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DOE OSTI2023

In-depth analysis on parallel processing patterns for high-performance Dataframes

The Data Science domain has expanded monumentally in both research and industry communities during the past decade, predominantly owing to the Big Data revolution. Artificial Intelligence (AI) and Machine Learning (ML) are bringing more complexities to data engineering applications, which are now integrated into data processing pipelines to process terabytes of data. Typically, a significant amount of time is spent on data preprocessing in these pipelines, and hence improving its efficiency directly impacts the overall pipeline performance. The community has recently embraced the concept of Dataframes as the de-facto data structure for data representation and manipulation. However, the most widely used serial Dataframes today (R, pandas) experience performance limitations while working on even moderately large data sets. We believe that there is plenty of room for improvement by taking a look at this problem from a high-performance computing point of view. In a prior publication, we presented a set of parallel processing patterns for distributed dataframe operators and the reference runtime implementation, Cylon. In this paper, we are expanding on the initial concept by introducing a cost model for evaluating the said patterns. Furthermore, we evaluate the performance of Cylon on the ORNL Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Asi Nuclear Energy Sensors Data Portal Chatbot And Data Structuring Tool

The Idaho National Laboratory (INL) is advancing the development of an AI-powered chatbot and data structuring tool specifically designed to accelerate data mining processes for sensor-related information and seamlessly integrate the results into the ASI Sensors Data Portal (https://nes.energy.gov/). By doing so, the software aims to enhance the accessibility, usability, and organization of sensor data for nuclear energy applications. The software initial phase focuses on retrieving comprehensive datasets, prioritizing the past five years of publicly available information from the Office of Scientific and Technical Information (OSTI). These datasets will be meticulously processed to ensure compatibility, employing cleaning and preprocessing steps to eliminate irrelevant, incomplete, or corrupted information, thus establishing a robust foundation for subsequent AI use. The data will serve as the backbone for training an AI model and chatbot, which will act as an interactive tool enabling users to ask complex, context-specific questions and receive accurate, validated answers derived from constrained literature. In parallel, the project incorporates a data structuring process supported by AI to organize sensor information from multiple sources into a standardized format. This structured data will include detailed sensor specifications, such as measurement range, applications, accuracy, and operating conditions, generated and documented with AI. These specifications will be systematically integrated into the sensor portal. To maintain the highest levels of accuracy and relevance, all AI-generated outputs will be reviewed and validated by subject matter experts (SMEs), with additional fields or parameters added as needed. Future stages of the project aim to expand the dataset beyond OSTI to include other sources and potentially incorporate unclassified controlled information (UCI) with restricted access protocols to address security and confidentiality requirements.

Mapes, NormanJ. [Idaho National Laboratory (INL), ↗

DOE OSTI2020

A 1D coupled transport/cold plasma wave model for parallel ponderomotive density modification near RF actuators

The plasma density profile close to RF actuators plays a vital role in the efficiency of power coupling from the antenna to the core plasma of fusion devices. Nonlinear interactions can be significant when considering the interaction of applied RF power and the tenuous SOL plasma, and the inclusion of this region in computational analysis is essential to providing robust predictive simulations of plasma response to RF application. Of particular interest is the observed density modification during RF operation. Here we present a self consistent description of the nonlinear ponderomotive force in the antenna near field region, via coupling a 1D field aligned transport model with a 1D cold plasma wave model. Results are presented, which show a parallel electric field of 300 Vm -1 drove a density reduction of ~ 20% over 25 RF periods.

Barnett, Rhea↗

DOE OSTI2019

Cardinal: A Lower Length-scale Simulator for Fluoride Cooled High Temperature Reactors

The new DOE-NE “Center of Excellence for Thermal-fluids applications in Nuclear Energy” inaugurated in April 2018 considers and researches novel new solution strategies for historically challenging flow issues that still plague the current fleet of deployed Light Water Reactor (LWR) nuclear reactors as well as predicting various fluid flow and fluid related issues with advanced reactor technologies. Our advanced thermal-fluids research and development approach synergistically combines three natural, though overlapping, length and time scales in a hierarchal multi-scale approach to avoid the temptation and pitfalls of attempting to develop a single “solve all” algorithm for physical fluid flow problems that will span 109 in spatial and temporal scales. The demonstrate the multi-scale philosophy of the center we focus first on Fluoride Cooled High Temperature Reactors (FHRs), and in particular on the Berkeley’s PB-FHR design Mark-I design. The Fluoride salt cooled High temperature Reactor (FHR) is a class of advanced nuclear reactors that combine the robust coated particle fuel form from high temperature gas cooled reactors, direct reactor auxiliary cooling system (DRACS) passive decay removal of liquid metal fast reactors, and the transparent, high volumetric heat capacitance liquid fluoride salt working fluids - Flibe - from molten salt reactors. This combination of fuel and coolant enables FHRs to operate in a high-temperature low-pressure design space that has beneficial safety and economic implications. The PB-FHR reactor relies on a pebble bed approach and pebble bed reactors are in a sense the poster child for multiscale analysis. The lower length-scale simulator for pebble reactor cores comprises three physics: neutronics (OpenMC), thermal-fluids (Nek5000) and fuel performance (BISON). As part of center of excellence ongoing research efforts we have developed “Cardinal”, a new tool platform for lower length-scale simulation. Cardinal tightly couples all three physics and leverages advances in MOOSE such as the MultiApp system and the concept of MOOSE-wrapped Apps. Moreover it is designed from the ground-up to scale on massively parallel architectures and perform well on world-class super-computing architectures. In this report we describe the design of Cardinal and present a demo of the application of Cardinal to an FHR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Preparing NERSC users for Cori, a Cray XC40 system with Intel many integrated cores

The newest NERSC supercomputer Cori is a Cray XC40 system consisting of 2,388 Intel Xeon Haswell nodes and 9,688 Intel Xeon-Phi “Knights Landing” (KNL) nodes. Compared to the Xeon-based clusters NERSC users are familiar with, optimal performance on Cori requires consideration of KNL mode settings; process, thread, and memory affinity; fine-grain parallelization; vectorization; and use of the high-bandwidth MCDRAM memory. This paper describes our efforts preparing NERSC users for KNL through the NERSC Exascale Science Application Program, Web documentation, and user training. We discuss how we configured the Cori system for usability and productivity, addressing programming concerns, batch system configurations, and default KNL cluster and memory modes. Here, system usage data, job completion analysis, programming and running jobs issues, and a few successful user stories on KNL are presented.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Modelling of edge plasma dynamics with active wall boundary conditions

A self-consistent 2D model is presented for transport in boundary plasma and plasma-facing material walls. Plasma dynamics in the domain is represented by a 2D collisional plasma fluid model in the edge-plasma code UEDGE, and transport of hydrogen and heat in the wall is represented by a system of reaction–diffusion equations in the 1D wall code FACE. To account for variation of parameters along the wall, in the coupled model multiple instances of the FACE code run in parallel. Here, the coupled model provides a tool for investigating a range of dynamic plasma–material interactions phenomena in 2D. For demonstration of its capability, one application of particular interest is the role of active wall in tokamak strike point sweeping proposed for mitigation of divertor heat loads. In the present study, the coupled calculations are applied to investigation of the impact of heat and hydrogen transport in the material wall on the divertor plasma and target heat load during sweeping of the target strike point for parameters of a high-power tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2017

A fast, efficient direct slicing method for slender member structures

We describe a method for quickly and efficiently slicing structures consisting of a large number of slender members called struts connected at node positions called joints. Previous research on periodic lattice structures shows these structures are highly mechanically efficient with exceptionally high stiffness- and strength-to-weight ratios. Additive manufacturing technologies allow the construction slender member structures with complicated macroscale shapes. These structures could consist of thousands or millions of geometric primitives describing the struts. Structures with large numbers of geometric objects cause the conventional methods for manipulating, storing, and slicing the geometry of these parts via STL files to be highly inefficient. This work describes an alternate design process for slender member structures using efficient methods for manipulating, storing, and slicing the geometry of the part. These new methods, in particular a fast, efficient direct slicing method, enable printing slender member structures with over one hundred thousand struts. The slicing algorithm is nearly perfectly parallel so it could extend to handle structures with over one million struts, helping to facilitate the adoption of slender member structures for engineering-scale applications.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Simulation of 24,000 Electron Dynamics: Real-Time Time-Dependent Density Functional Theory (TDDFT) with the Real-Space Multigrids (RMG)

Here, we present the theory, implementation, and benchmarking of a real-time time-dependent density functional theory (RT-TDDFT) module within the RMG code, designed to simulate the electronic response of molecular systems to external perturbations. Our method offers insights into nonequilibrium dynamics and excited states across a diverse range of systems, from small organic molecules to large metallic nanoparticles. Benchmarking results demonstrate excellent agreement with established TDDFT implementations and showcase the superior stability of our time integration algorithm, enabling long-term simulations with minimal energy drift. The scalability and efficiency of RMG on massively parallel architectures allow for simulations of complex systems, such as plasmonic nanoparticles with thousands of atoms. Future extensions, including nuclear and spin dynamics, will broaden the applicability of this RT-TDDFT implementation, providing a powerful toolset for studies of photoactive materials, nanoscale devices, and other systems where real-time electronic dynamics is essential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Fluorescence Color by Data-Driven Design of Genomic Silver Clusters

DNA nucleobase sequence controls the size of DNA-stabilized silver clusters, leading to their well-known yet little understood sequence-tuned colors. The enormous space of possible DNA sequences for templating clusters has challenged the understanding of how sequence selects cluster properties and has limited the design of applications that employ these clusters. Here, we investigate the genomic role of DNA sequence for fluorescent silver clusters using a data-driven approach. Employing rapid parallel silver cluster synthesis and fluorimetry, we determine the fluorescence spectra of silver cluster products stabilized by 1432 distinct DNA oligomers. By applying pattern recognition algorithms to this large experimental data set, we discover certain DNA base patterns, or “motifs,” that correlate to silver clusters with similar fluorescence spectra. These motifs are employed in machine learning classifiers to predictively design DNA template sequences for specific fluorescence color bands. Our method improves selectivity of templates by 330% for silver clusters with peak emission wavelengths beyond 660 nm. The discovered base motifs also provide physical insights into how DNA sequence controls silver cluster size and color. Finally, this predictive design approach for color of DNA-stabilized silver clusters exhibits the potential of machine learning and data mining to increase the precision and efficiency of nanomaterials design, even for a soft-matter-inorganic hybrid system characterized by an extremely large parameter space.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Interfacial Inversion of Stealth Surfactants

Amphiphilic macromolecular surfactants segregate to liquid–liquid interfaces, thereby reducing the interfacial tension and free energy. Here, we investigated “stealth surfactants” in the form of core–shell bottlebrush polymers comprised of pH-responsive diblock copolymer side chains forming a hydrophilic core and a hydrophobic shell, enabling solubility in oil. At liquid–liquid interfaces, these polymers undergo a structural “inversion”, with hydrophilic blocks segregating into the aqueous phase and hydrophobic blocks residing in the oil phase. The reconfiguration kinetics and surfactant properties are influenced by multiple factors, including the molecular weights of the backbone and side chain components, the hydrophilic-to-hydrophobic balance of the side chains, and the pH of the aqueous phase. An observed nonmonotonic dependence of interfacial tension with time is attributed to a progressive structural inversion, where the projected area of the macromolecule onto the interface decreases. To validate this inversion hypothesis, interfacial properties were characterized by sum-frequency generation vibrational spectroscopy, which revealed configurational changes of the core–shell bottlebrush polymers at the fluid interface and revealed a pH-dependent interfacial coverage. Coarse-grained molecular dynamics simulations supported these experimental findings, showing that the pH-responsive core and hydrophobic shell assume a time-averaged configuration with orientations parallel and perpendicular to the plane of the interface, respectively. These findings open routes to design multistimuli-responsive polymeric surfactants and compatibilizers, expanding their potential applications in advanced interfacial systems.

Stealth surfactants↗

DOE OSTI2017

X-ray transparent microfluidic chips for high-throughput screening and optimization of in meso membrane protein crystallization

Elucidating and clarifying the function of membrane proteins ultimately requires atomic resolution structures as determined most commonly by X-ray crystallography. Many high impact membrane protein structures have resulted from advanced techniques such as in meso crystallization that present technical difficulties for the set-up and scale-out of high-throughput crystallization experiments. In prior work, we designed a novel, low-throughput X-ray transparent microfluidic device that automated the mixing of protein and lipid by diffusion for in meso crystallization trials. Here, in this work, we report X-ray transparent microfluidic devices for high-throughput crystallization screening and optimization that overcome the limitations of scale and demonstrate their application to the crystallization of several membrane proteins. Two complementary chips are presented: (1) a high-throughput screening chip to test 192 crystallization conditions in parallel using as little as 8 nl of membrane protein per well and (2) a crystallization optimization chip to rapidly optimize preliminary crystallization hits through fine-gradient re-screening. We screened three membrane proteins for new in meso crystallization conditions, identifying several preliminary hits that we tested for X-ray diffraction quality. Further, we identified and optimized the crystallization condition for a photosynthetic reaction center mutant and solved its structure to a resolution of 3.5 Å.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Neoclassical transport and profile prediction in transport barriers

Strong gradient regions in tokamaks, such as the pedestal or internal transport barriers, are regions of reduced turbulence where neoclassical transport can play a dominant role. However, standard neoclassical transport theory assumes that the gradient length scales of density, temperature, and potential are of the order of the system size. In the pedestal, gradient length scales are much shorter and are measured to be of the order of the ion poloidal gyroradius. We present an extension of neoclassical theory that is applicable in transport barriers of large aspect ratio tokamaks. We show that particle and momentum transport are connected in such a way that a source of parallel momentum can drive a significant neoclassical ion particle flux. In strong gradient regions, density, electric potential, mean parallel flow, and ion temperature are shown to no longer be flux functions. Instead, they have a small but important poloidally varying piece that modifies the transport equations to lowest order. This introduces a nonlinearity in the transport problem through the coupling with quasineutrality that yields multiple co-existing solutions when solving for the plasma profiles. The different solutions could be connected to low and high transport states and jumps between solutions could provide a new neoclassical explanation for H-L back-transitions.

Trinczek, Silvia [Princeton Plasma Physics Laborat↗

DOE OSTI2020

Fast neural Poincaré maps for toroidal magnetic fields

Poincaré maps for toroidal magnetic fields are routinely employed to study gross confinement properties in devices built to contain hot plasmas. In most practical applications, evaluating a Poincaré map requires numerical integration of a magnetic field line, a process that can be slow and that cannot be easily accelerated using parallel computations. We propose a novel neural network architecture, the HénonNet, and show that it is capable of accurately learning realistic Poincaré maps from observations of a conventional field-line-following algorithm. After training, such learned Poincaré maps evaluate much faster than the field-line integration method. Moreover, the HénonNet architecture exactly reproduces the primary physics constraint imposed on field-line Poincaré maps: flux preservation. Furthermore, this structure-preserving property is the consequence of each layer in a HénonNet being a symplectic map. We demonstrate empirically that a HénonNet can learn to mock the confinement properties of a large magnetic island by using coiled hyperbolic invariant manifolds to produce a sticky chaotic region at the desired island location. This suggests a novel approach to designing magnetic fields with good confinement properties that may be more flexible than ensuring confinement using KAM tori.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

Heat Transfer in a Semitransparent Medium

The problem of 1D radiative-conductive heat transfer in a homogeneous isotropic gray medium near a planar diffuse nontransparent surface and in between parallel plates with different temperatures has been solved analytically. Nonconvective measurements of the thermal resistance of parallel-plane polyethylene foam specimens versus the number of layers (i.e., thickness) have been taken, both without and with thin screens made of aluminum foil. The applicability of the suggested theoretical approach and experimental technique for the measurement of radiative heat transfer and heat transfer by conduction in light heat-protective materials has been demonstrated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

650V SiC Integrated Power Module for Automotive Inverters

The Delphi team, including CREE/Wolfspeed for SiC power devices, with packaging by Delphi supported by Oak Ridge National Laboratory, and guidance from Volvo and other OEMs resulted in a robust, high performance integrated double-side cooled SiC-based Power Module that meets or exceeds the targets identified by DOE in the original FOA. The double-side cooled packages were designed to be scalable for voltages up to 800V and for phase currents up to 500Arms and that can be paralleled for currents up to 90Arms. These modules were confirmed and demonstrated in a traction drive inverter intended for an inverter for a specific OEM vehicle application and showed improved performance as compared to inverter systems with silicon based IGBTs and Diode with losses 70% lower at lower currents and up to 40% lower at peak current levels. This teaming resulted in a WBG integrated power module to be used in an inverter manufactured in Kokomo, Indiana, which will be manufacturable in volume at a cost that will enable reduced vehicle to cost improved performance, particularly by reducing weight and space-claim for the power electronics, as well as improving reliability overall. The targeted use of this developed power module is for a vehicle traction drive to be manufactured in the CY 2021 timeframe. The direct impact of this project will accelerate commercialization of advanced wide bandgap power semiconductor technology for electrified vehicles of all types, increasing their energy efficiency and marketability. In turn, more efficient and more marketable electrified vehicles will have the overall impact of reducing greenhouse gas emissions and other air pollutants, along with reducing our nation’s dependence on foreign energy sources.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

UPC++ v1.0 Specification, Revision 2020.10.0

UPC++ is a C++11 library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). All communication operations are syntactically explicit and default to non-blocking; asynchrony is managed through the use of futures, promises and continuation callbacks, enabling the programmer to construct a graph of operations to execute asynchronously as high-latency dependencies are satisfied. A global pointer abstraction provides system-wide addressability of shared memory, including host and accelerator memories. The parallelism model is primarily process-based, but the interface is thread-safe and designed to allow efficient and expressive use in multi-threaded applications. The interface is designed for extreme scalability throughout, and deliberately avoids design features that could inhibit scalability.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

UPC++ v1.0 Specification, Revision 2021.9.0

UPC++ is a C++ library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). All communication operations are syntactically explicit and default to non-blocking; asynchrony is managed through the use of futures, promises and continuation callbacks, enabling the programmer to construct a graph of operations to execute asynchronously as high-latency dependencies are satisfied. A global pointer abstraction provides system-wide addressability of shared memory, including host and accelerator memories. The parallelism model is primarily process-based, but the interface is thread-safe and designed to allow efficient and expressive use in multi-threaded applications. The interface is designed for extreme scalability throughout, and deliberately avoids design features that could inhibit scalability.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2023

UPC++ v1.0 Specification (Rev. 2023.9.0)

97 MATHEMATICS AND COMPUTING↗