Search NASA⌕ Search

SEARCH · Search NASA

Results for “dependable computing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A Projective Phase Space Generator for Hadronic Vector Boson Plus One Jet Production

In this paper we use our previously developed projective phase space generator for the calculation of the hadronic production of a vector boson with one additional jet at Next-to-Leading Order. The projective phase space generator allows us to make physical predictions in novel ways, speeding up both evaluation time and attainable accuracy. For the numerical evaluation we explore a computational model which combines the use of both multi-threading and distributed resources through the use of grid or cloud computing without depending on local institutional computer availability. The projective phase space method is well suited for this approach and gives through the use of cloud computing instant access to a large pool of resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Dependable classical-quantum computing systems engineering

Increasing evidence suggests quantum computing (QC) complements traditional High-Performance Computing (HPC) by leveraging its unique capabilities, leading to the emergence of a new, hybrid paradigm, QHPC. However, this integration introduces new challenges, with dependability–defined by reproducibility, resiliency, and security and privacy–emerging as a central concern for building trustworthy systems that provide an advantage to the users. This paper proposes a framework for dependable QHPC system design, organized around these three pillars. We identify integration challenges, anticipate roadblocks, and highlight productive synergies across QC, HPC, cloud platforms, and network security. Drawing from both classical computing principles and quantum-specific insights, we present a roadmap for co-design that supports robust hybrid architectures. Our approach offers concrete metrics for assessing dependability, provides design guidance for engineers working at the QC-HPC interface, and surfaces new engineering questions around complexity, scale, and fault tolerance. Ultimately, designing for dependability is key to realizing practical, scalable QHPC systems and accelerating the broader quantum ecosystem capable of translating quantum promises into actual application delivery.

HPC↗
DOE OSTI2021

Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth

Sustaining a robust metabolic network requires a balanced and fully functioning proteome. In addition to amino acids, many enzymes require cofactors (coenzymes and engrafted prosthetic groups) to function properly. Extensively validated resource allocation models, such as genome-scale models of metabolism and gene expression (ME-models), have the ability to compute an optimal proteome composition underlying a metabolic phenotype, including the provision of all required cofactors. Here we apply the ME-model for Escherichia coli K-12 MG1655 to computationally examine how environmental conditions change the proteome and its accompanying cofactor usage. We found that: (1) The cofactor requirements computed by the ME-model mostly agree with the standard biomass objective function used in models of metabolism alone (M-models); (2) ME-model computations reveal non-intuitive variability in cofactor use under different growth conditions; (3) An analysis of ME-model predicted protein use in aerobic and anaerobic conditions suggests an enrichment in the use of peroxyl scavenging acids in the proteins used to sustain aerobic growth; (4) The ME-model could describe how limitation in key protein components affect the metabolic state of E . coli . Genome-scale models have thus reached a level of sophistication where they reveal intricate properties of functional proteomes and how they support different E . coli lifestyles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

DFT and microkinetic comparison of Pt, Pd and Rh-catalyzed ammonia oxidation

Ammonia oxidation is the heart of the Ostwald process and is important in emissions control. Catalytic behaviors are a function of conditions and are observed to vary across the platinum group metals (PGMs) Pt, Pd, Rh. Here, we combine density functional theory computations and microkinetic modeling to rationalize these dependencies. We compute reactions over model (2 1 1) and (1 1 1) surfaces of PGMs. Binding energies are similar on Pd and Pt and generally greater on Rh, while activation energies vary across all metals. Rates on (2 1 1) surfaces are greater than (1 1 1) surfaces. Additionally, the stepped Pt is most active and stepped Rh most selective to N 2 at ammonia slip conditions, while at Ostwald process conditions, stepped Pd is most active and stepped Pt most selective to NO. Degree of rate and selectivity control analysis provides insights into the reactions limiting performance of PGMs. Both activation barriers and surface coverages influence rates and selectivities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Methods and apparatus to modify a binary file for scalable dependency loading on distributed computing systems

Methods and apparatus to modify a binary file for scalable loading on distributed computing systems are disclosed. An example method to modify a binary file for scalable loading on a distributed computing system includes identifying, by executing an instruction with a processor, in the binary file a file name for a shared file, determining, by executing an instruction with the processor, whether the shared file can be loaded based on a path name specified in the binary file, and, responsive to a determination that the shared file can be loaded, generating, by executing an instruction with the processor, an identifier that can be used to access a local file scalably copied from a global file system, and modifying, by executing an instruction with the processor, the binary file by replacing, in the binary file, the file name with the generated identifier.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Computing nuclear response functions with time-dependent coupled-cluster theory

We compute nuclear response functions by solving the time-dependent 𝐴-body Schrödinger equation, recording the time-dependent transition moment and extracting spectral information via Fourier transforms. The solution of the time-dependent many-body problem accounts for correlations on top of the mean field by taking advantage of a time-dependent formulation of coupled-cluster theory. As a validation, we focus on electric dipole transitions in 4 He and 16 O and compare moments of the response function distribution to the results of an equivalent static framework, finding negligible discrepancies. We investigate how proton and neutron densities evolve in time, and we see the traditional picture of soft and giant dipole resonances as collective oscillations of protons and neutrons emerging from our calculations in 16 O and 24 O. Furthermore, this method also allows us to investigate the behavior of the nucleus in the presence of a strong electric field. In that regime, the behavior of the system becomes chaotic. Qualitatively, the spectral information obtained in this limit is in line with previous time-dependent mean-field results.

Ab initio calculations↗
DOE OSTI2018

Fast and accurate quantum Monte Carlo for molecular crystals

Computer simulation plays a central role in modern-day materials science. The utility of a given computational approach depends largely on the balance it provides between accuracy and computational cost. Molecular crystals are a class of materials of great technological importance which are challenging for even the most sophisticated ab initio electronic structure theories to accurately describe. This is partly because they are held together by a balance of weak intermolecular forces but also because the primitive cells of molecular crystals are often substantially larger than those of atomic solids. Here, we demonstrate that diffusion quantum Monte Carlo (DMC) delivers subchemical accuracy for a diverse set of molecular crystals at a surprisingly moderate computational cost. As such, we anticipate that DMC can play an important role in understanding and predicting the properties of a large number of molecular crystals, including those built from relatively large molecules which are far beyond reach of other high-accuracy methods.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Fast synchronization-free algorithms for parallel sparse triangular solves with multiple right-hand sides

The sparse triangular solve kernels, SpTRSV and SpTRSM, are important building blocks for a number of numerical linear algebra routines. Parallelizing SpTRSV and SpTRSM on today's many-core platforms, such as GPUs, is not an easy task since computing a component of the solution may depend on previously computed components, enforcing a degree of sequential processing. As a consequence, most existing work introduces a preprocessing stage to partition the components into a group of level-sets or colour-sets so that components within a set are independent and can be processed simultaneously during the subsequent solution stage. However, this class of methods requires a long preprocessing time as well as significant runtime synchronization over-heads between the sets. To address this, we

HPC↗
DOE OSTI2025

FLAMES─Fast, Low-Storage, Accurate, and Memory-Efficient Adaptive Sampling─Approach to Resolve Spatially Dependent Dynamics of Molecular Liquids

Many critical phenomena in soft matter occur at large length scales, necessitating the resolution of their structure and dynamics at low wavenumbers. However, resolving wavenumber-dependent dynamics computationally via molecular dynamics simulations presents significant challenges, as these phenomena span several orders of magnitude in both time and length scales, resulting in high computational costs and memory demands. Here, this work highlights the computational and memory challenges associated with analyzing molecular trajectories in reciprocal space and demonstrates a method to address them. We introduce FLAMESFast, Low-storage, Accurate, and Memory-Efficient adaptive Sampling, which is a direct method for calculation of structure factors, allowing us to select only the required number of wavevectors for binning. We also use wavenumber-dependent time steps to extract dynamics. Our FLAMES approach effectively mitigates computational and memory/storage bottlenecks. We demonstrate the method using simulations of a model system, liquid octane, at various temperatures. Comparisons with experimental data and real space computation show that the FLAMES technique achieves high accuracy in resolving temperature- and spatially dependent dynamics while being significantly more computationally efficient and requiring less memory and storage than methods based on a uniform wavevector grid and fixed temporal spacing.

Chen, Guang [Argonne National Laboratory (ANL), Ar↗
DOE OSTI2017

Model's sparse representation based on reduced mixed GMsFE basis methods

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a large number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in random porous media is simulated by the proposed sparse representation method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

An Innovative Approach to Bridge a Skill Gap and Grow a Workforce Pipeline: The Computer System, Cluster, and Networking Summer Institute

Sustainable and effective computing infrastructure depends critically on the skills and expertise of domain scientists and of committed and well-trained advanced computing professionals. But, in its ongoing High Performance Computing (HPC) work, Los Alamos National Laboratory noted a persistent shortage of well-prepared applicants, particularly for entry-level cluster administration, file systems administration, and high speed networking positions. Further, based upon recruiting efforts and interactions with universities graduating students in related majors of interest (e.g., computer science (CS)), there has been a long standing skillset gap, as focused training in HPC topics is typically lacking or absent in undergraduate and in even many graduate programs. Given that the effective operation and use of HPC systems requires specialized and often advanced training, that there is a recognized HPC skillset gap, and that there is intense global competition for computing and computational science talent, there is a long-standing and critical need for innovative approaches to help bridge the gap and create a well-prepared, next generation HPC workforce. Our paper places this need in the context of the HPC work and workforce requirements at Los Alamos National Laboratory (LANL) and presents one such innovative program conceived to address the need, bridge the gap, and grow an HPC workforce pipeline at LANL. The Computer System, Cluster, and Networking Summer Institute (CSCNSI) completed its 10th year in 2016. The story of the CSCNSI and its evolution is detailed below with a description of the design of its Boot Camp, and a summary of its success and some key factors that have enabled that success.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Nanotubes, Plates, and Needles: Pathway-Dependent Self-Assembly of Computationally Designed Peptides

Computationally designed peptides form desired antiparallel, tetrameric coiled-coil bundles that hierarchically assemble into a variety of well-controlled nanostructures depending on aqueous solution conditions. The bundles selectively self-assemble into different structures: nanotubes, platelets, or needle-like structures at solution pH values of 4.5, 7, and 10, respectively. The self-assembly produces hollow tubes or elongated needle-like structures at pH conditions associated with charged bundles (pH 4.5 or 10); at neutral pH, near the pI of the bundle, a plate-like self-assembled structure forms. Transmission electron microscopy and small-angle X-ray scattering show the nanotubes to be uniform with a tube diameter of ~13 nm and lengths of up to several μm, yielding aspect ratios >1000. Combining the measured nanostructure geometry with the apparent charged states of the constituent amino acids, a tilted-bundle packing model is proposed for the formation of the homogeneous nanotubes. Here, this work demonstrates the successful use of assembly pathway control for the construction of nanostructures with diverse, well-structured morphologies associated with the folding and self-association of a single type of molecule.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Determination of Cell Doubling Times from the Return-on-Investment Time of Photosynthetic Vesicles Based on Atomic Detail Structural Models

Cell doubling times of the purple bacterium Rhodobacter sphaeroides during photosynthetic growth are determined experimentally and computationally as a function of illumination. For this purpose, energy conversion processes in an intracytoplasmic membrane vesicle, the chromatophore, are described based on an atomic detail structural model. The cell doubling time and its illumination dependence are computed in terms of the return-on-investment (ROI) time of the chromatophore, determined computationally from the ATP production rate, and the mass ratio of chromatophores in the cell, determined experimentally from whole cell absorbance spectra. The ROI time is defined as the time it takes to produce enough ATP to pay for the construction of another chromatophore. The ROI time of the low light-growth chromatophore is 4.5–2.6 h for a typical illumination range of 10–100 μmol photons m –2 s –1 , respectively, with corresponding cell doubling times of 8.2–3.9 h. Finally, when energy expenditure is considered as a currency, the benefit-to-cost ratio computed for the chromatophore as an energy harvesting device is 2–8 times greater than for photovoltaic and fossil fuel-based energy solutions and the corresponding ROI times are approximately 3–4 orders of magnitude shorter for the chromatophore than for synthetic systems.

09 BIOMASS FUELS↗
DOE OSTI2017

IR-safe and UV-safe integrands in the EFTofLSS with exact time dependence

Because large-scale structure surveys may very well be the next leading sources of cosmological information, it is important to have a precise understanding of the cosmological observables; for this reason, the Effective Field Theory of Large-Scale Structure (EFTofLSS) was developed. So far, most results in the EFTofLSS have used the so-called Einstein-de Sitter approximation, an approximation of the time dependence which is known to be accurate to better than one percent. However, in order to reach even higher accuracy, the full time dependence must be used. The computation with exact time dependence is sensitive to both infrared (IR) and ultraviolet (UV) effects in the loop integrands, and while these effects must cancel because of diffeomorphism invariance, they make numerical computation much less efficient. We provide a formulation of the one-loop, equal-time exact-time-dependence power spectrum of density perturbations which is manifestly free of these spurious IR and UV divergences at the level of the integrand. We extend our results to the total matter mode with clustering quintessence, show that IR and UV divergences cancel, and provide the associated IR- and UV-safe integrand. This also establishes that the consistency conditions are satisfied in this system. In conclusion, we then use our one-loop result to do an improved precision comparison of the two-loop dark-matter power spectrum with the Dark Sky N-body simulation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Revealing the Galaxy–Halo Connection through Machine Learning

Abstract Understanding the connections between galaxy stellar mass, star formation rate, and dark matter halo mass represents a key goal of the theory of galaxy formation. Cosmological simulations that include hydrodynamics, physical treatments of star formation, feedback from supernovae, and the radiative transfer of ionizing photons can capture the processes relevant for establishing these connections. The complexity of these physics can prove difficult to disentangle and obfuscate how mass-dependent trends in the galaxy population originate. Here, we train a machine-learning method called Explainable Boosting Machines (EBMs) to infer how the stellar mass and star formation rate of nearly 6 million galaxies simulated by the Cosmic Reionization on Computers project depend on the physical properties of halo mass, the peak circular velocity of the galaxy during its formation history v peak , cosmic environment, and redshift. The resulting EBM models reveal the relative importance of these properties in setting galaxy stellar mass and star formation rate, with v peak providing the most dominant contribution. Environmental properties provide substantial improvements for modeling the stellar mass and star formation rate in only ≲10% of the simulated galaxies. We also provide alternative formulations of EBM models that enable low-resolution simulations, which cannot track the interior structure of dark matter halos, to predict the stellar mass and star formation rate of galaxies computed by high-resolution simulations with detailed baryonic physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Influence of shape resonances on the angular dependence of molecular photoionization delays

Characterizing time delays in molecular photoionization as a function of the ejected electron emission direction relative to the orientation of the molecule and the light polarization axis provides unprecedented insights into the attosecond dynamics induced by extreme ultraviolet or X-ray one-photon absorption, including the role of electronic correlation and continuum resonant states. Here, we report completely resolved experimental and computational angular dependence of single-photon ionization delays in NO molecules across a shape resonance, relying on synchrotron radiation and time-independent ab initio calculations. The angle-dependent time delay variations of few hundreds of attoseconds, resulting from the interference of the resonant and non-resonant contributions to the dynamics of the ejected electron, are well described using a multichannel Fano model where the time delay of the resonant component is angle-independent. Comparing these results with the same resonance computed in e-NO + scattering highlights the connection of photoionization delays with Wigner scattering time delays.

74 ATOMIC AND MOLECULAR PHYSICS↗