Results for “Computational demand” — Page 28

DOE OSTI2022

Pathways to a Sustainable Aviation Ecosystem: Electrified Aviation Demand Modeling

With leading energy experts, high-performance computing, and powerful analysis and modeling capabilities, the National Renewable Energy Laboratory (NREL) empowers aviation stakeholders with tools and data to project future energy demand and explore supply options. As a result, NREL can help electric utilities and airport operations identify aviation electrification opportunities and prepare for future electricity needs.

aerial vehicles↗

DOE OSTI2020

Influence of Terminal Carboxyl Groups on the Structure and Reactivity of Functionalized m-Carboranethiolate Self-Assembled Monolayers

The structure and function of self-assembled monolayers (SAMs) at the nanoscale are determined by the steric and electronic effects of their building blocks. Carboranethiol molecules form pristine monolayers that provide tunable two-dimensional systems to probe lateral and interfacial interactions. Additional ω-functionality, such as carboxyl groups, can be introduced to change the properties of the exposed surfaces. Here, two geometrically similar isomeric m-carborane analogues of m-mercaptobenzoic acid, 1-COOH-7-SH-1,7-C 2 B 10 H 10 and racem-1-COOH-9-SH-1,7-C 2 B 10 H 10 , are characterized and their SAMs on Au{111} are examined. The latter isomer belongs to the rare group of chiral cage molecules and becomes, to our knowledge, the first example assembled on Au{111}. Although different in symmetry, molecules of both isomers assemble into similar hexagonal surface patterns. The nearest-neighbor spacing of 8.4 ± 0.4 Å is larger than that of non-carboxylated isomers, consistent with the increased steric demands of the carboxyl groups. Computational modeling reproduced this spacing and suggests a tilt relative to the surface normal. However, tilt domains are not observed experimentally, suggesting the presence of strong lateral interactions. Analyses of the influence of the functional groups through the pseudo-aromatic m-carborane skeleton showed that the thiol group attached to either carbon or boron atoms increases the carboxyl group acidity in solution. In contrast, the acidity of the exposed carboxyl group in the SAMs decreases upon surface attachment; computational analyses suggest that the driving force of this shift is the dielectric of the environment in the monolayer as a result of confined intermolecular interactions, proximity to the Au surface, and partial desolvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Bridging Python to Silicon: The SODA Toolchain

Systems performing scientific computing, data analysis, and machine learning tasks have a growing demand for application-specific accelerators that can provide high computational performance while meeting strict size and power requirements. However, the algorithms and applications that need to be accelerated are evolving at a rate that is incompatible with manual design processes based on hardware description languages. Agile hardware design tools based on compiler techniques can help by quickly producing an application-specific integrated circuit (ASIC) accelerator starting from a high-level algorithmic description. Here, we present the software-defined accelerator (SODA) synthesizer, a modular and open-source hardware compiler that provides automated end-to-end synthesis from high-level software frameworks to ASIC implementation, relying on multilevel representations to progressively lower and optimize the input code. Our approach does not require the application developer to write any register-transfer level code, and it is able to reach up to 364 giga floating point operations per second (GFLOPS)/W efficiency (32-bit precision) on typical convolutional neural network operators.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

A Reference Implementation for a Quantum Message Passing Interface

Practical applications of quantum computing are currently limited by the number of qubits that can be set with reasonable fidelities for each system. Therefore, a distributed quantum computing system with multiple quantum computers coherently connected is highly demanding. To realize the internode communication of quantum information, the software interface, Quantum Message Passing Interface (QMPI), leveraging the framework built for classical MPI but taking advantage of quantum teleportation to communicate between different quantum nodes was proposed. In this project, we develop the QMPI with point-to-point and collective operations in Qiskit and characterize its performance by demonstrating the application implementations. Moreover, we developed a new technique for optimizing collective communication of the distributed quantum programs with Multi-Controlled Toffoli gates. This technique beats the state-of-the-art in terms of fidelity and the number of remote EPR pairs consumed in both simulations and experiments.

Shi, Yue↗

DOE OSTI2023

Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES): Workshop Report

Large-eddy simulation (LES) is used as a tool to understand physical processes such as turbulence, aerosols, clouds, precipitation, radiation, the interactions among all these, and their interactions with the underlying surface. Over the next 10 years, LES will drive fundamental progress in open scientific questions in these areas as LES is increasingly used to gain understanding of complex interacting physical processes involving atmospheric turbulence. This growth will be driven both by scientific demand and the expansion of computational resources needed to conduct LES, and the form that the growth takes will largely be determined by how computational resources are leveraged for scientific gain. In particular, we suggest that computational resources are likely to be leveraged in two separate but not necessarily distinct ways. On one hand, growth in computational resources will allow LES to be made more routine, that is, performed more frequently, while on the other hand, the computational expense (measured in total floating point operations) afforded to individual LES will expand dramatically, allowing simulations to increase in both domain size and resolution as well as physical detail. Current U.S. Department of Energy (DOE) projects such as LES ARM Symbiotic Simulation and Observation Activity (LASSO) are leading the way in conducting routine LES, building large, public databases that are accessible for data science, sensitivity studies, and training for machine learning. LES will also become more routine as it becomes more accessible for individual researchers to address their scientific questions of interest. Scientific questions addressed by LES over the next 10 years are likely to include cloud organization and aggregation; aerosol cloud interactions and atmospheric chemistry (including geo-engineering); urban-scale LES; atmospheric extreme events, ranging from small-scale severe weather to wildfires; and ocean-wave-atmosphere interactions. Further LES-related research will likely grow significantly in areas related to societal impact studies of air quality and extreme weather events, applications to renewable energy forecasting and resource assessment, and aid in decision-making processes. The growth in the use of LES in atmospheric science research will drive the need for better physical process representations (e.g., cloud aerosol microphysics, radiation, and atmospheric chemistry) at the scales resolved by LES. To date, many of the process representations used by LES have been taken directly from coarser-resolution models. Promising methods for LES process representations include superdroplet and quadrature methods for microphysics, 3D approaches for radiation, and better representation of chemistry and aerosol processes. At LES resolution, land-atmosphere interactions for complex terrains, land cover/types, biogeochemistry, and plant canopy models are needed as an improvement beyond traditional and widely used Monin-Obuhkov similarity theory.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES) (Workshop Report)

Large-eddy simulation (LES) is used as a tool to understand physical processes such as turbulence, aerosols, clouds, precipitation, radiation, the interactions among all these, and their interactions with the underlying surface. Over the next 10 years, LES will drive fundamental progress in open scientific questions in these areas as LES is increasingly used to gain understanding of complex interacting physical processes involving atmospheric turbulence. This growth will be driven both by scientific demand and the expansion of computational resources needed to conduct LES, and the form that the growth takes will largely be determined by how computational resources are leveraged for scientific gain. In particular, we suggest that computational resources are likely to be leveraged in two separate but not necessarily distinct ways. On one hand, growth in computational resources will allow LES to be made more routine, that is, performed more frequently, while on the other hand, the computational expense (measured in total floating point operations) afforded to individual LES will expand dramatically, allowing simulations to increase in both domain size and resolution as well as physical detail.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Description of FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

The urgency to deliver fusion power is growing now more than ever, with increasing pressure for both public programs and private companies to meet milestones timelines and overcome significant remaining technical challenges to ensure growth of a nascent fusion industry in time to meet rapidly growing clean energy demands. With incredible advancements in computation and years of investment in fusion model development and validation, integrated modeling is poised to fill a key role in accelerating the timeline to a fusion pilot plant (FPP). Future fusion pilot plants will operate in regimes far beyond current experience, and device design will rely on physics-based prediction and extrapolation. Many concepts will also rely on simulation to assess safety (shielding, tritium management, materials activation and lifetimes), economics and scalability before the decision to build. Importantly, integrated simulation can be used to reveal and solve the complexities of system integration that may otherwise not be apparent in physical components or models developed in isolation. New experimental test facilities that produce relevant conditions to validate and resolve key technical challenges for various subsystems (materials, blankets, fuel cycle, etc.) have been repeatedly called for by the fusion community but are not yet realized. Integrated modeling has an important role in identifying realistic load conditions (thermal, electromagnetic, plasma, neutron and photon loads, etc.) and defining the components and experiments for these test facilities in order to ensure meaningful validation that sufficiently reduces modeling uncertainties and technical risk for the full integrated reactor. The Fusion REactor Design and Assessment (FREDA) SciDAC project is building a component-based integrated modeling framework & data structure to enable self-consistent, multi-fidelity, iterative optimization workflows for the fusion reactor design process. FREDA aims to shorten the time to viable designs by providing a set of flexible workflows to support the various stages of the design process using an integrated model hierarchy, ranging from the simple analytic descriptions to the highest fidelity, theory-based plasma and engineering modeling developed by the fusion and fission communities. These tools are expected to be needed for timely support of FPP design in the milestone program and in the FIRE collaboratives. The plasma simulation backbone of FREDA is IPS-FASTRAN with newly developed coupled Core-Edge Pedestal-SOL (CESOL) workflows, which is being extended to the far-SOL region up to the plasma facing components. FREDA incorporates the FERMI engineering modeling suite and will enable self-consistent evaluation of the thermal shields, limiters, blanket, magnets, and other surrounding structures with predictions of temperatures, erosion, dpa, activation, tritium generation and transport, creep, corrosion, material degradation, etc. Parametric generation of 3D CAD enables rapid iteration of component geometry in response to plasma and loading specifications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES) (Workshop Report)

Large-eddy simulation (LES) is used as a tool to understand physical processes such as turbulence, aerosols, clouds, precipitation, radiation, the interactions among all these, and their interactions with the underlying surface. Over the next 10 years, LES will drive fundamental progress in open scientific questions in these areas as LES is increasingly used to gain understanding of complex interacting physical processes involving atmospheric turbulence. This growth will be driven both by scientific demand and the expansion of computational resources needed to conduct LES, and the form that the growth takes will largely be determined by how computational resources are leveraged for scientific gain. In particular, we suggest that computational resources are likely to be leveraged in two separate but not necessarily distinct ways. On one hand, growth in computational resources will allow LES to be made more routine, that is, performed more frequently, while on the other hand, the computational expense (measured in total floating point operations) afforded to individual LES will expand dramatically, allowing simulations to increase in both domain size and resolution as well as physical detail. Current U.S. Department of Energy (DOE) projects such as LES ARM Symbiotic Simulation and Observation Activity (LASSO) are leading the way in conducting routine LES, building large, public databases that are accessible for data science, sensitivity studies, and training for machine learning. LES will also become more routine as it becomes more accessible for individual researchers to address their scientific questions of interest. Scientific questions addressed by LES over the next 10 years are likely to include cloud organization and aggregation; aerosol cloud interactions and atmospheric chemistry (including geo-engineering); urban-scale LES; atmospheric extreme events, ranging from small-scale severe weather to wildfires; and ocean-wave-atmosphere interactions. Further LES-related research will likely grow significantly in areas related to societal impact studies of air quality and extreme weather events, applications to renewable energy forecasting and resource assessment, and aid in decision-making processes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1972

Autonomous power subsystem design for an Outer Planet Spacecraft.

This paper describes the overall design of the Thermoelectric Outer Planet Spacecraft (TOPS) power subsystem. It discusses the implementation of spacecraft requirements into a fault-tolerant design in which an on-board self-test and repair computer is utilized to provide autonomous operation. Development of a protected bus concept is discussed whereby electrical power supplied to essential spacecraft loads is maintained in the event of major on-board power blackouts. Particular attention is given to describing the interfaces and operation of the power subsystem with the spacecraft control computer subsystem. Autonomous power management operations are discussed where the on-board computer adjusts the spacecraft load demand to provide maximum utilization of source power for a given mission mode.

Andrews, R. E.↗

NASA NTRS1997

Developing Interim Systems

One of the recent challenges in the aerospace industry has been to smoothly transition operations-oriented computer systems to meet increasing demands on smaller budgets. Sometimes the best solution is not affordable, but the current situation is equally untenable.

limitations resource-scavenging↗

NASA NTRS2006

FETs Based on Doped Polyaniline/Polyethylene Oxide Fibers

A family of experimental highly miniaturized field-effect transistors (FETs) is based on exploitation of the electrical properties of nanofibers of polyaniline/ polyethylene oxide (PANi/PEO) doped with camphorsulfonic acid. These polymer-based FETs have the potential for becoming building blocks of relatively inexpensive, low-voltage, highspeed logic circuits that could supplant complementary metal oxide/semiconductor (CMOS) logic circuits. The development of these polymerbased FETs offers advantages over the competing development of FETs based on carbon nanotubes. Whereas it is difficult to control the molecular structures and, hence, the electrical properties of carbon nanotubes, it is easy to tailor the electrical properties of these polymerbased FETs, throughout the range from insulating through semiconducting to metallic, through choices of doping levels and chemical manipulation of polymer side chains. A further advantage of doped PANi/PEO nanofibers is that they can be made to draw very small currents and operate at low voltage levels, and thus are promising for applications in which there are requirements to use many FETs to obtain large computational capabilities while minimizing power demands. Fabrication of an experimental FET in this family begins with the preparation of a substrate as follows: A layer of silicon dioxide between 50 and 200 nm thick is deposited on a highly doped (resistivity 0.01 W.cm) silicon substrate, then gold electrodes/contact stripes are deposited on the oxide. Next, one or more fibers of camphorsulphonic acid-doped PANi/PEO having diameters of the order of 100 nm are electrospun onto the substrate so as to span the gap between the gold electrodes (see Figure 1). Figure 2 depicts measured current-versus-voltage characteristics of the device of Figure 1, showing that saturation channel currents occur at source-todrain potentials that are surprisingly low, relative to those of CMOS FETs. The hole mobility in the depletion regime in this transistor was found to be 1.4 10(exp -4) sq cm/(V.s), while the one-dimensional charge density at zero gate bias was estimated to be approximately one hole per 50 two-ring repeat units of polyaniline, consistent with the rather high channel conductivity (approx. 10(exp -3) S/cm). Reducing or eliminating the PEO content of the fibers is expected to enhance the properties of future versions of this transistor.

Theofylaktos, Noulie↗

NASA NTRS2010

NASA Accelerates SpaceCube Technology into Orbit

On May 11, 2009, STS-125 Space Shuttle Atlantis blasted off from Kennedy Space Center on a historic mission to service the Hubble Space Telescope (HST). In addition to sending up the hardware and tools required to repair the observatory, the servicing team at NASA's Goddard Space Flight Center also sent along a complex experimental payload called Relative Navigation Sensors (RNS). The main objective of the RNS payload was to provide real-time image tracking of HST during rendezvous and docking operations. RNS was a complete success, and was brought to life by four Xilinx FPGAs (Field Programmable Gate Arrays) tightly packed into one integrated computer called SpaceCube. SpaceCube is a compact, reconfigurable, multiprocessor computing platform for space applications demanding extreme processing capabilities based on Xilinx Virtex 4 FX60 FPGAs. In a matter of months, the concept quickly went from the white board to a fully funded flight project. The 4-inch by 4-inch SpaceCube processor card was prototyped by a group of Goddard engineers using internal research funding. Once engineers were able to demonstrate the processing power of SpaceCube to NASA, HST management stood behind the product and invested in a flight qualified version, inserting it into the heart of the RNS system. With the determination of putting Xilinx into space, the team strengthened to a small army and delivered a fully functional, space qualified system to the mission.

Petrick, David↗

NASA NTRS2018

Introduction to Data Assimilation

Atmospheric data assimilation is a class of techniques used for producing descriptions of fields of air temperature, pressure, humidity, wind, etc. on a spatial grid or in terms of a finite functional representation. These are then used to initialize numerical weather forecasts or to analyze the atmosphere for other purposes. The techniques combine past, present, and even future observations in an approximate statistically optimal way. Various types of statistical or physically-based models and their corresponding adjoints are employed to relate diverse fields in both time and space and to relate what is observed to what is being analyzed. Computationally, the problem is very demanding and onstraining on the techniques that can be employed on a routine basis.

Atmospheric data assimilation↗

DOE OSTI2023

DevOps Pragmatic Practices and Potential Perils in Scientific Software Development

The DevOps movement, which aims to accelerate the continuous delivery of high-quality software, has taken a leading role in reshaping the software industry. Likewise, there is growing interest in applying DevOps tools and practices in the domains of computational science and engineering (CSE) to meet the ever-growing demand for scalable simulation and analysis. Translating insights from industry to research computing, however, remains an ongoing challenge; DevOps for science and engineering demands adaptation and innovation in those tools and practices. There is a need to better understand the challenges faced by DevOps practitioners in CSE contexts in bridging this divide. To that end, we conducted a participatory action research study to collect and analyze the experiences of DevOps practitioners at a major US national laboratory through the use of storytelling techniques. We share lessons learned and present opportunities for future investigation into DevOps practice in the CSE domain.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2003

Finite-Element Methods for Real-Time Simulation of Surgery

Two finite-element methods have been developed for mathematical modeling of the time-dependent behaviors of deformable objects and, more specifically, the mechanical responses of soft tissues and organs in contact with surgical tools. These methods may afford the computational efficiency needed to satisfy the requirement to obtain computational results in real time for simulating surgical procedures as described in Simulation System for Training in Laparoscopic Surgery (NPO-21192) on page 31 in this issue of NASA Tech Briefs. Simulation of the behavior of soft tissue in real time is a challenging problem because of the complexity of soft-tissue mechanics. The responses of soft tissues are characterized by nonlinearities and by spatial inhomogeneities and rate and time dependences of material properties. Finite-element methods seem promising for integrating these characteristics of tissues into computational models of organs, but they demand much central-processing-unit (CPU) time and memory, and the demand increases with the number of nodes and degrees of freedom in a given finite-element model. Hence, as finite-element models become more realistic, it becomes more difficult to compute solutions in real time. In both of the present methods, one uses approximate mathematical models trading some accuracy for computational efficiency and thereby increasing the feasibility of attaining real-time up36 NASA Tech Briefs, October 2003 date rates. The first of these methods is based on modal analysis. In this method, one reduces the number of differential equations by selecting only the most significant vibration modes of an object (typically, a suitable number of the lowest-frequency modes) for computing deformations of the object in response to applied forces.

Basdogan, Cagatay↗

DOE OSTI2022

Construction of bias-preserving operations for pair-cat codes

Fault-tolerant quantum computation with depolarization error often requires demanding error threshold and resource overhead. If the operations can maintain high noise bias—dominated by dephasing error with small bit-flip error—we can achieve hardware-efficient fault-tolerant quantum computation with a more favorable error threshold. Distinct from two-level physical systems, multilevel systems (such as harmonic oscillators) can achieve a desirable set of bias-preserving quantum operations while using continuous engineered dissipation or Hamiltonian protection to stabilize to the encoding subspace. For example, cat codes stabilized with driven-dissipation or Kerr nonlinearity can possess a set of bias-preserving gates while continuously correcting bosonic dephasing error. However, cat codes are not compatible with continuous quantum error correction against excitation loss error, because it is challenging to continuously monitor the parity to correct photon loss errors. In this work, we generalize the bias-preserving operations to pair-cat codes, which can be regarded as a multimode generalization of cat codes, to be compatible with continuous quantum error correction against both bosonic loss and dephasing errors. In conclusion, our results open the door towards hardware-efficient robust quantum information processing with both bias-preserving operations and continuous quantum error correction simultaneously correcting bosonic loss and dephasing errors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Graph Neural Network-based Tracking as a Service

Recent studies have shown promising results for track finding in dense environments using Graph Neural Network (GNN)-based algorithms. However, GNN-based track finding is computationally slow on CPUs, necessitating the use of coprocessors to accelerate the inference time. Additionally, the large input graph size demands a large device memory for efficient computation, a requirement not met by all computing facilities used for particle physics experiments, particularly those lacking advanced GPUs. Furthermore, deploying the GNN-based track-finding algorithm in a production environment requires the installation of all dependent software packages, exclusively utilized by this algorithm. These computing challenges must be addressed for the successful implementation of GNN-based track-finding algorithm into production settings. In response, we introduce a ``GNN-based tracking as a service'' approach, incorporating a custom backend within the NVIDIA Triton inference server to facilitate GNN-based tracking. This paper presents the performance of this approach using the Perlmutter supercomputer at NERSC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Tethys: A Spatiotemporal Downscaling Model for Global Water Demand

Humans use water for many important tasks, such as drinking, growing food, and cooling power plants. Since future water demands depend on complex global interactions between economic sectors (e.g., demand for wheat in one country causing demand for water to grow that wheat in another country), it is often modeled at coarse spatial and temporal scales as part of models that account for complex, multi-sector system dynamics. However, models that project future water availability typically simulate physical processes at much finer scales. Tethys enables integration between these kinds of models by downscaling region-scale water demand projections using sector-specific proxies and formulas.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗