and analyze FE-induced radiation. Such efforts could prove beneficial for improving cavity preparation and cleanroom assembly techniques during the prototype and production stages of Fermilab's Proton Improvement Plan-II (PIP-II) project. This study presents the initial steps of detailed Geant4 simulations aimed at analyzing FE-induced radiation in the low-beta 650 MHz 5-cell elliptical (LB650) cavity. Our goal is to combine these results with radiation diagnostics to enhance diagnostic accuracy and optimize detector positioning. This integrated approach ultimately aims to improve the preparation, assembly, and testing procedures for PIP-II SRF cavities, ensuring the delivery of FE-free cryomodules.

Wijethunga, Sajini A.K. [Fermilab] (ORCID:00000002↗

Roles of Mn and Co in Ni-rich layered oxide cathodes synthesized utilizing a Taylor Vortex Reactor

It is reported that layered oxides, composed of nickel, manganese, and cobalt (NMC), are sought after as cathode materials which provide improved energy density, cycle life, and safety in commercial lithium ion batteries (LIBs). Increasing Ni contents higher than 80% can provide even higher practical discharge capacities >200 mAh/g and similar to ~4 V discharge potential vs Li/Li + , making them promising cathodes for next generation LIBs. However, rapid capacity fade during cycling and heat-related safety concerns are delaying their successful transition to industry. We report systematic performance optimization of LiNiO 2 , LiNi 0.9 Mn 0.1 O 2 , and LiNi 0.9 Co 0.1 O 2 high Ni layered oxide cathodes synthesized by utilizing a Taylor Vortex Reactor. Co-free LiNi 0.9 Mn 0.1 O 2 cathode showed 200 mAh/g highest discharge capacity at 0.1 C rate with 84% retention after 103 cycles at 0.3C rate while LiNi 0.9 Co 0.1 O 2 cathode showed higher initial but poor cycle life (225 mAh/g highest discharge capacity at 0.1C rate with only 56% capacity retention after 103 cycles at 0.3 C rate. Synchrotron based X-ray diffraction (SXRD), X-ray absorption spectroscopy (XAS) and focused ion beam (FIB) imaging of pristine and cycled cathodes after 103 cycles provided important information on degradation mechanism. The roles of Mn and Co on layered structure formation, charge balance, cationic mixing, and electrochemical performance were elucidated using the crystallographic information from XRD refinement and electronic state analysis from XAS providing valuable information to design future Ni-rich layered oxide cathodes.

25 ENERGY STORAGE↗

Field Emission Analysis in SRF Cavities for PIP-II Using GEANT4

Field emission (FE) remains a significant hurdle for achieving optimal performance and reliability in super-conducting radiofrequency (SRF) cavities used in accelerator cryomodules. A thorough understanding of the generation and propagation of FE-induced radiation is therefore essential to mitigate this problem. The absence of standardized measurement protocols further complicates the comparison of radiation data across different testing phases and facilities. This highlights the need for a precise quantitative method to diagnose and analyze FE-induced radiation. Such efforts could prove beneficial for improving cavity preparation and cleanroom assembly techniques during the prototype and production stages of Fermilab's Proton Improvement Plan-II (PIP-II) project. This study presents the initial steps of detailed Geant4 simulations aimed at analyzing FE-induced radiation in the low-beta 650 MHz 5-cell elliptical (LB650) cavity. Our goal is to combine these results with radiation diagnostics to enhance diagnostic accuracy and optimize detector positioning. This integrated approach ultimately aims to improve the preparation, assembly, and testing procedures for PIP-II SRF cavities, ensuring the delivery of FE-free cryomodules.

Wijethunga, S. A.K. [Fermilab] (ORCID:000000028765↗

The Importance of Surface Oxygen for Lithiation and Morphology Evolution during Calcination of High-Nickel NMC Cathodes

Nanoscale morphology has a direct impact on the performance of materials for electrochemical energy storage. Despite this importance, little is known about the evolution of primary particle morphology nor its effect on chemical pathways during synthesis. In this work, operando characterization is combined with atomic-scale and continuum simulations to clarify the relationship between morphology of cathode primary particles and their lithiation during calcination of LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC-811). This combined approach reveals a key role for surface oxygen adsorption in facilitating the lithiation reaction by promoting metal diffusion and oxidation, and simultaneously providing surface sites for lithium insertion. Furthermore, oxygen surface termination is shown to increase the activation energy for sintering, leading to smaller primary particle sizes at intermediate temperatures. Smaller particles provide both shorter diffusion lengths for lithium incorporation and increased surface site density for lithium insertion. These insights provide a foundation for more tailored syntheses of cathode materials with optimized performance characteristics.

25 ENERGY STORAGE↗

Characterisation of signal-induced noise in Hamamatsu R11265 Multianode Photomultiplier Tubes

Signal-induced noise is observed in Hamamatsu R11265 Multianode Photomultiplier Tubes, manifesting up to several microseconds after the single photoelectron response signal and localised in specific anodes. The mean number of noise pulses varies between devices, and shows significant dependence on the applied high-voltage. The characterisation of this noise and the mitigation strategies to perform optimal single-photon counting at 40 MHz, as required by the LHCb Ring-Imaging Cherenkov detectors, are reported.

47 OTHER INSTRUMENTATION↗

Development of Advanced, Radiation Resistant, Optical-based Detector Technology for Future Experiments.

The primary objective of this project has been to advance the design of high-performance electromagnetic (EM) calorimeters for future particle physics experiments, to identify and measure the timing, position and energy of electrons, positrons and gamma rays, particularly in high-luminosity environments with intense radiation and pileup conditions. To meet such challenges, the proposed research has focused on the development of ultra-compact, radiation-hard calorimeter modules, to provide excellent timing, spatial, and energy resolution. The work aligns with the DOE’s Basic Research Needs (BRN) for High Energy Physics (HEP) Instrumentation and the research team contributes actively to the Coordinating Panel on Advanced Detectors (CPAD) RDC9 calorimetry collaboration in the USA and the European Committee on Future Accelerators (ECFA) DRD-CALO calorimetry collaboration at CERN, the European Laboratory for Particle Physics located in Geneva, Switzerland. The research builds on the RADiCAL (radiation-hard, ultra-compact) modular sampling calorimeter approach, developed by the research team, which employs dense and very bright optical materials such as LYSO:Ce scintillator plates that are interleaved with very dense tungsten plates to minimize detector size while optimizing performance. The modules are comparable in size to a human index finger, dimensionally 14 mm x 14 mm in cross section and 135 mm in length. And despite the small size, the structure is capable of providing excellent timing and energy resolution. This is facilitated through the use of specialized quartz capillaries filled with wavelength-shifting filaments, positioned at various depths along the length of a module, to collect and guide light signals to silicon photomultipliers (SiPMs) which detect and convert the optical signals to electronic signals for analysis. The primary goals of this project have been: (1) Achieve a timing resolution to σ t ≤ 30 ps for high-energy electrons and photons, important for their association with specific events produced in colliding-beam experiments and for the detection of decays-in-flight of long-lived particles. The project has achieved this goal in beam tests of a single RADiCAL module at CERN, during which a timing resolution of σ t = 27 ps was measured for electrons of energy E = 150 GeV. Based upon a mathematical fit to the data measured over a broad energy range from low energy to high energy, a resolution of σ t ≤ 18 ps has been estimated for electrons of very high (TeV) energy. From these measurements and with further expected technical improvements, the timing resolution should reach σ t ≤ 10 ps, important for searches for discovery physics in upcoming and future experiments. (2) Achieve an energy resolution of σ E / E ≤ 10% / $\sqrt{E}$. The project has yet to achieve this goal, but is close to it, having measured a value of σ E / E ≤ 15.9% / $\sqrt{E}$ using a modular array. Ultimately, the resolution goal is expected to be reached by adjustments to material thicknesses within the modules, which will improve the sampling fraction to measure more precisely the shower energy for lower energy particles. The versatility of the modular RADiCAL approach enables the testing of advanced materials, photosensors and electronics, developed in collaboration with CPAD RDC and ECFA DRD-CALO groups. The structure can distinguish electrons, positrons and gamma rays from hadrons and muons and beam-induced backgrounds, making it a valuable tool in a variety of detector environments, including future circular colliders (FCC-ee, FCC-hh) proposed for the European Laboratory for Particle Physics (CERN), the muon-collider proposed for Fermi National Accelerator Laboratory (Fermilab), and searches for new physics in beam-dump, fixed target and forward-physics experiments. And, while designed with particle physics applications in mind, the technologies developed in this project have the potential for application more broadly in particle and nuclear physics, materials science, and medical physics, underscoring the far-reaching potential of this line of instrumentation research and development.

47 OTHER INSTRUMENTATION↗

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

Protecting and Defending against Autonomous Control Systems and Digital Twin Cyber Attacks: Response Strategy for Hyperparameter attacks of Digital Twin Machine Learning Models in Nuclear Power Plants (Final)

Navigating through the complex tapestry of technological advancements, "Response Strategy for Hyperparameter attacks of Digital Twin Machine Learning Model in Nuclear Power Plants" stands at the intersection of cybersecurity and nuclear power plant operations, embarking on a journey through the intricacies of securing digital twins against malicious cyber activities. As nuclear power plants progressively integrate digital twin technology and machine learning models to optimize operations and ensure system reliability, they inadvertently expose themselves to a new spectrum of vulnerabilities, notably in the realm of hyperparameter attacks. Hyperparameters, integral in machine learning model tuning and optimal performance of digital twins, have emerged as a target for adversaries aiming to destabilize the predictive capabilities and therefore, the operational accuracy of these digital entities within critical infrastructures like nuclear plants. This paper, therefore, meticulously threads the needle through the development of a robust response strategy, poised to shield these digital reflections against calculated hyperparameter manipulations, ensuring that the digital twin can effectively and securely function as a reliable proxy for its physical counterpart. The ensuing sections delve into the orchestrated maelstrom of multi-rate time-changing intelligent coordinated hyperparameter attacks and the implementation of event-triggered predictive control, laying down a structured, predictive, and responsive framework that safeguards the nexus where the digital and physical realms of nuclear power plants coalesce. The operational integrity of digital twins in nuclear power plants depends critically on the security of machine learning hyperparameters. This study makes two different contributions. First, a decision-based idea known as a multi-rate time changing intelligent coordinated hyperparameter attack is put forth. In this attack, many hyperparameters are repeatedly changed using both random and intelligent optimal techniques by the attacker. These assaults introduce varied rates at different attack steps, compromise various amounts of hyperparameters, and improve stealth and flexibility. Second, a technique is developed for event triggered predictive control to rapidly respond to potential hyperparameter attacks. This control integrates a sliding window framework, retaining a history of previous data points and employing linear regression to predict the next data point from the current dataset. The control gain K is determined using the Lyapunov-Krasovskii method, and subsequently, an action is developed. Finally, the outcome of the simulation demonstrates the viability of the proposed method for defending nuclear power plant digital twins from hyperparameter attacks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Efficient exascale discretizations: High-order finite element methods

Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of floating point operations to energy intensive data movement. One of the few viable approaches to achieve high efficiency in the area of PDE discretizations on unstructured grids is to use matrix-free/partially assembled high-order finite element methods, since these methods can increase the accuracy and/or lower the computational time due to reduced data motion. In this paper we provide an overview of the research and development activities in the Center for Efficient Exascale Discretizations (CEED), a co-design center in the Exascale Computing Project that is focused on the development of next-generation discretization software and algorithms to enable a wide range of finite element applications to run efficiently on future hardware. CEED is a research partnership involving more than 30 computational scientists from two US national labs and five universities, including members of the Nek5000, MFEM, MAGMA and PETSc projects. We discuss the CEED co-design activities based on targeted benchmarks, miniapps and discretization libraries and our work on performance optimizations for large-scale GPU architectures. We also provide a broad overview of research and development activities in areas such as unstructured adaptive mesh refinement algorithms, matrix-free linear solvers, high-order data visualization, and list examples of collaborations with several ECP and external applications.

97 MATHEMATICS AND COMPUTING↗