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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 127 records · Page 7

Architectural Approaches for Integrating ADMS and DERMS: Challenges, Comparisons, and Real-World Use Cases

The electrical distribution landscape is rapidly transforming due to the proliferation of distributed energy resources (DERs) such as solar panels, wind turbines, battery storage systems, combined heat and power units, and electric vehicles, introducing variability and uncontrollability that traditional grid operators are ill-equipped to manage. This transformation is further accelerated by advancements in Information and Communication Technology infrastructure that connects control centers with end devices, demanding automation and a deeper understanding of new technologies by utility personnel. Advanced grid control techniques using system-level optimization, Artificial Intelligence, and Machine Learning at the enterprise level and distributed level are evolving to address these issues. There is also an opportunity to utilize the enormous data created by these new DER technologies in the grid. Advanced Distribution Management Systems (ADMS) and Distributed Energy Resource Management Systems (DERMS) are critical in addressing these challenges by automating grid operations and enhancing reliability. Given the relatively recent development of ADMS and DERMS, and the still relatively low level of ADMS and DERMS deployment in the industry, there is a notable deficiency in the comprehensive understanding of the challenges and benefits associated with these new technologies, especially with their complementary natures and integration architectures. This paper aims to bridge the knowledge gap in ADMS and DERMS integration, presenting three distinct integration architectures currently available, and discussing the challenges and benefits of each architecture to guide utilities, industry professionals, and researchers in optimizing grid management and decision-making processes for a resilient and efficient energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Anthropogenic extremely low volatility organics (ELVOCs) Govern the Growth of Molecular Clusters over the Southern Great Plains during the Springtime

New particle formation (NPF) and growth govern cloud condensation nuclei (CCN) concentrations in many regions. The mechanisms governing the nucleation of molecular clusters vary substantially in different regions of the atmosphere. Additionally, the growth of these clusters from ~2 to 20 nm sizes is often governed by the availability of extremely low volatility organic vapours (ELVOCs). While the pathways to ELVOC formation from the oxidation of biogenic monoterpenes with ozone is better understood, the chemical and mechanistic pathways for ELVOC formation from oxidation of anthropogenic organics are not well understood. We integrate measurements and three-dimensional regional model simulations with the Weather Research and Forecasting Model coupled to chemistry (WRF-Chem) to understand the processes governing new particle formation and growth and secondary organic aerosol (SOA) formation during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign at the Southern Great Plains (SGP) observatory in Oklahoma, and contrast it with a site within the Bankhead National Forest (BNF), Alabama in Southeast USA, where 5-year long measurements will begin in 2024. Simulations show that nucleation rates are at least an order of magnitude higher at SGP compared to BNF during the springtime days (April 28 and May 14, 2016), largely due to lower H2SO4 concentrations at BNF, which are needed for nucleation. In addition, the larger CS at BNF (compared to SGP) increase the loss of molecular clusters by coagulation to pre-existing particles. Among the 8 different nucleation mechanisms in WRF-Chem, we find that the amine+H2SO4 nucleation mechanism dominates at the SGP site, while the pure organic ion induced nucleation mechanism dominates over BNF. Through various WRF-Chem sensitivity simulations, we find that anthropogenic ELVOCs are critical for explaining the growth of newly formed particles and the resulting number size distribution observed near the surface at the SGP site during the daytime. In addition, we show that treating organic particles as semisolid, with strong diffusion-limited uptake of organic vapours, brings model predictions into closer agreement with the observed evolution of particle size distribution. Simulations also predict that anthropogenic SOA, formed by the oxidation of aromatic volatile organic compounds (VOCs), is the dominant organic aerosol component at SGP, while biogenic SOA dominates particle composition at the BNF site in Southeast USA on these days.

Shrivastava, ManishKumar B.↗

Thermal conductivity suppression in uranium-doped thorium dioxide due to phonon-spin interactions

In this work, impact of low level of uranium (U) atom substitution on thermal conductivity of thorium dioxide (ThO 2 ) is investigated. ThO 2 is an electronic insulator with a wide optical band-gap and no unpaired electrons whose thermal transport is governed by phonons. U-substitution introduces unpaired f-electrons resulting in paramagnetic behavior of U-ThO 2 at room temperature, which significantly suppresses its thermal conductivity. A single crystal of U-ThO 2 with graded composition of U is grown using a hydrothermal synthesis method, and thermal conductivity measurements are performed in regions with uniform composition of U at levels of 0%, 6%, 9% and 16%. Measured thermal conductivity profiles over 77–300 K temperature range are analyzed using an analytical expression for phonon-mediated thermal transport based on Klemens-Callaway model. Temperature dependent thermal conductivity is found to deviate significantly from the Rayleigh scattering trend expected for a simple substitutional point defect with a small perturbation to mass and interatomic forces. With the resonant scattering term, observed large suppression of thermal conductivity at low temperatures can be closely reproduced. Additionally, the extracted phonon-spin coupling constants imply a nonlinear relation of phonon-spin interaction intensity with respect to U doping percentage. Our study reveals how phonon-spin scattering contributed by unpaired f-electrons in U atoms influences thermal transport in the U-ThO 2 system.

36 MATERIALS SCIENCE↗

Phonon-Spin Scattering from Unpaired f-electrons in U atoms and It’s Influence on Thermal Transport in Uranium-doped Thorium Dioxide Single Crystals

In this work, impact of low level of uranium (U) atom substitution on thermal conductivity of thorium dioxide (ThO2) is investigated. ThO2 is an electronic insulator with a wide optical band-gap and no unpaired electrons whose thermal transport is governed by phonons. U-substitution introduces unpaired f-electrons resulting in paramagnetic behavior of U-ThO2 at room temperature, which significantly suppresses its thermal conductivity. A single crystal of U-ThO2 with graded composition of U is grown using a hydrothermal synthesis method, and thermal conductivity measurements are performed in regions with uniform composition of U at levels of 0%, 6%, 9% and 16%. Measured thermal conductivity profiles over 77–300 K temperature range are analyzed using an analytical expression for phonon-mediated thermal transport based on Klemens-Callaway model. Temperature dependent thermal conductivity is found to deviate significantly from the Rayleigh scattering trend expected for a simple substitutional point defect with a small perturbation to mass and interatomic forces. With the resonant scattering term, observed large suppression of thermal conductivity at low temperatures can be closely reproduced. Additionally, the extracted phonon-spin coupling constants imply a nonlinear relation of phonon-spin interaction intensity with respect to U doping percentage. Our study reveals how phonon-spin scattering contributed by unpaired f-electrons in U atoms influences thermal transport in the U-ThO2 system.

36 - MATERIALS SCIENCE↗

Screening analysis of enhanced weathering of igneous rocks and industrial waste materials

Enhanced weathering (EW) is a promising emerging carbon dioxide removal approach that involves harnessing and accelerating the natural weathering process by which atmospheric CO2 passively reacts with exposed alkaline minerals and is removed from the atmosphere. This manuscript reports on a screening level techno-economic analysis of EW. Two primary cases utilizing different sources of alkaline material are considered: (1) utilizing naturally occurring mined igneous rocks, and (2) utilizing industrial waste materials. The modeled EW process encompasses material purchase, comminution, transport, distribution of material on farmland, and measurement, reporting and verification of CO2 removal. Detailed sensitivities are performed to highlight promising scenarios for application. The analysis highlights that utilizing materials with high weathering potential in suitable locations may result in relatively low levelized cost of captured (less than $100 per total tonnes of CO2 captured from the atmosphere). NETL is publishing a detailed and transparent report titled “Enhanced Weathering: Techno-Economic and Life Cycle Screening Analysis” that includes more detail on the screening level techno-economic analysis and includes a life cycle analysis.

Leptinsky, Sarah [NETL Site Support Contractor, Na↗

The Amazon River‐Breeze Circulation Limits Detection of Aerosol‐Cloud Interactions in Warm Clouds

Increased aerosol concentrations can brighten low-level clouds and extend their lifetimes, but aerosol–cloud interactions (ACI) remain highly uncertain and difficult to quantify. We show that part of this uncertainty is caused by topographical influences on clouds, that is, those arising from land–water contrasts. This is demonstrated using satellite retrievals in regions with extensive river networks, such as the Amazon Basin. 15 years of MODerate resolution Imaging Spectroradiometer (MODIS) satellite data show cloud formation over the Amazon River basin is suppressed by 26% with warm low clouds above the river exhibiting a 22% smaller droplet effective radius and 18% higher droplet concentration ($N_d$) compared to adjacent land clouds. Thus, clouds above the river may appear polluted but are actually influenced by river-breeze circulations driven by the thermal contrast between the river and the surrounding land. These responses are robust in both wet and dry seasons, and tests using an improved MODIS retrieval product show cloud differences are unlikely due to retrieval artifacts. In situ measurements from the Green Ocean Amazon Experiment (GoAmazon) confirm that $N_d$ is elevated above rivers and are also higher when carbon monoxide concentrations are elevated near the large city of Manaus. Lagrangian airmass tracking over Manaus shows that regional-scale river-breeze circulations impact $N_d$ as much as the urban aerosol plume, complicating ACI attribution and highlighting the need to isolate land-surface effects to assess ACI in continental regions.

Aerosol-Cloud Interactions↗

Controlled phosphate doping into nanoscopic SiO 2 proton conducting membranes

This article describes a method to introduce phosphate (PO 4 ) into SiO 2 atomic layer deposition (ALD) films in a self-limiting fashion. The method involves the use of a less common phosphate precursor, trimethyl phosphite [P(OMe) 3 ], to introduce PO 4 as a low-level dopant, <1 at. %, into a SiO 2 ALD process using bis(ethylmethylamino)silane and a modified O 3 conversion. P(OMe) 3 does not deposit a film with typical oxygen sources but incorporates as PO 4 in an ABC-type ALD scheme at deposition temperatures ranging from 100 to 300 °C. Addition of up to ∼1 at. % of PO 4 does not significantly impact the film density or concentrations of carbon and nitrogen impurities, which are both <0.4 at. %. Despite the relatively low dopant concentrations, PO 4 incorporation is shown to have a large impact on transport properties of the film. When explored as proton (H + )-conducting membranes, undoped SiO 2 ALD films showed H + conductivities (3 × 10 −6 –8 × 10 −5 S cm −1 ) and low H 2 permeabilities (<10 −9 cm 2 s −1 ) when measured at room temperature. The addition of PO 4 is shown to increase H + conductivity to 2 × 10 −4 S cm −1 , while maintaining low H 2 permeability of <10 −9 cm 2 s −1 . The ratio of H + conductivity to H 2 permeability, a key performance metric for H + -conducting membranes used in water electrolyzers, exceeds that of commercial Nafion-117 membranes. Here, the moderate H + conductivity and very low H 2 permeability of PO 4 -doped SiO 2 films make them promising candidates as fluorine-free replacements for Nafion in applications such as water electrolysis, hydrogen fuel cells, and redox flow batteries.

Atomic layer deposition↗

Screening Analysis of Terrestrial Enhanced Rock Weathering of Igneous Rocks and Industrial Waste Materials

This poster, presented at the 17th Greenhouse Gas Control Technology Conference, reports on an NETL screening level techno-economic assessment of enhanced weathering (EW). EW is a promising emerging carbon dioxide removal approach that involves harnessing and accelerating the natural weathering process by which atmospheric CO2 passively reacts with exposed alkaline minerals and is removed from the atmosphere. Two primary cases utilizing different sources of alkaline material are considered: (1) utilizing naturally occurring mined igneous rocks, and (2) utilizing industrial waste materials. The analysis highlights that utilizing materials with high weathering potential in suitable locations may result in relatively low levelized cost of captured. NETL is publishing a detailed and transparent report titled “Enhanced Weathering: Techno-Economic and Life Cycle Screening Analysis” that includes more detail on the screening level techno-economic analysis and includes a life cycle analysis.

carbon dioxide removal↗

Lowering entry barriers to developing custom simulators of distributed applications and platforms with SimGrid

Researchers in parallel and distributed computing (PDC) often resort to simulation because experiments conducted using a simulator can be for arbitrary experimental scenarios, are less resource-, labor-, and time-consuming than their real-world counterparts, and are perfectly repeatable and observable. Many frameworks have been developed to ease the development of PDC simulators, and these frameworks provide different levels of accuracy, scalability, versatility, extensibility, and usability. Further, the SimGrid framework has been used by many PDC researchers to produce a wide range of simulators for over two decades. Its popularity is due to a large emphasis placed on accuracy, scalability, and versatility, and is in spite of shortcomings in terms of extensibility and usability. Although SimGrid provides sensible simulation models for the common case, it was difficult for users to extend these models to meet domain-specific needs. Furthermore, SimGrid only provided relatively low-level simulation abstractions, making the implementation of a simulator of a complex system a labor-intensive undertaking. In this work we describe developments in the last decade that have contributed to vastly improving extensibility and usability, thus lowering or removing entry barriers for users to develop custom SimGrid simulators.

97 MATHEMATICS AND COMPUTING↗

Optical 14 C Tracing for Biological and Pharmaceutical Applications Using Two-Color Cavity Ringdown Spectroscopy

Laser-based 14 C quantitation has been proposed as a more affordable, higher-throughput, table-top alternative to accelerator mass spectrometry (AMS). Here, we demonstrate the feasibility of a mid-IR 14 C detector based on two-color cavity ringdown spectroscopy (2C-CRDS) for low-level 14 C isotope tracing in biological studies. The 2C-CRDS technique quantifies the sample 14 C content by measuring the 14 CO 2 absorption signals from the combusted samples with mid-IR lasers. With 2C-CRDS, we previously demonstrated the most sensitive and accurate optical measurements of 14 CO 2 . The current detection sensitivity and quantitation accuracy of the instrument, at a few parts per quadrillion (where a quadrillion = 10 15 ) 14 C/C mole fraction, is competitive against AMS. Here, by applying the 2C-CRDS 14 C sensor to two applications relevant to 14 C-labeled biochemical analysis and pharmaceutical studies, we demonstrate sub-fCi level (where 1 fCi = 10 –15 Ci) quantitation of sample 14 C activity, with a minimum sample-size requirement of 3 mg of carbon. The current measurement throughput, ~25 min/sample, is largely limited by the sampling efficiency of the online combustion and CO 2 processing interface to the 2C-CRDS instrument. The possibility of a significantly improved measurement throughput of a few minutes per sample is suggested by the results of a flow-through 14 CO 2 sampling scheme. In conclusion, this improved measurement efficiency, combined with the relatively low cost and compact size of a 2C-CRDS sensor, could potentially revolutionize high-sensitivity 14 C tracing in biological, pharmaceutical, and clinical studies.

60 APPLIED LIFE SCIENCES↗

Organic Evaporation, Oxidation, and Hydrolysis Testing in Support of Hanford Sample-and-Send

The Hanford site has approximately 54 to 56 million gallons of radioactive mixed waste stored in 156 unretrieved underground storage tanks. The Hanford Waste Treatment and Immobilization Plant (WTP) is being built to treat and immobilize the tank waste. The baseline method for immobilization of Low Activity Waste (LAW) through the WTP is vitrification, but additional immobilization capacity is needed to supplement the initial LAW melters. An alternative cementitious waste form is being investigated for that future immobilization method. However, one impediment to a cementitious waste form is the presence of Land Disposal Restricted (LDR) organic chemicals in tank waste, which are regulated on a concentration based standard in the final waste form. Hence, if the quantity of organics in LAW is high enough, they must be destroyed or removed to make a waste form compatible with disposal in a mixed low level waste landfill. This work evaluates potential avenues for treatment of LDR organics to eliminate the impediment and permit possible use of a cementitious waste form. Vacuum evaporation testing to remove LDR organics consisted of preparing a non-radioactive LAW simulant, spiking that simulant with organic chemicals, and evaporating the mixture via differential distillation. The apparatus was a laboratory-scale vacuum evaporator operated at 60 ±5 torr absolute (vacuum evaporation). The LAW simulant represented the liquid expected to be retrieved from the Hanford tank farms at approximately 4.0 M [Na+] total sodium ion concentration. The concentration of the organic chemicals added was significantly higher than typically found in the tank waste samples since the higher levels were necessary to assist in analytical measurement and tracking of the spiked species.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Mojo: MLIR-based Performance-Portable HPC Science Kernels on GPUs for the Python Ecosystem

We explore the performance and portability of the novel Mojo language for scientific computing workloads on GPUs. As the first language based on the LLVM’s Multi-Level Intermediate Representation (MLIR) compiler infrastructure, Mojo aims to close performance and productivity gaps by combining Python’s interoperability and CUDA-like syntax for compile-time portable GPU programming. We target four scientific workloads: a seven-point stencil (memory-bound), BabelStream (memory-bound), miniBUDE (compute-bound), and Hartree–Fock (compute-bound with atomic operations); and compare their performance against vendor baselines on NVIDIA H100 and AMD MI300A GPUs. We show that Mojo’s performance is competitive with CUDA and HIP for memory-bound kernels, whereas gaps exist on AMD GPUs for atomic operations and for fast-math compute-bound kernels on both AMD and NVIDIA GPUs. Although the learning curve and programming requirements are still fairly low-level, Mojo can close significant gaps in the fragmented Python ecosystem in the convergence of scientific computing and AI.

Godoy, William [ORNL] (ORCID:0000000225905178)↗

FY25 Organic Evaporation Testing in Support of Hanford Sample-and-Send

The Hanford Waste Treatment and Immobilization Plant (WTP) is being built to treat and immobilize the approximately 56 million gallons of radioactive mixed waste stored in 156 underground storage tanks. The baseline method for immobilization of Low-Activity Waste (LAW) is vitrification, but additional immobilization capacity is needed to supplement the initial LAW melters. Additionally, efforts are being undertaken to accelerate the disposition of Pre-Treated Waste (PTW) in Hanford’s West Area. An alternative cementitious waste form is being investigated as an alternative immobilization method. However, one impediment to a cementitious waste form is the presence of Land Disposal Restricted (LDR) organic chemicals in tank waste, which are regulated on a concentration-based standard in the final waste form. Hence, if the quantity of organics in PTW and LAW is high enough, treatment may be needed to destroy or remove said organics to make a waste form compatible with disposal in a mixed low level waste landfill. This work evaluates evaporation as a potential avenue for treatment of LDR organics to eliminate the impediment and permit possible use of a cementitious waste form.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Microbial Ecology and Site Characteristics Underlie Differences in Salinity-Methane Relationships in Coastal Wetlands

Methane (CH 4 ) is a potent greenhouse gas emitted by archaea in anaerobic environments such as wetland soils. Tidal freshwater wetlands are predicted to become increasingly saline as sea levels rise due to climate change. Previous work has shown that increases in salinity generally decrease CH 4 emissions, but with considerable variation, including instances where salinization increased CH 4 flux. We measured microbial community composition, biogeochemistry, and CH 4 flux from field samples and lab experiments from four different sites across a wide geographic range. We sought to assess how site differences and microbial ecology affect how CH 4 emissions are influenced by salinization. CH 4 flux was generally, but not always, positively correlated with CO 2 flux, soil carbon, ammonium, phosphate, and pH. Methanogen guilds were positively correlated with CH 4 flux across all sites, while methanotroph guilds were both positively and negatively correlated with CH 4 depending on site. There was mixed support for negative relationships between CH 4 fluxes and concentrations of alternative electron acceptors and abundances of taxa that reduce them. CH 4 /salinity relationships ranged from negative, to neutral, to positive and appeared to be influenced by site characteristics such as pH and plant composition, which also likely contributed to site differences in microbial communities. The activity of site-specific microbes that may respond differently to low-level salinity increases is likely an important driver of CH 4 /salinity relationships. Our results suggest several factors that make it difficult to generalize CH 4 /salinity relationships and highlight the need for paired microbial and flux measurements across a broader range of sites.

54 ENVIRONMENTAL SCIENCES↗

Improving vertical detail in simulated temperature and humidity data using machine learning

Atmospheric models used for weather forecasting and climate predictions discretise the atmosphere onto a vertical grid. There are however atmospheric phenomena that occur on scales smaller than the thickness of those model layers. The formation of low-level clouds due to temperature inversions is an example. This leads to atmospheric models underestimating, or even missing, these clouds and their radiative effects. Using radiosonde observations as training data, a machine learning model is used to improve the vertical detail of modelled profiles of temperature and specific humidity. In addition, a physics-informed machine learning model is developed and compared to the traditional approach; showing improvements in the cloud fraction profiles calculated from its predictions. The vertically enhanced profiles also improve the representation of layers of convective inhibition and anomalous refractivity gradients. This work facilitates targeted improvements to the representation of certain atmospheric processes without the burden of increased memory and computational cost from increasing vertical resolution throughout the whole model.

54 ENVIRONMENTAL SCIENCES↗

The Two Arctic Wintertime Boundary Layer States: Disentangling the Role of Cloud and Wind Regimes in Reanalysis and Observations During MOSAiC

The wintertime central Arctic atmosphere comprises a radiatively clear and a radiatively opaque state, which are linked to synoptic forcing and mixed-phase clouds. Weather and climate models often lack process representations surrounding these states, but prior work mostly treated the problem as an aggregate of synoptic conditions, resulting in partially overlapping biases. Here, we disaggregate the Arctic states and confront ERA5 reanalysis with observations from the MOSAiC campaign over the central Arctic sea ice during winter 2019/2020. Low-level winds and liquid water path (LWP) are combined to derive different synoptic classes. Results show that the clear state is primarily formed by weak/moderate winds and the absence of liquid-bearing clouds, while strong winds and enhanced LWP primarily form the radiatively opaque state. ERA5 struggles to reproduce these basic statistics, shows too weak sensitivity of thermal radiation to synoptic forcing, and overestimates thermal radiation for similar LWP amounts. The latter is caused by a warm bias, which has a pronounced inversion structure and is largest in clear and calm conditions. Under strong synoptic forcing, the warm bias is constant with height and discrepancies in mixed-phase cloud altitude appear. Separating synoptic conditions is regarded as useful for process-oriented evaluation of the Arctic troposphere in models.

54 ENVIRONMENTAL SCIENCES↗

Engineering of 2‐ketoacid Decarboxylases for Production of Isobutanol and Other Fusel Alcohols in Saccharomyces cerevisiae

Isobutanol is a fusel alcohol that can be produced microbially for use as a biofuel or upgraded into sustainable aviation fuel (SAF). A key enzyme in the isobutanol biosynthetic pathway is 2-ketoacid decarboxylase (KDC), which irreversibly decarboxylates 2-ketoisovalerate (KIV) to yield isobutyraldehyde. However, many previously characterized KDC enzymes also act promiscuously on other 2-ketoacids, (e.g., pyruvate) to produce a related aldehyde (e.g., acetaldehyde). This unwanted side reaction is especially important when isobutanol is produced in Saccharomyces cerevisiae (S. cerevisiae) because it leads to pyruvate being diverted to ethanol. In order to make S. cerevisiae a strict isobutanologen, a KDC enzyme that is specific for KIV must be deployed. In this study, we used a combination of cell-based and in vitro enzyme assays to investigate KDC substrate specificity, characterizing a large set of homologs for KIV, pyruvate, and phenylpyruvate (PPV) activity. A diverse range of substrate specificities was discovered, and some previously uncharacterized KDCs were revealed to have high KIV activity and low pyruvate activity. Multi-site saturation mutagenesis (SSM) of one of these KDCs identified mutants with increased KIV activity, while maintaining low levels of pyruvate activity. In a KIV bioconversion experiment, bioprospected and engineered KDCs allowed similar KIV consumption to when using the previously characterized Lactococcus lactis KdcA, though with some ethanol also produced. The KDCs identified here show promise for production of isobutanol and other alcohols derived from 2-ketoacids, and the dataset of newly characterized KDCs can inform future efforts to understand and engineer substrate specificity in KDCs.

2-ketoacid decarboxylase↗

Architecture and performance of Perlmutter's 35 PB ClusterStor E1000 all-flash file system

NERSC's newest system, Perlmutter, features a 35 PB all-flash Lustre file system built on HPE Cray ClusterStor E1000. Here, we present its architecture, early performance figures, and performance considerations unique to this architecture. We demonstrate the performance of E1000 OSSes through low-level Lustre tests that achieve over 90% of the theoretical bandwidth of the SSDs at the OST and LNet levels. We also show end-to-end performance for both traditional dimensions of I/O performance (peak bulk-synchronous bandwidth) and nonoptimal workloads endemic to production computing (small, incoherent I/Os at random offsets) and compare them to NERSC's previous system, Cori, to illustrate that Perlmutter achieves the performance of a burst buffer and the resilience of a scratch file system. Finally, we discuss performance considerations unique to all-flash Lustre and present ways in which users and HPC facilities can adjust their I/O patterns and operations to make optimal use of such architectures.

97 MATHEMATICS AND COMPUTING↗