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At least 73 records · Page 4

TCP Throughput Profiles Using Measurements over Dedicated Connections

Wide-area data transfers in high-performance computing infrastructures are increasingly being carried over dynamically provisioned dedicated network connections that provide high capacities with no competing traffic. We present extensive TCP throughput measurements and time traces over a suite of physical and emulated 10 Gbps connections with 0-366 ms round-trip times (RTTs). Contrary to the general expectation, they show significant statistical and temporal variations, in addition to the overall dependencies on the congestion control mechanism, buffer size, and the number of parallel streams. We analyze several throughput profiles that have highly desirable concave regions wherein the throughput decreases slowly with RTTs, in stark contrast to the convex profiles predicted by various TCP analytical models. We present a generic throughput model that abstracts the ramp-up and sustainment phases of TCP flows, which provides insights into qualitative trends observed in measurements across TCP variants: (i) slow-start followed by well-sustained throughput leads to concave regions; (ii) large buffers and multiple parallel streams expand the concave regions in addition to improving the throughput; and (iii) stable throughput dynamics, indicated by a smoother Poincare map and smaller Lyapunov exponents, lead to wider concave regions. These measurements and analytical results together enable us to select a TCP variant and its parameters for a given connection to achieve high throughput with statistical guarantees.

Rao, Nageswara S.↗

High-throughput mass spectrometry analysis using immediate drop-on-demand technology coupled with an open port sampling interface

Rationale: The sampling throughput of immediate drop-on-demand technology (I.DOT) coupled with an open port sampling interface (OPSI) is limited by software communication. To enable much-needed high-throughput mass spectrometry (MS) analysis capabilities, a novel software was developed that allows for flexible sample selection from a 96-well plate and for maximized analysis throughput using I.DOT/OPSI-MS coupling. Methods: Wells of a 96-well I.DOT plate were filled with propranolol solution and were used to test maximum sampling throughput strategies to minimize analysis time. Demonstration of chemical reaction monitoring was done using acid-catalyzed ring closure of 2,3-diaminonaphthalene (DAN) with nitrite to form 2,3-naphthotriazole (NAT). Analytes were detected in positive electrospray ionization mode using selected reaction monitoring. Results: A maximum throughput of 1.54 s/sample (7.41 min/96-well plate with three technical replicates) was achieved, and it was limited by the peak width of the MS signal resulting in an occasional slight overlap between the peaks. Further, relative standard deviation was 10 ± 1% with all tested sampling strategies. Chemical reaction monitoring of DAN to NAT using nitrite was successfully accomplished with 2 s/sample throughout showing almost complete transformation in 10 min with no signal overlap. Conclusions: This work illustrates the development of a noncontact, automated I.DOT/OPSI-MS system with improved throughput achieved through an optimized software interface. Its achievable analysis time and precision make it a viable approach for drug discovery and in situ reaction monitoring studies.

47 OTHER INSTRUMENTATION↗

A high-throughput fluorescence resonance energy transfer (FRET)-based endothelial cell apoptosis assay and its application for screening vascular disrupting agents

Highlights: Black-Right-Pointing-Pointer An endothelial cell apoptosis assay using FRET-based biosensor was developed. Black-Right-Pointing-Pointer The fluorescence of the cells changed from green to blue during apoptosis. Black-Right-Pointing-Pointer This method was developed into a high-throughput assay in 96-well plates. Black-Right-Pointing-Pointer This assay was applied to screen vascular disrupting agents. -- Abstract: In this study, we developed a high-throughput endothelial cell apoptosis assay using a fluorescence resonance energy transfer (FRET)-based biosensor. After exposure to apoptotic inducer UV-irradiation or anticancer drugs such as paclitaxel, the fluorescence of the cells changed from green to blue. We developed this method into a high-throughput assay in 96-well plates by measuring the emission ratio of yellow fluorescent protein (YFP) to cyan fluorescent protein (CFP) to monitor the activation of a key protease, caspase-3, during apoptosis. The Z Prime factor for this assay was above 0.5 which indicates that this assay is suitable for a high-throughput analysis. Finally, we applied this functional high-throughput assay for screening vascular disrupting agents (VDA) which could induce endothelial cell apoptosis from our in-house compounds library and dioscin was identified as a hit. As this assay allows real time and sensitive detection of cell apoptosis, it will be a useful tool for monitoring endothelial cell apoptosis in living cell situation and for identifying new VDA candidates via a high-throughput screening.

60 APPLIED LIFE SCIENCES↗

Lead discovery for mammalian elongation of long chain fatty acids family 6 using a combination of high-throughput fluorescent-based assay and RapidFire mass spectrometry assay

A high-throughput RapidFire mass spectrometry assay is described for elongation of very long-chain fatty acids family 6 (Elovl6). Elovl6 is a microsomal enzyme that regulates the elongation of C12-16 saturated and monounsaturated fatty acids. Elovl6 may be a new therapeutic target for fat metabolism disorders such as obesity, type 2 diabetes, and nonalcoholic steatohepatitis. To identify new Elovl6 inhibitors, we developed a high-throughput fluorescence screening assay in 1536-well format. However, a number of false positives caused by fluorescent interference have been identified. To pick up the real active compounds among the primary hits from the fluorescence assay, we developed a RapidFire mass spectrometry assay and a conventional radioisotope assay. These assays have the advantage of detecting the main products directly without using fluorescent-labeled substrates. As a result, 276 compounds (30%) of the primary hits (921 compounds) in a fluorescence ultra-high-throughput screening method were identified as common active compounds in these two assays. It is concluded that both methods are very effective to eliminate false positives. Compared with the radioisotope method using an expensive {sup 14}C-labeled substrate, the RapidFire mass spectrometry method using unlabeled substrates is a high-accuracy, high-throughput method. In addition, some of the hit compounds selected from the screening inhibited cellular fatty acid elongation in HEK293 cells expressing Elovl6 transiently. This result suggests that these compounds may be promising lead candidates for therapeutic drugs. Ultra-high-throughput fluorescence screening followed by a RapidFire mass spectrometry assay was a suitable strategy for lead discovery against Elovl6. - Highlights: • A novel assay for elongation of very-long-chain fatty acids 6 (Elovl6) is proposed. • RapidFire mass spectrometry (RF-MS) assay is useful to select real screening hits. • RF-MS assay is proved to be beneficial because of its high-throughput and accuracy. • A combination of fluorescent and RF-MS assays is effective for Elovl6 inhibitors.

60 APPLIED LIFE SCIENCES↗

Caveats and limitations of plate reader-based high-throughput kinetic measurements of intracellular calcium levels

Calcium plays a crucial role in virtually all cellular processes, including neurotransmission. The intracellular Ca{sup 2+} concentration ([Ca{sup 2+}]{sub i}) is therefore an important readout in neurotoxicological and neuropharmacological studies. Consequently, there is an increasing demand for high-throughput measurements of [Ca{sup 2+}]{sub i}, e.g. using multi-well microplate readers, in hazard characterization, human risk assessment and drug development. However, changes in [Ca{sup 2+}]{sub i} are highly dynamic, thereby creating challenges for high-throughput measurements. Nonetheless, several protocols are now available for real-time kinetic measurement of [Ca{sup 2+}]{sub i} in plate reader systems, though the results of such plate reader-based measurements have been questioned. In view of the increasing use of plate reader systems for measurements of [Ca{sup 2+}]{sub i} a careful evaluation of current technologies is warranted. We therefore performed an extensive set of experiments, using two cell lines (PC12 and B35) and two fluorescent calcium-sensitive dyes (Fluo-4 and Fura-2), for comparison of a linear plate reader system with single cell fluorescence microscopy. Our data demonstrate that the use of plate reader systems for high-throughput real-time kinetic measurements of [Ca{sup 2+}]{sub i} is associated with many pitfalls and limitations, including erroneous sustained increases in fluorescence, limited sensitivity and lack of single cell resolution. Additionally, our data demonstrate that probenecid, which is often used to prevent dye leakage, effectively inhibits the depolarization-evoked increase in [Ca{sup 2+}]{sub i}. Overall, the data indicate that the use of current plate reader-based strategies for high-throughput real-time kinetic measurements of [Ca{sup 2+}]{sub i} is associated with caveats and limitations that require further investigation. - Research Highlights: > The use of plate readers for high-throughput screening of intracellular Ca{sup 2+} is associated with many pitfalls and limitations. > Single cell fluorescent microscopy is recommended for measurements of intracellular Ca{sup 2+}. > Dual-wavelength dyes (Fura-2) are preferred over single-wavelength dyes (Fluo-4) for measurements of intracellular Ca{sup 2+}. > Probenecid prevents dye leakage but abolishes depolarization-evoked Ca{sup 2+} influx, severely hampering measurements of Ca{sup 2+}. > In general, care should be taken when interpreting data from high-throughput kinetic measurements.

60 APPLIED LIFE SCIENCES↗

Quantitative analysis of treatment process time and throughput capacity for spot scanning proton therapy

Purpose: To determine the patient throughput and the overall efficiency of the spot scanning system by analyzing treatment time, equipment availability, and maximum daily capacity for the current spot scanning port at Proton Therapy Center Houston and to assess the daily throughput capacity for a hypothetical spot scanning proton therapy center. Methods: At their proton therapy center, the authors have been recording in an electronic medical record system all treatment data, including disease site, number of fields, number of fractions, delivered dose, energy, range, number of spots, and number of layers for every treatment field. The authors analyzed delivery system downtimes that had been recorded for every equipment failure and associated incidents. These data were used to evaluate the patient census, patient distribution as a function of the number of fields and total target volume, and equipment clinical availability. The duration of each treatment session from patient walk-in to patient walk-out of the spot scanning treatment room was measured for 64 patients with head and neck, central nervous system, thoracic, and genitourinary cancers. The authors retrieved data for total target volume and the numbers of layers and spots for all fields from treatment plans for a total of 271 patients (including the above 64 patients). A sensitivity analysis of daily throughput capacity was performed by varying seven parameters in a throughput capacity model. Results: The mean monthly equipment clinical availability for the spot scanning port in April 2012–March 2015 was 98.5%. Approximately 1500 patients had received spot scanning proton therapy as of March 2015. The major disease sites treated in September 2012–August 2014 were the genitourinary system (34%), head and neck (30%), central nervous system (21%), and thorax (14%), with other sites accounting for the remaining 1%. Spot scanning beam delivery time increased with total target volume and accounted for approximately 30%–40% of total treatment time for the total target volumes exceeding 200 cm{sup 3}, which was the case for more than 80% of the patients in this study. When total treatment time was modeled as a function of the number of fields and total target volume, the model overestimated total treatment time by 12% on average, with a standard deviation of 32%. A sensitivity analysis of throughput capacity for a hypothetical four-room spot scanning proton therapy center identified several priority items for improvements in throughput capacity, including operation time, beam delivery time, and patient immobilization and setup time. Conclusions: The spot scanning port at our proton therapy center has operated at a high performance level and has been used to treat a large number of complex cases. Further improvements in efficiency may be feasible in the areas of facility operation, beam delivery, patient immobilization and setup, and optimization of treatment scheduling.

60 APPLIED LIFE SCIENCES↗

Impact of anatomical fractionation of corn stover on hammer mill throughput and energy consumption

The goal of this Case Study was to quantify the impacts of variable moisture and ash on hammer mill throughput and energy consumption and on loss of very wet stover that causes failures in the first stage grinder and that are not able to be fed to conversion, as compared to a status quo Base Case system. Also considered was convertible carbohydrate content (minimum total carbohydrate specification) and maximum ash content and the delivered feedstock cost impacts of not being able to feed stover not meeting the total carbohydrate specification to the conversion reactor. Laboratory data on the impacts of moisture content and tissue fraction on throughput and energy consumption in a stage 2 hammer mill were received from FCIC Subtask 5.1. Additional air classifier throughput, energy consumption and separation efficiency data were obtained from FCIC Subtask 5.1 for the new air classifier, which has three exit streams (lights, middle and heavies). These data were utilized to develop the necessary response surface equations to perform throughput analysis using discrete event simulation. Because the ash contents and particle sizes had not been analyzed in the laboratory at the time of the model runs, we assumed that the ash distributed proportionally with total mass into the lights and heavies in an air classifier having two exit streams (lights and heavies) and that the lights fraction from the air classifier was not removed. Key takeaways from this Case Study are that due to lower energy consumption, it is more cost effective to hammer mill fractionated corn stover tissues than whole stover. Reduction of grinding energy was significant and may possibly be connected to particle-particle interactions in the grinder that lead to increased residence time of leaves and husks, resulting in decreased throughput and higher generation of fines when milling whole stover. While we did not see significant impacts to throughput, this was due to moisture failures of the first stage grinder in each system dominating failures and downtime. The operating cost savings of reduced grinding energy savings in the second stage hammer mills alone was high enough to offset the added capital cost of the air classifier and extra grinding line.

09 BIOMASS FUELS↗

Cross Inference of Throughput Profiles Using Micro Kernel Network Method

Dedicated network connections are being increasingly deployed in cloud, centralized and edge computing and data infrastructures, whose throughput profiles are critical indicators of the underlying data transfer performance. Due to the cost and disruptions to physical infrastructures, network emulators, such as Mininet, are often used to generate measurements needed to estimate throughput profiles, typically expressed as a function of the connection round trip time. The profiles estimated using measurements from such emulated networks are usually inaccurate for high bandwidth and high latency connections, since they do not accurately reflect the critical network transport dynamics mainly due to computing and memory constraints of the host. We present a machine learning (ML) method to estimate the throughput profiles using emulation measurements to closely match the testbed and production network profiles. In particular, we propose a micro Kernel Network (mKN) that provides baseline throughput measurements on the host running Mininet emulations, which are used to learn a regression map that converts them to the corresponding testbed measurement estimates. Once initially learned, this map is applied to measurements from subsequent network emulations on the same host. We present experimental measurements to illustrate this approach, and derive generalization equations for the proposed mKN-ML method. Using a four-site scenario emulation, we show the effectiveness of this method in providing accurate concave throughput profiles from inaccurate convex or non-smooth ones indicated by Mininet emulation.

Rao, Nageswara↗

Optimizing High-Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server

Abstract With machine learning applications now spanning a variety of computational tasks, multi-user shared computing facilities are devoting a rapidly increasing proportion of their resources to such algorithms. Graph neural networks (GNNs), for example, have provided astounding improvements in extracting complex signatures from data and are now widely used in a variety of applications, such as particle jet classification in high energy physics (HEP). However, GNNs also come with an enormous computational penalty that requires the use of GPUs to maintain reasonable throughput. At shared computing facilities, such as those used by physicists at Fermi National Accelerator Laboratory (Fermilab), methodical resource allocation and high throughput at the many-user scale are key to ensuring that resources are being used as efficiently as possible. These facilities, however, primarily provide CPU-only nodes, which proves detrimental to time-to-insight and computational throughput for workflows that include machine learning inference. In this work, we describe how a shared computing facility can use the NVIDIA Triton Inference Server to optimize its resource allocation and computing structure, recovering high throughput while scaling out to multiple users by massively parallelizing their machine learning inference. To demonstrate the effectiveness of this system in a realistic multi-user environment, we use the Fermilab Elastic Analysis Facility augmented with the Triton Inference Server to provide scalable and high-throughput access to a HEP-specific GNN and report on the outcome.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High-throughput platforms for metabolomics

We report that mass spectrometry has become a choice method for broad-spectrum metabolite analysis in both fundamental and applied research. This can range from comprehensive analysis achieved through time-consuming chromatography to the rapid analysis of a few target metabolites without chromatography. In this review article, we highlight current high-throughput MS-based platforms and their potential application in metabolomics. Although current MS platforms can reach throughputs up to 0.5. seconds per sample, the metabolite coverage of these platforms are low compared to low-throughput, separation-based MS methods. High-throughput comes at a cost, as it's a trade-off between sample throughput and metabolite coverage. As we will discuss, promising emerging technologies, including microfluidics and miniaturization of separation techniques, have the potential to achieve both rapid and more comprehensive metabolite analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Throughput Analytics of Cloud Networks

A network of virtual machines at cloud server sites connected over virtual IO connections is a flexible, easily deployable, and cost-effective alternative to a physical network infrastructure with dedicated servers connected over leased fiber lines. We study the throughput performance of such a cloud network by collecting measurements over Google Cloud infrastructure spanning multiple continents. To study its ideal performance and impact of packet losses, we utilize its emulation using dedicated servers and connection hardware emulation devices. We compare the measurements over the cloud network to those over its emulation on a testbed. We examine the throughput profiles of both networks as a function of the round trip time and their utilization-concavity coefficients, estimated using measurements for common TCP versions. The throughput profile's concave-convex shape and its coefficient are critical indicators of the network performance, qualitatively and quantitatively, respectively. The results indicate their overall agreement between the production cloud network and its emulation using dedicated connections, and a near optimal throughput performance of the former except for a few under-performing connections. Also, the number of parallel flows is found to be a dominant factor in optimizing the throughput across various conditions and TCP versions.

Phanekham, Derek↗

Throughput Measurements and Profile Analysis of Cloud Networks

Cloud networks utilize virtual connections to connect virtual machines distributed across cloud sites. They are increasingly deployed due to flexible provisioning using software and cost-effectiveness in not requiring to build physical network infrastructure. However, their extensive virtualization makes it unclear how well the established practices of conventional networks translate to them. Here, we study throughput measurements over a Google Cloud network using a matching hardware emulated conventional network, which provide production and exploratory conditions, respectively. The measurements span connections representing local, cross-continental and around the Earth distances. We study the effects of parallel flows, congestion control algorithms and retransmissions on the network throughput profile expressed as a function of RTT. We compare the throughput profile of Google Cloud network with those of emulated network under various loss conditions, including those too disruptive or expensive in the former. Our analysis based on the concave-convex shape and utilization-concavity coefficients of throughput profiles indicates an overall agreement of performance between the two networks, thereby justifying the use of conventional network emulations to analyze cloud networks. In terms of practical use, our study establishes that BBR and BBRv2 alpha TCP achieve higher throughput compared to loss-based congestion control algorithms under most network configurations, especially, under losses at large RTT.

Phanekham, Derek [Southern Methodist Univ., Dallas↗

Senescence chips for ultrahigh-throughput isolation and removal of senescent cells

Cellular senescence plays an important role in organismal aging and age-related diseases. However, it is challenging to isolate low numbers of senescent cells from small volumes of biofluids for downstream analysis. Furthermore, there is no technology that could selectively remove senescent cells in a high-throughput manner. In this work, we developed a novel microfluidic chip platform, termed senescence chip, for ultrahigh-throughput isolation and removal of senescent cells. The core component of our senescence chip is a slanted and tunable 3D micropillar array with a variety of shutters in the vertical direction for rapid cell sieving, taking advantage of the characteristic cell size increase during cellular senescence. The 3D configuration achieves high throughput, high recovery rate, and device robustness with minimum clogging. We demonstrated proof-of-principle applications in isolation and enumeration of senescent mesenchymal stem cells (MSCs) from undiluted human whole blood, and senescent cells from mouse bone marrow after total body irradiation, with the single cell resolution. After scale-up to a multilayer and multichannel structure, our senescence chip achieved ultrahigh-throughput removal of senescent cells from human whole blood with an efficiency of over 70% at a flow rate of 300 ml/hr. Sensitivity and specificity of our senescence chips could be augmented with implementation of multiscale size separation, and identification of background white blood cells using their cell surface markers such as CD45. With the advantages of high throughput, robustness, and simplicity, our senescence chips may find wide applications and contribute to diagnosis and therapeutic targeting of cellular senescence.

59 BASIC BIOLOGICAL SCIENCES↗

Nile Red Detection of Bacterial Hydrocarbons and Ketones in a High-Throughput Format

A method for use in high-throughput screening of bacteria for the production of long-chain hydrocarbons and ketones by monitoring fluorescent light emission in the presence of Nile red is described. Nile red has previously been used to screen for polyhydroxybutyrate (PHB) and fatty acid esters, but this is the first report of screening for recombinant bacteria making hydrocarbons or ketones. The microtiter plate assay was evaluated using wild-type and recombinant strains of Shewanella oneidensis and Escherichia coli expressing the enzyme OleA, previously shown to initiate hydrocarbon biosynthesis. The strains expressing exogenous Stenotrophomonas maltophilia oleA, with increased levels of ketone production as determined by gas chromatography-mass spectrometry, were distinguished with Nile red fluorescence. Confocal microscopy images of S. oneidensis oleA-expressing strains stained with Nile red were consistent with a membrane localization of the ketones. This differed from Nile red staining of bacterial PHB or algal lipid droplets that showed intracellular inclusion bodies. These results demonstrated the applicability of Nile red in a high-throughput technique for the detection of bacterial hydrocarbons and ketones. IMPORTANCE In recent years, there has been renewed interest in advanced biofuel sources such as bacterial hydrocarbon production. Previous studies used solvent extraction of bacterial cultures followed by gas chromatography-mass spectrometry (GC-MS) to detect and quantify ketones and hydrocarbons (Beller HR, Goh EB, Keasling JD, Appl. Environ. Microbiol. 76: 1212-1223, 2010; Sukovich DJ, Seffernick JL, Richman JE, Gralnick JA, Wackett LP, Appl. Environ. Microbiol. 76: 3850-3862, 2010). While these analyses are powerful and accurate, their labor-intensive nature makes them intractable to high-throughput screening; therefore, methods for rapid identification of bacterial strains that are overproducing hydrocarbons are needed. The use of high-throughput evaluation of bacterial and algal hydrophobic molecule production via Nile red fluorescence from lipids and esters was extended in this study to include hydrocarbons and ketones. This work demonstrated accurate, high-throughput detection of high-level bacterial long-chain ketone and hydrocarbon production by screening for increased fluorescence of the hydrophobic dye Nile red.

Pinzon, NM↗

Throughput comparison of microscope objectives and custom lenses for laser diode output beam collimation

The efficiency with which microscope objectives and custom lenses collimate laser diode emission was measured. Four microscope objectives of 10, 21, 45, and 60 power and two custom lenses of 1 and 0.8 power were used. An autocollimator system was used to measure throughput. It consisted of 1 m focal length lens, a 10 power microscope objective, and a 128-element G series Reticon linear array. Collimating throughput efficiency was defined as the ratio of measured collimated power to total laser output power. Two throughput efficiencies were obtained: one for the didoe operation below lasing and the other for the diode operation above lasing. The custom lenses had higher throughput efficiencies than the microscope objectives. The f/0.8 system provided better throughput efficiencies than the f/1.0 system.

Fuhr, P. L.↗

NASA's Evolutionary Xenon Thruster (NEXT) Project Qualification Propellant Throughput Milestone: Performance, Erosion, and Thruster Service Life Prediction After 450 kg

The NASA s Evolutionary Xenon Thruster (NEXT) program is tasked with significantly improving and extending the capabilities of current state-of-the-art NSTAR thruster. The service life capability of the NEXT ion thruster is being assessed by thruster wear test and life-modeling of critical thruster components, such as the ion optics and cathodes. The NEXT Long-Duration Test (LDT) was initiated to validate and qualify the NEXT thruster propellant throughput capability. The NEXT thruster completed the primary goal of the LDT; namely to demonstrate the project qualification throughput of 450 kg by the end of calendar year 2009. The NEXT LDT has demonstrated 28,500 hr of operation and processed 466 kg of xenon throughput--more than double the throughput demonstrated by the NSTAR flight-spare. Thruster performance changes have been consistent with a priori predictions. Thruster erosion has been minimal and consistent with the thruster service life assessment, which predicts the first failure mode at greater than 750 kg throughput. The life-limiting failure mode for NEXT is predicted to be loss of structural integrity of the accelerator grid due to erosion by charge-exchange ions.

Herman, Daniel A.↗

Space Link Extension Protocol Emulation for High-Throughput, High-Latency Network Connections

New space missions require higher data rates and new protocols to meet these requirements. These high data rate space communication links push the limitations of not only the space communication links, but of the ground communication networks and protocols which forward user data to remote ground stations (GS) for transmission. The Consultative Committee for Space Data Systems, (CCSDS) Space Link Extension (SLE) standard protocol is one protocol that has been proposed for use by the NASA Space Network (SN) Ground Segment Sustainment (SGSS) program. New protocol implementations must be carefully tested to ensure that they provide the required functionality, especially because of the remote nature of spacecraft. The SLE protocol standard has been tested in the NASA Glenn Research Center's SCENIC Emulation Lab in order to observe its operation under realistic network delay conditions. More specifically, the delay between then NASA Integrated Services Network (NISN) and spacecraft has been emulated. The round trip time (RTT) delay for the continental NISN network has been shown to be up to 120ms; as such the SLE protocol was tested with network delays ranging from 0ms to 200ms. Both a base network condition and an SLE connection were tested with these RTT delays, and the reaction of both network tests to the delay conditions were recorded. Throughput for both of these links was set at 1.2Gbps. The results will show that, in the presence of realistic network delay, the SLE link throughput is significantly reduced while the base network throughput however remained at the 1.2Gbps specification. The decrease in SLE throughput has been attributed to the implementation's use of blocking calls. The decrease in throughput is not acceptable for high data rate links, as the link requires constant data a flow in order for spacecraft and ground radios to stay synchronized, unless significant data is queued a the ground station. In cases where queuing the data is not an option, such as during real time transmissions, the SLE implementation cannot support high data rate communication.

Computer Networking↗

High-throughput simulations for insight into grain boundary structure-property relationships and other complex microstructural phenomena

High-throughput simulations can be a powerful tool in the discovery of new materials and behaviors. As part of a special issue on Rising Stars in Computational Materials Science, this paper uses the work of the author to show how high-throughput simulations have had an impact in grain boundary structure-property relationships and other complex microstructural phenomena. The work demonstrates how new tools designed to analyze large datasets produced by high-throughput simulations are enabling comprehensive grain boundary structure-property relationships to be obtained. High-throughput simulations are also used to demonstrate the impact descriptive and inferential statistics has had in extracting key aspects of deformation in metallic glasses. Finally, several different examples are used to show a balanced approach between simulations designed to survey and simulations designed for detailed analysis. Together, the two approaches provide a comprehensive picture of the variety of behaviors that exist, while ensuring that the physics underlying the behaviors are thoroughly understood.

36 MATERIALS SCIENCE↗