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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.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Comparative evaluation of deep learning workloads for leadership-class systems

Deep learning (DL) workloads and their performance at scale are becoming important factors to consider as we design, develop and deploy next-generation high-performance computing systems. Since DL applications rely heavily on DL frameworks and underlying compute (CPU/GPU) stacks, it is essential to gain a holistic understanding from compute kernels, models, and frameworks of popular DL stacks, and to assess their impact on science-driven, mission-critical applications. At Oak Ridge Leadership Computing Facility (OLCF), we employ a set of micro and macro DL benchmarks established through the Collaboration of Oak Ridge, Argonne, and Livermore (CORAL) to evaluate the AI readiness of our next-generation supercomputers. In this paper, we present our early observations and performance benchmark comparisons between the Nvidia V100 based Summit system with its CUDA stack and an AMD MI100 based testbed system with its ROCm stack. We take a layered perspective on DL benchmarking and point to opportunities for future optimizations in the technologies that we consider.

Yin, Junqi↗
DOE OSTI2016

Induction of oxidative and nitrosative stresses in human retinal pigment epithelial cells by all-trans-retinal

Delayed clearance of free form all-trans-retinal (atRAL) is estimated be the key cause of retinal pigment epithelium (RPE) cells injury during the pathogenesis of retinopathies such as age-related macular degeneration (AMD), however, the underlying molecular mechanisms are far from clear. In this study, we investigated the cytotoxicity effect and underlying molecular mechanism of atRAL on human retinal pigment epithelium ARPE-19 cells. The results indicated that atRAL could cause cell dysfunction by inducing oxidative and nitrosative stresses in ARPE-19 cells. The oxidative stress induced by atRAL was mediated through up-regulation of reactive oxygen species (ROS) generation, activating mitochondrial-dependent and MAPKs signaling pathways, and finally resulting in apoptosis of ARPE-19 cells. The NADPH oxidase inhibitor apocynin could partly attenuated ROS generation, indicating that NADPH oxidase activity was involved in atRAL-induced oxidative stress in ARPE-19 cells. The nitrosative stress induced by atRAL was mainly reflected in increasing nitric oxide (NO) production, enhancing iNOS, ICAM-1 and VCAM-1 expressions, and promoting monocyte adhesion. Furthermore, above effects could be dramatically blocked by using a nuclear factor kappa B (NF-κB) inhibitor SN50, indicated that atRAL-induced oxidative and nitrosative stresses were mediated by NF-κB. The results provide better understanding of atRAL-induced toxicity in human RPE cells. - Highlights: • atRAL induces oxidative stress-mediated apoptosis in ARPE-19 cells. • atRAL induces oxidative stress-mediated inflammation in ARPE-19 cells. • NF-κB is involved in atRAL-induced oxidative and nitrosative stresses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Thermoreversible and Injectable ABC Polypeptoid Hydrogels: Controlling the Hydrogel Properties through Molecular Design

Here, a series of ABC triblock copolypeptoids [i.e., poly( N -allyl glycine)- b -poly( N -methyl glycine)-b-poly( N -decyl glycine) (AMD)] with well-defined structure and varying composition have been synthesized by sequential primary amine-initiated ring-opening polymerization of the corresponding N-substituted N -carboxyanhydride monomers (Al-NCA, Me-NCA, and De-NCA). The ABC block copolypeptoids undergo sol-to-gel transitions with increasing temperature in water and biological media at low concentrations (2.5–10 wt %). The sol–gel transition is rapid and fully reversible with a narrow transition window, evidenced by the rheological measurements. The gelation temperature ( T gel ) and mechanical stiffness of the hydrogels are highly tunable: T gel in the 26.2–60.0 °C range, the storage modulus (G') and Young’s modulus ( E ) in the 0.2–780 Pa and 0.5–2346 Pa range, respectively, at the physiological temperature (37 °C) can be readily accessed by controlling the block copolypeptoid composition and the polymer solution concentration. The hydrogel is injectable through a 24 gauge syringe needle and maintains their shape upon in contact with surfaces or water baths that are kept above the sol–gel transition temperature. The hydrogels exhibit minimal cytotoxicity toward human adipose derived stem cells (hASCs), evidenced from both alamarBlue and PicoGreen assays. Furthermore, quantitative PCR analysis revealed significant up-regulation of the Col2a1 gene and down-regulation of ANGPT1 gene, suggesting that the hydrogel exhibit biological activity in inducing chondrogenesis of hASCs. It was also demonstrated that the hydrogel can be used to quantitatively encapsulate water-soluble enzymes (e.g., horseradish peroxidase) by manipulating the sol–gel transition. The enzymatic activity of HRP remain unperturbed after encapsulation at 37 °C for up to 7 d, suggesting that the hydrogel does not adversely affect the enzyme structure and thereby the enzymatic activity. These results suggest that the polypeptoid hydrogel a promising synthetic platform for tissue engineering or protein storage applications.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Discovery of Cs 2 (UO 2 )Al 2 O 5 by Molten Flux Methods: A Uranium Aluminate Containing Solely Aluminate Tetrahedra as the Secondary Building Unit

The flux synthesis, solid state synthesis, and characterization of a new aluminate, Cs 2 (UO 2 )Al 2 O 5 , are reported. Cs 2 (UO 2 )Al 2 O 5 crystallizes in the tetragonal space group $I_{4_1}$/ amd with lattice parameters $a$ = 7.3254(2) and c = 30.9849(7) and is constructed from edge-sharing chains of UO 7 pentagonal bipyramids that are connected to [Al 2 O 5 ] 4– two-dimensional sheets. The cesium cations, which are heavily disordered, occupy small channels in the $a$ and $b$ directions in the framework structure. The optical properties and ion exchange behaviors are reported along with DFT calculations that support the observed results of the ion exchange experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Atomic Layer Deposition of Ultrathin Nickel Sulfide Films and Preliminary Assessment of Their Performance as Hydrogen Evolution Catalysts

Transition metal sulfides reflect significant potential for applications ranging from catalysis to electrocatalysis to photovoltaics due to their high stability and conductivity. Nickel sulfide, particularly known for its ability to electrochemically reduce protons to hydrogen gas nearly as efficiently as expensive noble metals, can be challenging to produce with certain surface site compositions or morphologies, e.g., conformal thin films. To this end, we employed atomic layer deposition (ALD), a preeminent method to fabricate uniform and conformal films, to construct thin films of nickel sulfide (NiS x ) using bis( N , N '-di- tert -butylacetamidinato)nickel(II) (Ni(amd) 2 ) vapor and hydrogen sulfide gas. Effects of experimental conditions such as pulse and purge times and temperature on the growth of NiS x were investigated. These revealed a wide temperature range, 125–225 °C, over which self-limiting NiS x growth can be observed. In situ quartz crystal microbalance (QCM) studies revealed conventional linear growth behavior for NiS x films, with a growth rate of 9.3 ng/cm 2 per cycle being obtained. The ALD-synthesized films were characterized using X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD) methods. To assess the electrocatalyitic activity of NiS x for evolution of molecular hydrogen, films were grown on conductive-glass supports. Overpotentials at a current density of 10 mA/cm 2 were recorded in both acidic and pH 7 phosphate buffer aqueous reaction media and found to be 440 and 576 mV, respectively, with very low NiS x loading. These findings hint at the promise of ALD-grown NiS x materials as water-compatible electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Metagenomic reconstructions of bacterial CRISPR loci constrain population histories

Bacterial CRISPR-Cas systems offer insight into recent population history because they rapidly incorporate, in a unidirectional manner, short fragments (spacers) from coexisting infective virus populations into host chromosomes. Immunity is achieved by sequence identity between transcripts of spacers and their targets. Here, we used metagenomics to study the stability and dynamics of the type I-E CRISPR-Cas locus of Leptospirillum group II bacteria in biofilms sampled over 5 years from an acid mine drainage (AMD) system. Despite recovery of 452,686 spacers from CRISPR amplicons and metagenomic data, rarefaction curves of spacers show no saturation. The vast repertoire of spacers is attributed to phage/plasmid population diversity and retention of old spacers, despite rapid evolution of the targeted phage/plasmid genome regions (proto-spacers). The oldest spacers (spacers found at the trailer end) are conserved for at least 5 years, and 12% of these retain perfect or near-perfect matches to proto-spacer targets. The majority of proto-spacer regions contain an AAG proto-spacer adjacent motif (PAM). Spacers throughout the locus target the same phage population (AMDV1), but there are blocks of consecutive spacers without AMDV1 target sequences. Results suggest long-term coexistence of Leptospirillum with AMDV1 and periods when AMDV1 was less dominant. Metagenomics can be applied to millions of cells in a single sample to provide an extremely large spacer inventory, allow identification of phage/plasmids and enable analysis of previous phage/plasmid exposure. As a result, this method can provide insights into prior bacterial environment and genetic interplay between hosts and their viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors

Abstract Efficient and accurate algorithms are necessary to reconstruct particles in the highly granular detectors anticipated at the High-Luminosity Large Hadron Collider and the Future Circular Collider. We study scalable machine learning models for event reconstruction in electron-positron collisions based on a full detector simulation. Particle-flow reconstruction can be formulated as a supervised learning task using tracks and calorimeter clusters. We compare a graph neural network and kernel-based transformer and demonstrate that we can avoid quadratic operations while achieving realistic reconstruction. We show that hyperparameter tuning significantly improves the performance of the models. The best graph neural network model shows improvement in the jet transverse momentum resolution by up to 50% compared to the rule-based algorithm. The resulting model is portable across Nvidia, AMD and Habana hardware. Accurate and fast machine-learning based reconstruction can significantly improve future measurements at colliders.

Physics↗
DOE OSTI2026

Delving into the depths of NGC 3783 with XRISM V. Broad-band modelling of ionized outflows

The Seyfert 1 galaxy NGC 3783 hosts a multi-phase warm absorber (WA) that has been extensively studied in the X-ray band. High-resolution spectra from 2000−2001 revealed a complex outflow with multiple ionization and velocity components. Two decades later, new XMM-Newton and XRISM observations allow us to investigate the long-term evolution of these outflows. We performed joint spectral modelling of the XMM-Newton /RGS and XRISM/Resolve time-averaged spectra using the pion photoionization code within SPEX. We derived the ionization parameter, column density, turbulent velocity, and outflow velocity for each absorption component, and investigated their thermal stability and absorption measure distribution (AMD) to characterize the physical and dynamical properties of the WA in NGC 3783 in 2024. We compared these results with the 2000−2001 epoch to assess long-term variability, stability, and possible changes in the absorber population. We identify eight WA components spanning log ξ = 1.08 − 3.38 and outflow velocities of 480−1230 km s −1 . The ranges of column densities and turbulent velocities remain broadly consistent with the WAs from 2000−2001, but the earlier data contained more low-ionization, high-velocity components. The total column density of all the outflows in 2024 is 1.5 times larger than in 2000−2001, which means that it has been replenished by fresh material. The dominant unresolved transition array (UTA) absorber (component B3) has increased its column density by a factor of three while maintaining a similar ionization parameter. The WAs in NGC 3783 have undergone significant structural and dynamical evolution over the past 24 years.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Application of performance portability solutions for GPUs and many-core CPUs to track reconstruction kernels

Next generation High-Energy Physics (HEP) experiments are presented with significant computational challenges, both in terms of data volume and processing power. Using compute accelerators, such as GPUs, is one of the promising ways to provide the necessary computational power to meet the challenge. The current programming models for compute accelerators often involve using architecture-specific programming languages promoted by the hardware vendors and hence limit the set of platforms that the code can run on. Developing software with platform restrictions is especially unfeasible for HEP communities as it takes significant effort to convert typical HEP algorithms into ones that are efficient for compute accelerators. Multiple performance portability solutions have recently emerged and provide an alternative path for using compute accelerators, which allow the code to be executed on hardware from different vendors. We apply several portability solutions, such as Kokkos, SYCL, C++17 std::execution::par, Alpaka, and OpenMP/OpenACC, on two mini-apps extracted from the mkFit project: p2z and p2r. These apps include basic kernels for a Kalman filter track fit, such as propagation and update of track parameters, for detectors at a fixed z or fixed r position, respectively. The two mini-apps explore different memory layout formats. We report on the development experience with different portability solutions, as well as their performance on GPUs and many-core CPUs, measured as the throughput of the kernels from different GPU and CPU vendors such as NVIDIA, AMD and Intel.

Kwok, Ka Hei Martin↗
DOE OSTI2024

Evaluating Performance Portability with the CMS Heterogeneous Pixel Reconstruction code

In the past years the landscape of tools for expressing parallel algorithms in a portable way across various compute accelerators has continued to evolve significantly. There are many technologies on the market that provide portability between CPU, GPUs from several vendors, and in some cases even FPGAs. These technologies include C++ libraries such as Alpaka and Kokkos, compiler directives such as OpenMP, the SYCL open specification that can be implemented as a library or in a compiler, and standard C++ where the compiler is solely responsible for the offloading. Given this developing landscape, users have to choose the technology that best fits their applications and constraints. For example, in the CMS experiment the experience so far in heterogeneous reconstruction algorithms suggests that the full application contains a large number of relatively short computational kernels and memory transfer operations. In this work we use a stand-alone version of the CMS heterogeneous pixel reconstruction code as a realistic use case of HEP reconstruction software that is capable of leveraging GPUs effectively. We summarize the experience of porting this code base from CUDA to Alpaka, Kokkos, SYCL, std::par, and OpenMP offloading. We compare the event processing throughput achieved by each version on NVIDIA and AMD GPUs as well as on a CPU, and compare those to what a native version of the code achieves on each platform.

Andriotis, Nikolaos↗
DOE OSTI2024

Porting ATLAS Fast Calorimeter Simulation to GPUs with Performance Portable Programming Models

FastCaloSim is a parameterized simulation of the particle energy response and of the energy distribution in the ATLAS calorimeter. It is a relatively small and self-contained package with massive inherent parallelism and captures the essence of GPU offloading via important operations like data transfer, memory initialization, floating point operations, and reduction. It was identified by the High Energy Physics Center for Computational Excellence project as a good testbed for evaluating the performance and ease of portability of programming models. In this paper, we will discuss the results of our evaluation of the porting process to Kokkos, SYCL, Alpaka, OpenMP and std::par (nvc++), and compare performance on NVIDIA, AMD and Intel GPUs, as well as multicore CPUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Experience with the alpaka performance portability library in the CMS software

ion Library for Parallel Kernel Acceleration) is a header-only C++ library that provides performance portability across different back-ends, abstracting the underlying levels of parallelism. It supports serial and parallel execution on CPUs, and extremely parallel execution on NVIDIA, AMD and Intel GPUs.This contribution will show how alpaka is used in the CMS software to develop and maintain a single code base; to use different toolchains to build the code for each supported back-end, and link them into a single application; to seamlessly select the best backend at runtime, and implement portable reconstruction algorithms that run efficiently on CPUs and GPUs from different vendors. It will describe the validation and deployment of the alpaka-based implementation in the CMS High Level Trigger, and highlight how it achieves near-native performance.

Alawieh, Jaafar [CERN]↗
DOE OSTI2013

Palynological study of the genera Ruellia, Ecbolium, Asystasia, Blepharis and Dicliptera (Acanthaceae) of Yemen

Pollen morphology of five genera of the family Acanthaceae, namely Ruellia, Blepharis, Asystasia, Ecbolium and Dicliptera (Acanthaceae) of Yemen has been examined using light and scanning electron microscope. Pollen descriptions were provided with two shapes distinguished, spheroidal and prolate. Most of the pollen grains were tricolporate amd psuedocolpi except those of Blepharis which are colpate. The surface is coarsely reticulate, in addition to the lumina that varies in size.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Automated Hybrid Variance Reduction on Advanced Architectures in the Shift Monte Carlo Code

Monte Carlo transport methods are the most accurate schemes for solving problems with complex energy and spatial features, but they come with a high computational cost. Although hybrid methods have enabled the use of Monte Carlo transport for a large class of problems, they still require significant computing resources. Modern multicore CPUs with large numbers of compute cores and graphical processing units (GPUs) provide opportunities to optimize the memory and run-time costs of hybrid Monte Carlo methods. This paper documents the development and analysis of three Monte Carlo transport algorithms that support hybrid transport using the consistent adjoint-driven importance sampling (CADIS) and forward-weighted CADIS methods in the Shift Monte Carlo code: history-based transport using static and dynamic threading on multicore CPUs and event-based transport enabling weight window tracking on GPUs. The results are shown for two challenging hybrid problems on the Frontier supercomputer at the Oak Ridge Leadership Computing Facility. The results show that all three methods yield good performance and enable solutions of difficult fixed-source transport problems in less than 2 min on 20 nodes of Frontier. Dynamic threading was observed to give up to 20% better scaling behavior than static threading. Moreover, the AMD Instinct 250X GPU was found to give 9 to 11 times greater throughput per graphics compute die than the best CPU performance. In conclusion, additional opportunities for optimization of hybrid transport on GPUs are discussed.

Denovo↗
DOE OSTI2026

Application of Portable Parallelization Strategies for GPUs on track reconstruction kernels

Utilizing the computational power of GPUs is one of the key ingredients to meet the computing challenges presented to the next generation of High-Energy Physics (HEP) experiments. Unlike CPUs, developing software for GPUs often involves using architecturespecific programming languages promoted by the GPU vendors and hence limits the platform that the code can run on. Various portability solutions have been developed to achieve portable, performant software across different GPU vendors. Given the rapid evolution of these portability solutions, an early adoption of them in simple HEP testbed applications will help us understand the strengths and weaknesses of respective approaches.We apply several portability solutions, including Alpaka, Kokkos, SYCL and std::execution::par, on kernels for track propagation extracted from the mkFit project. We report on the development experience of the same application with different portability solutions, as well as their performance on GPUs, measured as the throughput of the kernels, from different manufacturers such as NVIDIA, AMD and Intel.

Kwok, Martin [Fermilab] (ORCID:0000000286936146)↗
DOE OSTI2022

Interpretable AI forecasting for numerical relativity waveforms of quasicircular, spinning, nonprecessing binary black hole mergers

We present a deep-learning artificial intelligence model (AI) that is capable of learning and forecasting the late-inspiral, merger and ringdown of numerical relativity waveforms that describe quasicircular, spinning, nonprecessing binary black hole mergers. We used the NRHybSur3dq8 surrogate model to produce train, validation and test sets of ℓ = |m| = 2 waveforms that cover the parameter space of binary black hole mergers with mass ratios q ≤ 8 and individual spins |s$^{z}_ {(1,2)}$| ≤ 0.8. These waveforms cover the time range t ∊ [-5000 M, 130 M], where t = 0M marks the merger event, defined as the maximum value of the waveform amplitude. We harnessed the ThetaGPU supercomputer at the Argonne Leadership Computing Facility to train our AI model using a training set of 1.5 million waveforms. We used 16 NVIDIA DGX A100 nodes, each consisting of 8 NVIDIA A100 Tensor Core GPUs and 2 AMD Rome CPUs, to fully train our model within 3.5 h. Our findings show that artificial intelligence can accurately forecast the dynamical evolution of numerical relativity waveforms in the time range t ∊ [-100 M, 130 M]. Sampling a test set of 190,000 waveforms, we find that the average overlap between target and predicted waveforms is ≳99% over the entire parameter space under consideration. We also combined scientific visualization and accelerated computing to identify what components of our model take in knowledge from the early and late-time waveform evolution to accurately forecast the latter part of numerical relativity waveforms. This work aims to accelerate the creation of scalable, computationally efficient and interpretable artificial intelligence models for gravitational wave astrophysics

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Direct observations of shape fluctuation in long-time atomistic simulations of metallic nanoclusters

Metallic nanoclusters are functional materials whose unique physical and chemical properties are sensitively controlled by their shapes and structures. An in-depth understanding of their morphological stability is therefore of crucial importance. It has been well documented by transmission electron microscopy (TEM) studies that metallic nanoclusters can interconvert between different isomers. However, the relevant mechanisms remain elusive because the timescales of such shape fluctuations are too short to be resolved experimentally and yet too long for conventional atomistic simulations. By employing massively parallel accelerated molecular dynamics (AMD) simulations reaching timescales of milliseconds, here we provide a clear description of the dynamical processes leading to shape fluctuation in metallic nanoclusters of platinum, silver, copper, and gold at different sizes and temperatures. In all these materials, direct transformations between face-centered-cubic and fivefold symmetric structures (decahedron or icosahedron) are observed away from the melting point. These transitions occur following either a slip-mediated twinning mechanism or a surface-reconstruction driven process. The identified pathways are shown to be reversible, allowing for genuine shape fluctuation processes that do not involve melting or other external factors.

36 MATERIALS SCIENCE↗