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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

NuMI Graphite Target Fin Removal Assembly

Materials scientists want to study the irradiated graphite target from the Neutrino at the Main Injector (NuMI) beam line. In order to gather these irradiated graphite fins from the target canister, it will have to be done remotely. Therefore, a removal assembly will need to be created in order to do this efficiently and well. This project aims to make progressive steps towards deploying the final target removal assembly. Furthermore, calculations related to the removal assembly design were done, and tests were planned to discover further information about the feasibility of this design. The main result from this project is the deflection of the cantilever arm, which is 0.354 inches due to the weight of the beam and cutting tool. Additionally, more results of this project are the testing assembly CAD model and the feasibility of design. This project concludes that there is still more work that needs to be done for the removal assembly to be deployed, but there were foundational steps that were made in the implementation of this design. Finally, there should be further steps and tests to determine the feasibility of this removal assembly.

Malovski, Azra [NIU, DeKalb]↗
DOE OSTI2023

Interconnection and Interoperability Requirements of Hydrogen Assets to Enable Grid Integration

Traditionally, the inverters used for distributed energy resources (DERs) including solar, energy storage and hydrogen fuel cells are grid following assets. Grid following assets track real power and reactive power setpoints decided by either a local autonomous controller or a remote controller like a microgrid controller. In the past five years, multiple challenges have increased the need for grid forming inverters that can interface to a wide variety of energy resources. These grid forming inverters are becoming critical assets for power systems to enable the replacement of existing rotational machines and provide grid services such as grid resiliency services and black-start. Hydrogen assets (fuel cells) have the potential to successfully replace rotating machines and act as voltage and frequency master by leveraging the long-duration and seasonal energy storage capabilities of hydrogen technologies. This poster presents the progress made in budget period 1 of the proposed work. We will leverage an existing ARIES platform experimental setup to run power-hardware-in-the-loop and controller-hardware-in-the-loop experiments with grid forming fuel cell inverters to develop and document the standardization requirements.

electrolyzer↗
DOE OSTI2020

Savannah River Site H-Canyon Advancing Technologies for Remote Inspections - 20345

In 2017, the DOE Environmental Management Office of Technology Development (DOE-EM TD) sponsored the H-Canyon Advanced Technology Demonstration (ATD) to demonstrate to DOE facilities the value of using new commercial-off-the-shelf (COTS) and near-ready technologies to solve difficult problems and enhance worker safety. The DOE Savannah River Site (SRS) H-Canyon Air Exhaust Tunnel (HCAEX) inspection task was identified as representative of the hazardous, human denied environments which could benefit from advanced technologies. The HCAEX underground concrete tunnel is visually inspected biannually using a camera mounted on a remotely operated vehicle (ROV) designed and built by SRNL. While tunnel images have provided valuable visual information, it is desirable to have a higher order of understanding of the environment to support a more thorough structural integrity (SI) analysis and for long term planning purposes. As part of the ATD, the Concrete Integrated Product Team (CIPT) was formed to identify and evaluate available sensors and methods mature enough to remotely obtain tunnel concrete characterization data of high value and with a high probability of success. The team included SMEs and H-Canyon stakeholders in the field of concrete, nondestructive examination (NDE), structural integrity, sensors and remote systems from SRNL, SRNS, LANL, DOE-SR and the Army Corps of Engineering. The CIPT completed an in-depth identification of customer concrete inspection needs and potential technology solutions. Sensors and methods were evaluated on performance, data usefulness, cost and the feasibility of a successful deployment given the unique tunnel access challenges and environment. Two technologies were identified as promising by the CIPT for near term demonstration and evaluation: Lidar (Light Detection and Ranging) 3-dimensional (3D) mapping and remote robotic deployment of NDE instrumentation. Laser spectroscopy to characterize tunnel surface chemical changes was also of interest, but presently cost prohibitive. This paper will include a discussion of the two efforts underway to evaluate and implement the CIPT recommendations. First, the status of the November 2019 deployment of Lidar at a single location into the tunnel is presented. This initial deployment provided the team a learning curve and lessons learned on the challenges of tunnel deployment to include remote operation and data collection, stabilization of the sensor in high air flow (∼30 mph), ability to achieve a tolerance accuracy of 0.25-inches, and the probability to identify change in tunnel dimensions over time. Secondly, a discussion on the development of the Robotic Arm Concrete Inspection Test Bed capable of deploying NDE instruments to examine custom concrete forms will be presented. Concrete forms simulating the rough concrete surfaces, strength, composition and potential structural defects that can be found at our DOE EM facilities have been designed and built for the test bed. Two state-of-the art concrete NDE instruments have been identified as having potential to work on rough concrete walls, they are being tested and characterized as to their ability to provide desired structural integrity data to include wall thickness and defect identification on the developed test beams. Lastly, lessons learned, and the path forward will be presented. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Remote Americium Detection Using an Optical Sensor: A D-Optimal Strategy for Efficient PLS-Based Modeling

A fiber-optic visible–near-infrared absorption spectroscopy system in a glove box was demonstrated for remote quantification of Am(III) (0–500 µM) and HNO 3 (0.1–9 M) using partial least squares regression (PLSR) models. The sensor platform, featuring a simple plug-and-play spectrophotometer, can enable noninvasive, real-time monitoring of actinide process solutions. To establish a flexible PLSR model calibration strategy, a D-optimal design developed using Nd(III) in previous studies was successfully extended to an actinide system with Am(III) to effectively minimize sample set size while maintaining robust prediction performance. The results suggest strong spectral similarities between Nd(III) and Am(III) and validate Nd(III) as an effective optical surrogate for trivalent actinide species. This work also supports the generalizability of a D-optimal training set selection approach for two-factor systems. The PLS1 models for Am(III) and HNO 3 outperformed a PLS2 model and maintained reasonable performance in the presence of interfering U(VI). The resulting sensor system and multivariate approach provides a flexible and scalable solution for process monitoring, control, and safety in diverse nuclear applications.

actinide↗
DOE OSTI2022

Overview of the MOSAiC expedition: Snow and sea ice

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Assessment of the Electrical Substation-Grid Testbed with Inside/Outside Devices and Distributed Ledger Technology

The electrical substation-grid testbed was created to integrate the GOOSE and/or DNP (Distributed Network Protocol) messages with time synchronized sources and Distributed Ledger Technology (DLT). The objective was to study the impact of faults and cyber-events at an electrical substation with inside (protective relays) and outside (power meters) substation devices. The electrical substation-grid testbed was based on the design of a 34.5/ 12.47 kV electrical substation (sectionalized bus configuration) with two power transformers, connected to radial power lines and load feeders. The electrical substation-grid testbed was installed at 252 lab space (Advanced Power System Protection), Grid Research Integration and Deployment Center (GRID-C), Oak Ridge National Laboratory. This testbed was created for Task 5, DarkNet project. The electrical substation-grid testbed was created to simulate fault and/or cyber events that could potentially result in damage to the electrical infrastructure. In addition, tests were run that are usually not allowed to be performed in an operational electrical power grid, because these test scenarios could trip breakers and/or generate fault situations that could potentially damage equipment. The number of tests performed in the electrical substation-grid testbed were executed in a better way than in a real electrical substation and/or power grid, because multiple tests could be run in a short period of time, and complex permits, and safety/ schedule restrictions like in a real electrical substation environment were not needed. The electrical substation-grid testbed was created using real measurement, communication, and protection devices that are used by electrical utilities, to have same conditions that we could observe in a real power grid or electrical substation. The electrical substation-grid testbed was based on using a real time simulator and expansion box with amplifiers that were wired to electrical substation-grid devices. This hardware-in-the-loop (HIL) was provided by protective relays, power meters, ethernet switches, remote terminal units, synchronized timing network clock, DLT devices, workstations, and servers. This report includes the design, installation, and assessment of the electrical substation-grid testbed that was similar to an operational electrical substation, integrating the power system protection, communication, and control systems. The results for the electrical substation-grid testbed were based on:• verifying the analog signals for protective relays and power meters, • observing the synchronized time source frame at devices, • authenticating the GOOSE (IEC 61850) and DNP messages from power meters and protective relays, and • verifying the trip conditions of protective relays at fault tests with the power system fault event detection, using DLT devices. For future work, the electrical substation-grid testbed with protective relays and power meters, using DLT and synchronized time source from DarkNet, will be used to study the impact of cyber-events at inside and outside substation devices. Advanced algorithms for detecting cyber-events produced by non-desired protective relay settings will be studied, to improve the detection and reliability of protection, control, and communication systems at power grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Field Programmable Gate Array-Based Reactor Protection Systems and Potential for Inclusion of Secure Elements to Improve Cybersecurity

For acceptable implementations of technologies like wireless communications, remote monitoring, etc., strong mitigations must be developed and evaluated to ensure that new attack pathways do not increase risk for Advanced Reactors. Secure Elements can be adopted and adapted for this purpose based on tamper resistance and cryptographic abilities, but research must be done to properly integrate into critical components such as FPGA-based Important to Safety systems in conjunction with current and future regulations on cyber security features in Advanced Reactors. Typically, the integration of a Secure Element happens during the POST and UEFI boot of a computing platform, performed by the Operating System, which is not possible with FPGAs because they do not include these firmware components. Work must be done to identify a reliable and secure method for integration in FPGA-based systems which lack Operating Systems and therefore complex boot procedures, system calls, etc.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Field Programmable Gate Array-Based Reactor Protection Systems and Potential for Inclusion of Secure Elements to Improve Cybersecurity

For acceptable implementations of technologies like wireless communications, remote monitoring, etc., strong mitigations must be developed and evaluated to ensure that new attack pathways do not increase risk for Advanced Reactors. Secure Elements can be adopted and adapted for this purpose based on tamper resistance and cryptographic abilities, but research must be done to properly integrate into critical components such as FPGA-based Important to Safety systems in conjunction with current and future regulations on cyber security features in Advanced Reactors. Typically, the integration of a Secure Element happens during the POST and UEFI boot of a computing platform, performed by the Operating System, which is not possible with FPGAs because they do not include these firmware components. Work must be done to identify a reliable and secure method for integration in FPGA-based systems which lack Operating Systems and therefore complex boot procedures, system calls, etc.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Application of emerging monitoring techniques at the Illinois Basin – Decatur Project

The Illinois Basin – Decatur Project is a large-scale carbon capture and storage demonstration project located in Decatur, Illinois, USA. In this project, one million metric tons of carbon dioxide (CO 2 ) was captured from an ethanol production facility and successfully injected into a deep saline reservoir over a period of three years. The scale of this project presented an opportunity to explore emerging technologies for effective long-term monitoring of the carbon capture and storage site. This research documents the application of three emerging monitoring techniques: (1) a prototype “open-path” sensor, a method of continuously monitoring atmospheric CO 2 by applying tunable diode laser absorption spectroscopy to provide a warning system for personnel safety along pipelines and at wellheads; (2) the Greenhouse Gas Laser Imaging Tomography Experiment (GreenLITE), an automated system for measuring two-dimensional spatial distribution of atmospheric CO 2 concentrations; and (3) periodic aerial imagery, a method of documenting surface-vegetation dynamics to detect vegetative responses to CO 2 leaks. The objective of this work was to assess the advantages and limitations of these monitoring techniques and quantify their reliability over an extended deployment at an active industrial site. These results will aid in determining viability of long-term monitoring on a commercial scale.

42 ENGINEERING↗
DOE OSTI2020

Quantifying Leaf Chlorophyll Concentration of Sorghum from Hyperspectral Data Using Derivative Calculus and Machine Learning

Leaf chlorophyll concentration (LCC) is an important indicator of plant health, vigor, physiological status, productivity, and nutrient deficiencies. Hyperspectral spectroscopy at leaf level has been widely used to estimate LCC accurately and non-destructively. This study utilized leaf-level hyperspectral data with derivative calculus and machine learning to estimate LCC of sorghum. We calculated fractional derivative (FD) orders starting from 0.2 to 2.0 with 0.2 order increments. Additionally, 43 common vegetation indices (VIs) were calculated from leaf spectral reflectance factor to make comparisons with reflectance-based data. Within the modeling pipeline, three feature selection methods were assessed: Pearson’s correlation coefficient (PCC), partial least squares based variable importance in the projection (VIP), and random forest-based mean decrease impurity (MDI). Finally, we used partial least squares regression (PLSR), random forest regression (RFR), support vector regression (SVR), and extreme learning regression (ELR) to estimate the LCC of sorghum. Results showed that: (1) increasing derivative order can show improved model performance until certain order for reflectance-based analysis; however, it is inconclusive to state that a particular order is optimal for estimating LCC of sorghum; (2) VI-based modeling outperformed derivative augmented reflectance factor-based modeling; (3) mean decrease impurity was found effective in selecting sensitive features from large feature space (reflectance-based analysis), whereas simple Pearson’s correlation coefficient worked better with smaller feature space (VI-based analysis); and (4) SVR outperformed all other models within reflectance-based analysis; alternatively, ELR with VIs from original reflectance yielded slightly better results compared to all other models.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Large Game Distribution Camera Study at Los Alamos National Laboratory

The unique habitats at the Laboratory support a diverse community of wildlife. The habitat types that include Pinon Juniper, Ponderosa Pine, and Mixed-conifer forests each provide different resources important for a variety of species. Wildlife monitoring for large game animals can be challenging because they avoid interactions with humans, and prefer undeveloped areas. This study was conducted to analyze the distribution of predators and other game animals seasonally across the Laboratory. This research informs decisions regarding wildlife management recommendations for conservation and protection. This study utilized game cameras to remotely monitor wildlife. As camera technology has advanced, game cameras have become adequate for documenting individuals, and are commonly used in wildlife studies on predation, abundance, occupancy, diversity, and endangered species detection. Twenty cameras were placed across the LANL landscape using a modified systematic sampling design. They were deployed in February 2018 and retrieved in January 2019, thus each camera sampled for one full year. All images were reviewed and the species, number, age, and sex of all animals in the photo were recorded. Here we present data for the most abundant species encountered: deer, elk, coyote, bear, bobcat, mountain lion, and fox respectively. The data were summarized by species and season. Future work will include occupancy modelling for each species. This will allow the development of heat maps showing species distributions across the Laboratory.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Developing a New Criticality Safety Hands-On Training Utilizing ZPPR Plates

Nuclear criticality safety is an extremely important part of the work at Los Alamos National Laboratory (LANL). As part of the work LANL performs to continue to keep criticality safety a top priority, LANL has developed and regularly teaches nuclear criticality safety training classes for both the United States Department of Energy Nuclear Criticality Safety Program as well as internal trainings for LANL employees. A portion of the training classes is comprised of hands-on demonstrations, where students get the opportunity to handle special nuclear material at the National Criticality Experiments Research Center (NCERC). One hands-on demonstration uses the “Class foils,” thin HEU foils which are stacked with lucite moderator plates. A hand-stack is performed until the multiplication reaches the “three-quarters rule,” where the demonstration is continued remotely on a vertical lift assembly up until the system is critical. This hands-on demonstration eventually achieves a critical configuration and follows the ANS-1 guidelines on an approach to critical. Another hands-on demonstration involves handling clad plutonium and neptunium spheres, and follows procedures using criticality safety evaluations to ensure that the hands-on demonstrations remain subcritical.This hands-on demonstration also involves the use of polyethylene shells around the plutonium sphere to demonstrate how additional reflector increases the criticality of a system. This paper is focused on developing a new hands-on demonstration using Zero Power Physics Reactor (ZPPR) plates. This new hands-on demonstration will follow the ANS-8 standards as it is not desired to achieve criticality with the ZPPR plates during the hands-on demonstration. A hands-on demonstration using multiple plutonium parts will likely be more applicable to personnel who handle plutonium on a daily basis, such as LANL glovebox operators.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Smart Packaging for Critical Energy Shipment (SPaCES)

Recent technical advances have brought forth revolutionary Smart Packaging (SP) technology. SP incorporates multiple electronics, chemical, and mechanical sensing technologies into packaging materials, and utilizes them to monitor and display package content status. SP can also employ embedded micro actuators to react to undesirable package conditions such as moisture/temperature anomalies or harmful chemical reactions and neutralize it. When further integrated with wireless sensing and secure networking, SP provides wholistic system-wide remote situation awareness capability for real-time crisis management. Finally, we also see that SP can be further integrated with 3D printing technology to offer form-factor customization and application specific solutions suitable for DOE (Department of Energy) NNSA’s (National Nuclear Security Administration) R/N (radiological/nuclear) material shipment and management needs; this has the potential to improve safety, security, and overall operation process quality. This report surveys SP technology as the state of the art (SOTA) and analyzes how it can integrate with cybersecurity and 3D printing to address NNSA’s critical R/N material shipment and storage requirements. This report further presents our FY23/24 investigation plan describing project background, goal, motivation, proposed work, and statement of work and cost.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Remote-Contact Catalysis for Target-Diameter Semiconducting Carbon Nanotube Arrays

Electrostatic catalysis has been an exciting development in chemical synthesis (beyond enzymes catalysis1 ) in recent years, boosting reaction rates and selectively producing certain reaction products2 . Most of the studies to date have been focused on using external electric field (EEF) to rearrange the charge distribution in small molecule reactions such as Diels-Alder addition3 , carbene reaction4 , etc. However, in order for these EEFs to be effective, a field on the order of 1 V/nm (10 MV/cm) is required, and the direction of the EEF has to be aligned with the reaction axis5 . Such a large and oriented EEF will be challenging for large-scale implementation, or materials growth with multiple reaction axis or steps. Here, we demonstrate that the energy band at the tip of an individual single-walled carbon nanotube6 (SWCNT) can be spontaneously shifted in a high-permittivity growth environment, with its other end in contact with a low-work function electrode (e.g., hafnium carbide or titanium carbide7 ). By adjusting the Fermi level at a point where there is a substantial disparity in the density of states (DOS) between semiconducting (s-) and metallic (m-) SWCNTs8 , we achieve effective electrostatic catalysis for s-SWCNT growth assisted by a weak EEF perturbation (200V/cm). This approach enables the production of high-purity (99.92%) s-SWCNT horizontal arrays with narrow diameter distribution (0.95±0.04 nm), targeting the requirement of advanced SWCNT-based electronics for future computing9-11. These findings highlight the potential of electrostatic catalysis in precise materials growth, especially for s-SWCNTs, and pave the way for the development of advanced SWCNT-based electronics12.

Wang, Jiangtao↗
DOE OSTI2022

Climate change penalty and benefit on surface ozone: a global perspective based on CMIP6 earth system models

Abstract This work presents an analysis of the effect of climate change on surface ozone discussing the related penalties and benefits around the globe from the global modelling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. As part of AerChemMIP (Aerosol Chemistry Model Intercomparison Project) all models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions trajectory (SSP3-7.0). A multi-model global average climate change benefit on surface ozone of −0.96 ± 0.07 ppbv °C −1 is calculated which is mainly linked to the dominating role of enhanced ozone destruction with higher water vapour abundances under a warmer climate. Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration on an annual basis as well as for boreal winter and summer varying spatially from −0.2 to −2 ppbv °C −1 , with strongest decline over tropical oceanic regions. The implication is that over regions remote from pollution sources (except over the Arctic) there is a consistent climate change benefit for baseline ozone due to global warming. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural biogenic volatile organic compounds emission sources with a rate ranging regionally from 0.2 to 2 ppbv C −1 , implying a regional surface ozone penalty due to global warming. Overall, the future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

Zanis, Prodromos↗
DOE OSTI2022

Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.

The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these polar regions covered by sea ice, the wind is relatively strong due to the absence of obstructions and redistributes a large part of the deposited snow mass, which complicates estimates for precipitation hardly distinguishable from blowing or drifting snow. Moreover, the snow mass balance in the sea ice system is still poorly understood, notably due to the complex structure of its surface. Quantitatively assessing the snow distribution on sea ice and its connection to the sea ice surface features is an important step to remove the snow mass balance uncertainties (i.e., snow transport contribution) in the Arctic environment. In this work we introduce snowBedFoam 1.0., a physics-based snow transport model implemented in the open-source fluid dynamics software OpenFOAM. We combine the numerical simulations with terrestrial laser scan observations of surface dynamics to simulate snow deposition in a MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) sea ice domain with a complicated structure typical for pressure ridges. The results demonstrate that a large fraction of snow accumulates in their vicinity, which compares favorably against scanner measurements. However, the approximations imposed by the numerical framework, together with potential measurement errors (precipitation), give rise to quantitative inaccuracies, which should be addressed in future work. The modeling of snow distribution on sea ice should help to better constrain precipitation estimates and more generally assess and predict snow and ice dynamics in the Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deep spectral CNN for laser induced breakdown spectroscopy

This work proposes a spectral convolutional neural network (CNN) operating on laser induced breakdown spectroscopy (LIBS) signals to learn to (1) disentangle spectral signals from the sources of sensor uncertainty (i.e., pre-process) and (2) get qualitative and quantitative measures of chemical content of a sample given a spectral signal (i.e., calibrate). Once the spectral CNN is trained, it can accomplish either task through a single feed-forward pass, with real-time benefits and without any additional side information requirements including dark current, system response, temperature and detector-to-target range. Our experiments demonstrate that the proposed method outperforms the existing approaches used by the Mars Science Lab for pre-processing and calibration for remote sensing observations from the Mars rover, ‘Curiosity’.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks

Gigapixel images are prevalent in scientific domains ranging from remote sensing, and satellite imagery to microscopy, etc. However, training a deep learning model at the natural resolution of those images has been a challenge in terms of both, overcoming the resource limit (e.g. HBM memory constraints), as well as scaling up to a large number of GPUs. In this paper, we trained Residual neural Networks (ResNet) on 22,528 x 22,528-pixel size images using a distributed spatial decomposition method on 2,304 GPUs on the Summit Supercomputer. We applied our method on a Whole Slide Imaging (WSI) dataset from The Cancer Genome Atlas (TCGA) database. WSI images can be in the size of 100,000 x 100,000 pixels or even larger, and in this work we studied the effect of image resolution on a classification task, while achieving state-of-the-art AUC scores. Moreover, our approach doesn't need pixel-level labels, since we're avoiding patching from the WSI images completely, while adding the capability of training arbitrary large-size images. This is achieved through a distributed spatial decomposition method, by leveraging the non-block fat-tree interconnect network of the Summit architecture, which enabled GPU-to-GPU direct communication. Finally, detailed performance analysis results are shown, as well as a comparison with a data-parallel approach when possible.

Tsaris, Aristeidis (aris)↗