Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “SaaS”

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 163 records · Page 9

MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science Through Cloud-enabled Climate Analytics-as-a-service

Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we it see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRAAS) is an example of cloud-enabled CAaaS built on this principle. MERRAAS enables MapReduce analytics over NASAs Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRAAS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRAAS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to organizational change, fosters innovation and experimentation, facilitates technology transfer, and provides the agility required to meet our customers' increasing and changing needs. Cloud Computing is providing a new tier in the data services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. For climate science, Cloud Computing's capacity to engage communities in the construction of new capabilies is perhaps the most important link between Cloud Computing and Big Data.

Data Analytics↗

Integrated Test and Evaluation Flight Test 3 Flight Test Plan

The desire and ability to fly Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) is of increasing urgency. The application of unmanned aircraft to perform national security, defense, scientific, and emergency management are driving the critical need for less restrictive access by UAS to the NAS. UAS represent a new capability that will provide a variety of services in the government (public) and commercial (civil) aviation sectors. The growth of this potential industry has not yet been realized due to the lack of a common understanding of what is required to safely operate UAS in the NAS. NASA's UAS Integration into the NAS Project is conducting research in the areas of Separation Assurance/Sense and Avoid Interoperability, Human Systems Integration (HSI), and Communication to support reducing the barriers of UAS access to the NAS. This research is broken into two research themes namely, UAS Integration and Test Infrastructure. UAS Integration focuses on airspace integration procedures and performance standards to enable UAS integration in the air transportation system, covering Sense and Avoid (SAA) performance standards, command and control performance standards, and human systems integration. The focus of Test Infrastructure is to enable development and validation of airspace integration procedures and performance standards, including the integrated test and evaluation. In support of the integrated test and evaluation efforts, the Project will develop an adaptable, scalable, and schedulable relevant test environment capable of evaluating concepts and technologies for unmanned aircraft systems to safely operate in the NAS. To accomplish this task, the Project will conduct a series of Human-in-the-Loop and Flight Test activities that integrate key concepts, technologies and/or procedures in a relevant air traffic environment. Each of the integrated events will build on the technical achievements, fidelity and complexity of the previous tests and technical simulations, resulting in research findings that support the development of regulations governing the access of UAS into the NAS.

Unmanned↗

UAS Integration in the NAS Project: Integrated Test and Evaluation (IT&E) Flight Test 3

The desire and ability to fly Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) is of increasing urgency. The application of unmanned aircraft to perform national security, defense, scientific, and emergency management are driving the critical need for less restrictive access by UAS to the NAS. UAS represent a new capability that will provide a variety of services in the government (public) and commercial (civil) aviation sectors. The growth of this potential industry has not yet been realized due to the lack of a common understanding of what is required to safely operate UAS in the NAS. NASA's UAS Integration into the NAS Project is conducting research in the areas of Separation Assurance/Sense and Avoid Interoperability, Human Systems Integration (HSI), and Communication to support reducing the barriers of UAS access to the NAS. This research is broken into two research themes namely, UAS Integration and Test Infrastructure. UAS Integration focuses on airspace integration procedures and performance standards to enable UAS integration in the air transportation system, covering Sense and Avoid (SAA) performance standards, command and control performance standards, and human systems integration. The focus of Test Infrastructure is to enable development and validation of airspace integration procedures and performance standards, including the integrated test and evaluation. In support of the integrated test and evaluation efforts, the Project will develop an adaptable, scalable, and schedulable relevant test environment capable of evaluating concepts and technologies for unmanned aircraft systems to safely operate in the NAS. To accomplish this task, the Project will conduct a series of Human-in-the-Loop and Flight Test activities that integrate key concepts, technologies and/or procedures in a relevant air traffic environment. Each of the integrated events will build on the technical achievements, fidelity and complexity of the previous tests and technical simulations, resulting in research findings that support the development of regulations governing the access of UAS into the NAS.

interoperability↗

High Resolution Nature Runs and the Big Data Challenge

NASA's Global Modeling and Assimilation Office at Goddard Space Flight Center is undertaking a series of very computationally intensive Nature Runs and a downscaled reanalysis. The nature runs use the GEOS-5 as an Atmospheric General Circulation Model (AGCM) while the reanalysis uses the GEOS-5 in Data Assimilation mode. This paper will present computational challenges from three runs, two of which are AGCM and one is downscaled reanalysis using the full DAS. The nature runs will be completed at two surface grid resolutions, 7 and 3 kilometers and 72 vertical levels. The 7 km run spanned 2 years (2005-2006) and produced 4 PB of data while the 3 km run will span one year and generate 4 BP of data. The downscaled reanalysis (MERRA-II Modern-Era Reanalysis for Research and Applications) will cover 15 years and generate 1 PB of data. Our efforts to address the big data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS), a specialization of the concept of business process-as-a-service that is an evolving extension of IaaS, PaaS, and SaaS enabled by cloud computing. In this presentation, we will describe two projects that demonstrate this shift. MERRA Analytic Services (MERRA/AS) is an example of cloud-enabled CAaaS. MERRA/AS enables MapReduce analytics over MERRA reanalysis data collection by bringing together the high-performance computing, scalable data management, and a domain-specific climate data services API. NASA's High-Performance Science Cloud (HPSC) is an example of the type of compute-storage fabric required to support CAaaS. The HPSC comprises a high speed Infinib and network, high performance file systems and object storage, and a virtual system environments specific for data intensive, science applications. These technologies are providing a new tier in the data and analytic services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. In our experience, CAaaS lowers the barriers and risk to organizational change, fosters innovation and experimentation, and provides the agility required to meet our customers' increasing and changing needs

big data analysis↗

UAS-NAS Integrated Human in the Loop: Test Environment Report

The desire and ability to fly Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) is of increasing urgency. The application of unmanned aircraft to perform national security, defense, scientific, and emergency management are driving the critical need for less restrictive access by UAS to the NAS. UAS represent a new capability that will provide a variety of services in the government (public) and commercial (civil) aviation sectors. The growth of this potential industry has not yet been realized due to the lack of a common understanding of what is required to safely operate UAS in the NAS. NASA's UAS Integration in the NAS Project is conducting research in the areas of Separation Assurance/Sense and Avoid Interoperability (SSI), Human Systems Integration (HSI), and Communication to support reducing the barriers of UAS access to the NAS. This research was broken into two research themes namely, UAS Integration and Test Infrastructure. UAS Integration focuses on airspace integration procedures and performance standards to enable UAS integration in the air transportation system, covering Sense and Avoid (SAA) performance standards, command and control performance standards, and human systems integration. The focus of the Test Infrastructure theme was to enable development and validation of airspace integration procedures and performance standards, including the execution of integrated test and evaluation. In support of the integrated test and evaluation efforts, the Project developed an adaptable, scalable, and schedulable relevant test environment incorporating live, virtual, and constructive elements capable of validating concepts and technologies for unmanned aircraft systems to safely operate in the NAS. To accomplish this task, the Project planned to conduct three integrated events: a Human-in-the-Loop simulation and two Flight Test series that integrated key concepts, technologies and/or procedures in a relevant air traffic environment. Each of the integrated events were built on the technical achievements, fidelity and complexity of previous simulations and tests, resulting in research findings that support the development of regulations governing the access of UAS into the NAS. The purpose of this document is to describe how well the system under test was representative

Human in the Loop↗

November 2013 Analysis of High Energy Electrons on the Japan Experimental Module (JEM: Kibo)

Albedo (precipitating/splash) electrons, created by galactic cosmic rays (GCR) interaction with the upper atmosphere move upwards away from the surface of the earth. In the past validation work these particles were often considered to have negligible contribution to astronaut radiation exposure on the International Space Station (ISS). Estimates of astronaut exposure based on the available Computer Aided Design (CAD) models of ISS consistently underestimated measurements onboard ISS when the contribution of albedo particles to exposure were neglected. Recent measurements of high energy electrons outside ISS Japan Experimental Module (JEM) using Exposed Facility (EF), Space Environment Data Acquisition Equipment - Attached Payload (SEDA-AP) and Standard DOse Monitor (SDOM), indicates the presence of high energy electrons at ISS altitude. In this presentation the status of these energetic electrons is reviewed and mechanism for the creation of these particles inside/outside South Atlantic Anomaly (SAA) region explained. In addition, limited dosimetric evaluation of these electrons at 600 MeV and 10 GeV is presented.

Badavi, Francis F.↗

Development of Augmented Spark Impinging Igniter System for Methane Engines

The Lunar Cargo Transportation and Landing by Soft Touchdown (Lunar CATALYST) program is establishing multiple no-funds-exchanged Space Act Agreement (SAA) partnerships with U.S. private sector entities. The purpose of this program is to encourage the development of robotic lunar landers that can be integrated with U.S. commercial launch capabilities to deliver payloads to the lunar surface. As part of the efforts in Lander Technologies, NASA Marshall Space Flight Center (MSFC) is developing liquid oxygen (LOX) and liquid methane (LCH4) engine technology to share with the Lunar CATALYST partners. Liquid oxygen and liquid methane propellants are attractive owing to their relatively high specific impulse for chemical propulsion systems, modest storage requirements, and adaptability to NASA's Journey to Mars plans. Methane has also been viewed as a possible propellant choice for lunar missions, owing to the performance benefits and as a technology development stepping stone to Martian missions. However, in the development of methane propulsion, methane ignition has historically been viewed as a high risk area in the development of such an engine. A great deal of work has been conducted in the past decade devoted to risk reduction in LOX/CH4 ignition. This paper will review and summarize the history and results of LOX/CH4 ignition programs conducted at NASA. More recently, a NASA-developed Augmented Spark Impinging (ASI) igniter body, which utilizes a conventional spark exciter system, is being tested with LOX/CH4 to help support internal and commercial engine development programs, such as those in Lunar CATALYST. One challenge with spark exciter systems, especially at altitude conditions, is the ignition lead that transmits the high voltage pulse from the exciter to the spark igniter (spark plug). The ignition lead can be prone to corona discharge, reducing the energy delivered by the spark and potentially causing non-ignition events. For the current work, a commercial compact exciter system, which eliminates this high voltage cabling, was tested at altitude conditions. A modified, conventional exciter system with an improved ignition lead was also recently tested at altitude conditions. This test program demonstrated the capability of these exciter systems to operate at altitude. While more extensive testing may be required, these systems or similar ones may be used for future NASA and commercial engine programs.

methane↗

Boeing: Arc Jet Exposure of Ablative Non-Oxide CMC TPS for Planetary Probe and Sample Return Applications

NASA Game Changing Development (GCD) provided Boeing support under a Space Act Agreement (SAA) for arc jet sample design, CFD support and arc jet test time of stagnation and shear models for 3 Boeing TPS materials: BLA (Boeing Lightweight Ablator, 18, 21 and 22 densities), BPA (Boeing Phenolic Ablator, standard, graded density, or without reinforcement) and Non-oxide high temperature ceramic composite for structurally integrated TPS (SITPS). Results: For BLA, tested successfully to 500 W/cm² heat flux and heat loads up to 12 kJ/cm² with shear loads up to 370 Pa. The BPA 2017 formulation tested successfully to 1500 W/cm² and 80 kJ/cm², with shear loads up to 250 Pa. For SITIPS, Boeing fabricated C/SiC laminate materials survived testing in shear.

commercial space↗

AERoBOND Project Summary

Under NASA’s Convergent Aeronautics Solutions (CAS) project, the Adhesive-Free Bonding of Complex Composites (AERoBOND) project investigated off-stoichiometric epoxy polymers for fast, reliable assembly of epoxy matrix composite structures. The project goal was to demonstrate feasibility of the AERoBOND joining method by demonstrating mechanical properties greater than 80% of conventional co-cured materials while reducing structure weight by 1%. The project consisted of three convergent research areas: material and process development, systems analysis, and material and process modeling. Material and process development was the largest component of AERoBOND with approximately 6 FTE and 1WYE of support to formulate and characterize new resins, prepare carbon fiber prepregs, fabricate laminates, measure mechanical properties, analyze failure results, and select material and process improvements. The systems analysis activity estimated the potential reduction in part count and aircraft weight by comparing models of composite wing boxes with no fasteners (co-cured structure), fasteners in major joints (co-cured stringers), and fasteners in all joints. The materials and process modeling activity included a molecular model of the AERoBOND materials system to predict mechanical properties of resins with offset stoichiometry and a process model to predict the effect of resin formulation and processing conditions on the extent of mixing and degree of cure in a finished joint. As the number of airline passenger trips doubles in the next 20 years (IATA/Tourism Economics Air Passenger Forecasts, April 2019), the increased demand for new commercial aircraft is now the single greatest technical challenge to the airframe manufacturing industry. To meet efficiency requirements, new aircraft must be fabricated primarily from high performance structural composites, but manufacturing processes are inherently slow with the largest bottleneck attributed to assembly and installation of fasteners (NASA/TM–2019-220428). Manufactures of commercial transport aircraft are compelled to install more than 100,000 redundant fasteners into bonded joints to prevent failures due to unpredictable weak bonds. In structural adhesive bonds, the interface between adherend and adhesive is nearly two-dimensional making it susceptible to minute quantities of contamination, which can cause weak bonds. Currently, bond strength assessment is only possible through destructive testing (i.e., breaking the joint). For these reasons, regulatory organizations such as the Federal Aviation Administration (FAA) often require redundant load paths in secondary-bonded, primary-structures to alleviate concerns with bond performance. The AERoBOND process enables reflow of matrix resin during assembly to eliminate the material discontinuity at the interface, thereby eliminating the dependence of mechanical performance on interfacial adhesion. The AERoBOND joint is equivalent to the interlaminar region obtained during a co-cure process, so joint performance depends on the cohesive properties of the matrix resin. Conventional co-cured structures, although too costly and complex for large-scale manufacturing, are trusted by manufacturers and regulators, and are certified for flight with few or no redundant fasteners.Systems analysis performed on a composite wing model at the scale of a single-aisle commercial transport aircraft indicated that >20,000 redundant fasteners per wing could be eliminated by implementing the AERoBOND joining method. A total weight reduction of 15% was predicted in a wing box by eliminating fasteners and thinning components that must no longer support localized fastener loads and accommodate fastener dimensions. Interlaminar shear fracture toughness measured by the end-notched flexure test was greater than 1 kJ/m2 (nearly 140% of the co-cured benchmark property), which is greatly in excess of the project goals for mechanical properties. Testing was planned to measure interlaminar tensile fracture toughness as well as interlaminar tensile and shear strengths using the same AERoBOND configuration, but was delayed due to closure of LaRC facilities during the COVID-19 pandemic. The AERoBOND process model is partially validated and available for experimental use. It allows the user to input AERoBOND process parameters such as material composition, laminate configuration, and cure cycle to predict the final cure state of the AERoBOND joint. A preliminary, multi-scale material model was developed to predict AERoBOND joint mechanical properties (stiffness and strength) based on the cure state of the joint provided by the process model. The timing for transition of this technology within NASA is excellent as NASA initiates new enduring projects to address composites manufacturing rate challenges. AERoBOND technology is well suited to AAVP/AATT objectives for rapid manufacturing of a composite wing. A minimal effort (1 FTE/$15k procurement/0 WYE) is proposed in FY21 to continue a minor mechanical testing effort and maintain a SAA with ASX composites to develop commercial quality prepreg material. An RFI with the composites industry is suggested to quantify the technology gap between the current TRL and the TRL needed for transition to industry. A moderate effort [3-4 FTE/$150k/1 WYE (~$115k)] is proposed in FY22 for the “high rate composites manufacturing” project currently in planning. The partnership with ASX Composites will be expanded to produce material for sub-element/element-scale “panel-off” activities. Industry partnerships with airframe manufacturers is an expected component to explore damage tolerance and environmental stability. Further development of multi-scale modeling tools (process model, meso-scale model, and molecular model) is planned to enhance and deliver tools for rapid manufacturing infusion.

Frank Louis Palmieri↗

Vulcan Reuse

This is an exciting time in the space launch market. We have providers developing various reuse concepts to help drive continued cost reductions in access to space. At the same time visions of a future marketplace in space are emerging that have energized the community to move toward economically viable space-based ventures. This paper explores the intersection of these two developments. Specifically, we focus on the underlying technologies developed for ULA’s Sensible, Modular, Autonomous Return Technology (SMART) approach to reuse and the intersection with needs in the cislunar marketplace. ULA has been working with NASA Langley Research Center on maturing their Hypersonic Inflatable Aerodynamic Decelerator (HIAD) technology into the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) technology demonstration mission scheduled to fly with the JPSS-2 Launch in 2022, and have honed in on a 6m diameter HIAD for that application. These efforts, under the NASA Space Act Agreements (SAA), have helped identify elements requiring further development for SMART Reuse, which could also benefit other potential mission infusion opportunities. This has proved to be a very fruitful collaboration as these aspects have evolved. The paper further delves into applications across commercial space and NASA’s Space Exploration mandate, in addition to the reusable launch vehicle applications.

John G Reed↗

Impact of Jason-2/T2L2 Ultra-Stable-Oscillator Frequency Model on DORIS stations coordinates and Earth Orientation Parameters

Doppler Orbitography and Radiopositioning Integrated on Satellite (DORIS)is a tracking technique based on a one-way ground to space Doppler link.For Low Earth Orbit (LEO) satellites, DORIS shows a robust capability interms of data coverage and availability, due to a wide and well-distributedground network, where data are made available by the International DorisService (IDS). However, systematic errors remain in the DORIS data, suchas instabilities of the on-board clock due to radiation encountered in space,which limit the accurate determination of station positions.The DORIS on-board clock frequency stability is degraded by the increased radiation found in the region of the South Atlantic Anomaly (SAA)and has been shown to degrade station position estimation. This paper in-troduces a new model correction to the DORIS data for the frequency ofthe Jason-2 Ultra Stable Oscillator (USO), derived from the Time Transferby Laser Link (T2L2) experiment (Belli and Exertier, 2018). We show thata multi-satellite DORIS solution including this T2L2-corrected data appliedto the frequency modelling for The DORIS data, improves the estimationof station coordinates. We show the tie residuals with respect to collocatedGPS stations are improved by several millimeters. We also demonstratethat the 117-day (Jason-2) draconitic signal in the geophysical parametersis reduced, implying that the origin of this signal is not just solar radiationpressure mis-modeling, but also radiation-induced clock perturbations onthe Jason-2 DORIS Ultra-Stable-Oscillator (USO). Finally we demonstratethrough comparisons with the International Earth Rotations and ReferenceSystems Service (IERS) C04 series for Earth Orientation Parameters (EOP),that the estimation of EOP is improved in both a Jason-2 DORIS-only anda multi-satellite DORIS solution for EOP.

DORIS↗

Mitigation Strategies for the Impact of Low Energy Laser Pulses in CALIOP Calibration and Level 2 Retrievals

Since mid-2016, the frequency of low energy laser pulses emitted by the CALIPSO lidar has been slowly increasing due to pressure losses in the canister housing the laser. While originally confined primarily to the South Atlantic Anomaly (SAA) region, these low energy pulses now occur intermittently around the globe. Low energy pulses can cause calibration biases and degrade the science quality of level 2 retrievals. We describe a new low energy mitigation (LEM) algorithm that will be implemented incrementally in future versions of the CALIOP data processing to identify and reject affected profiles during calibration and feature detection. The LEM algorithm effectively eliminates low energy calibration biases, improves level 2 retrievals, and minimizes level 2 data loss.

Jason Tackett↗

Shields-1 Energetic Proton Dose Comparison from Solar Minimum and Active Periods

Shields-1 has been operating in polar low earth orbit since December 2018 as part of the CubeSat Launch Initiative (CSLI) Educational Launch of Nanosatellites (ELaNa)XIX Mission. Shields-1 has 8 Teledyne µdosimeters behind shielding. These shielded µdosimeters have high minimum proton energy thresholds. The Shields-1 electronics enclosure µdosimeter has a minimum proton threshold energy of 151 MeV. The annualized total ionizing dose (TID) in the electronics enclosure was 75.6 +/- 3.2 RAD from July-August 2019, which was a solar minimum period. In contrast, the annualized TID was 61.0 +/- 2.5 RAD in July 2023, a solar active month. The TID change can be attributed to both the reduction in radiation at the South Atlantic Anomaly (SAA) and the decrease in galactic cosmic radiation during increasing solar activity. The measured GCR dose over the poles was reduced during the July 2023 solar active period in comparison with the July 2019 solar minimum period, using the most sensitive µdosimeter channel for the measurement. Shields-1 has demonstrated the capability of measuring the changes in high energy protons in polar low earth orbit during changes in solar activity, which contributes to the understanding of Earth in the heliosphere.

Shields-1 Dosimetry Space Sciences↗

Real-time Ridesharing for Transportation Hubs with Demand and Supply Uncertainty

Transportation hubs in major cities generate a significant amount of trips by taxis and for-hail vehicles (FHV), with many of the trips sharing similar destinations. This suggests promising opportunities to leverage the collective travel needs with dedicated ridesharing solutions to reduce the externalities of excessive traffic at transportation hubs. In this study, we develop a novel dynamic ridesharing approach to serve trips from the transportation hub by considering (1) demand (new passengers) and supply (newly available vehicles) in the near future and (2) the uncertainty of future predictions. Our approach consists of two stages. In the first stage, we develop a data structure called hub mobility tree to generate potential combinations of shareable trips as candidate schedules efficiently. Then the generated schedules are used in the second stage to formulate the stochastic hub-based ridesharing problem (SHRP), which is a stochastic integer programming problem with the objective to maximize the total expected ridesharing profit over time. Due to the prohibitive number of shareable trips, we then approximately solve SHRP by the sample average approximate method (SAA), and a dual Lagrangian technique is implemented to further improve the scalability of the solution approach. We demonstrate the performances of the proposed method by simulating the ridesharing service at JFK airport using NYC taxi and FHV data. The results indicate that the proposed method outperforms the myopic ridesharing (maximize profit for a single time step) and the rolling horizon method with point estimation of future demand and supply.

dynamic ridesharing↗

Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing

Abstract We study the performance of a cloud-based GPU-accelerated inference server to speed up event reconstruction in neutrino data batch jobs. Using detector data from the ProtoDUNE experiment and employing the standard DUNE grid job submission tools, we attempt to reprocess the data by running several thousand concurrent grid jobs, a rate we expect to be typical of current and future neutrino physics experiments. We process most of the dataset with the GPU version of our processing algorithm and the remainder with the CPU version for timing comparisons. We find that a 100-GPU cloud-based server is able to easily meet the processing demand, and that using the GPU version of the event processing algorithm is two times faster than processing these data with the CPU version when comparing to the newest CPUs in our sample. The amount of data transferred to the inference server during the GPU runs can overwhelm even the highest-bandwidth network switches, however, unless care is taken to observe network facility limits or otherwise distribute the jobs to multiple sites. We discuss the lessons learned from this processing campaign and several avenues for future improvements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗