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DOE OSTI2014

Design and expression of a short peptide as an HIV detection probe

Highlights: •We designed a short fusion peptide (FP-50) for in vivo expression. •This peptide is a very promising component for detection of gp120 protein. •The detectable level is about 20–200 times lower than previously published methods. •It is a novel probe to detect HIV-1 gp120 during early stages of HIV infection. -- Abstract: To explore a low-cost novel probe for HIV detection, we designed and prepared a 50-amino acid-length short fusion peptide (FP-50) via Escherichia coli in vivo expression. It was employed as a novel probe to detect HIV-1 gp120 protein. The detectable level of gp120 protein using the FP-50 peptide was approximately 20–200 times lower than previously published methods that used a pair of monoclonal antibodies. Thus, this short peptide is a very promising component for detection of gp120 protein during early stages of HIV infection.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

In situ multi-tier auto-ignition detection applied to dual-fuel combustion simulations

Here we use an anomaly detection methodology that is centered on analyzing fourth-order joint moments (co-kurtosis), particularly focusing on its application in auto-ignition of combustion problems with large numbers of species. Unsupervised anomaly detection is challenging to generalize across problem types and domains. A recent technique, centered on analyzing information in the fourth-order joint moment co-kurtosis, has shown promise, especially for high-dimensional scientific data. In this work we present developments to the co-kurtosis based anomaly detection method needed to make it effective and scalable for large-scale distributed scientific data, such as those generated by massively parallel simulations. An in situ co-kurtosis algorithm is employed as the anomaly detection method for identifying ignition kernels in simulations of turbulent combustion. Here, we extend an existing methodology which identifies regions of the domain where anomalies are present, and add another tier of anomaly detection where the individual samples contributing to the anomaly are identified. We apply this algorithm on-the-fly to a variety of turbulent reacting flow problems and compare it to the widely used (but significantly more expensive) chemical explosive mode analysis (CEMA). We demonstrate the ability of the method to detect and identify the onset of low and high temperature ignition which can be used for computational steering, as chemical and combustion anomalies occur intermittently at spatio-temporal locations unknown a priori. Finally, we apply our lightweight in situ algorithm to an exascale high-fidelity simulation with a total of 2.4 Trillion degrees of freedom, performed using an adaptive mesh refinement solver. Furthermore, through a scalability analysis, we show that the relative computational cost of this in-situ anomaly detection algorithm compared to an iteration of the reacting flow solver is negligible.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Examining the potential for detecting simultaneous noble gas and aerosol samples in the international monitoring system radionuclide network

The purpose of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) is to establish a legally binding ban on nuclear weapon test explosions or any other nuclear explosions. The Preparatory Commission for the CTBT Organization (CTBTO PrepCom) is developing the International Monitoring System (IMS) that includes a global network of 80 stations to monitor for airborne radionuclides upon entry into force of the CTBT. All 80 radionuclide stations will monitor for particulate radionuclides and at least half of the stations will monitor for radioxenon. The airborne radionuclide monitoring is an important verification technology both for the detection of a radionuclide release and in the determination of whether the release event originates from a nuclear explosion as opposed to an industrial use of nuclear materials. Nuclear power plants and many medical isotope production facilities release radioxenon into the atmosphere. Low levels of a few particulate isotopes, such as iodine, may also be released. Detections of multiple isotopes are useful for screening the radionuclide samples for relevance to the Treaty. This paper examines the anticipated joint detections in the IMS of noble gas and particulate isotopes from underground nuclear explosions where breaches in the underground containment vents from low levels to up to 1% of the radionuclide inventory of the resulting fission products to the atmosphere. Detection probabilities are based on 844 simulated release events spaced out at 17 release locations and one year in time. Six different release (venting) scenarios, including two fractionated scenarios, were analyzed. When ranked by detection probability, 11 particulate isotopes and one noble gas isotope ( 133 Xe) appear in the top 20 isotopes for all six release scenarios. Using the 11 particulate isotopes and the one noble gas isotope, the IMS has nearly the same detection probability as when 45 particulate and 4 noble gas isotopes are used. Thus, a limited list of relevant radionuclides may be sufficient for treaty verification purposes. The probability that at least one particulate and at least one radioxenon isotope would be detected in the IMS from the release events ranged from 0.15 to 0.86 depending on the release scenario.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2022

High-fidelity photoneutron detection via neutron activation analysis

To interdict illicit radioactive sources and prevent nuclear terror, governments have deployed portal monitor systems at ports of entry. Such portal monitors rely upon the detection of spontaneously-emitted radiation signatures, however, detection scenarios become more challenging for highly enriched uranium, which emits relatively few spontaneous radiation signatures. Photon active interrogation techniques can augment current cargo inspection scenarios and improve detection capabilities for illicit nuclear material. A high-energy photon interrogation source can induce photofission in nuclear material, producing strong radiation signatures for detection. Prompt fission signals are of specific interest because prompt neutrons are greater than 99% of the fission signal. When using detectors capable of spectroscopy, e.g., pulse shape discrimination-capable organic scintillators, the intense interrogating source often will cause pulse pile-up, degrading particle classification. In this work, we demonstrate photoneutron detection via neutron activation of aluminum and iron. The experiments rely upon nuclear reactions that can only be induced by neutrons, and are robust against pile-up, thereby providing high-confidence neutron rates. In this work, we apply neutron activation analysis for the detection of high-energy neutrons produced by high-energy photon irradiation; the depleted uranium sample was irradiated with a 9-MeV bremsstrahlung beam. We find that the irradiated depleted uranium produced an aluminum activation flux of 1.77 × 10 5 n cm –2 s –1 and an iron-56 activation flux of 1.05 × 10 5 n cm –2 s –1 . Furthermore, the ability to detect radioactivity induced by neutrons created in (, n) and photofission reactions demonstrates a new approach for photon active interrogation to identify nuclear materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Probabilistic limit of detection for ricin identification using a shotgun proteomics assay

Robust and highly specific methods for the detection of the protein toxin ricin are of interest to the law enforcement community. In previous studies, methods based on liquid chromatography-tandem mass spectrometry shotgun proteomics have been proposed. The successful implementation of this approach relies on specific data evaluation criteria addressing (1) the quality of the mass spectrometric data, (2) the confidence of peptide identifications (peptide-spectrum matches), and (3) the number and sequence specificity of peptides detected. We present such data evaluation criteria, and use a novel approach to establish the limit of detection for this ricin assay. Specifically, we use logistic regression to determine the probability of detection for individual ricin peptides at different concentrations. We then apply basic rules from probability theory, combining these individual peptide probabilities into an overall assay limit of detection. This procedure yields an assay limit of detection for ricin at 42.5 ng on column or 21.25 ng/µL for a 2-µL injection. We also show that, in spite of the conventional wisdom that detergents are deleterious to mass spectrometric analyses, the presence of Tween-20 did not prevent detection of ricin peptides, and indeed assays performed in buffers that included Tween-20 gave better results than assays performed using other buffer formulations with or without detergent removal.

Heller, Natalie C.↗

DOE OSTI2017

Detection and Quantification of Biologically Active Botulinum Neurotoxin Serotypes A and B Using a Förster Resonance Energy Transfer-Based Quantum Dot Nanobiosensor

Botulinum neurotoxin (BoNT) is the most potent toxin known. The ingestion of food contaminated with biologically active BoNT causes foodborne botulism, which can lead to respiratory paralysis, coma, and death after ingestion of as little as 70 mu g for a 70 kg human. Because of its lethality and challenges associated with current detection methods, there is an urgent need for highly sensitive rapid screening techniques capable of detecting biologically active BoNT. Here, we describe a Forster resonance energy transfer-based nanobiosensor that uses quantum dots (QDs) and two specific quencher-labeled peptide probes to detect and differentiate two biologically active forms of BoNT, serotypes A and B, which were responsible for 80% of human foodborne botulism cases in the U.S. from 2012 to 2015. Each peptide probe contains an enzymatic cleavage site specific to only one serotype. QDs were selected based on the spectral overlap with the quenchers. In the presence of the target BoNT serotype, the peptide probe is cleaved and the quenching of QD photoluminescence (PL) is reduced, giving a signal that is easily detected by a PL spectrophotometer. This sensor performance was evaluated with light chains of BoNT/A and BoNT/B (LcA and LcB), catalytic domains of the respective serotypes. LcA and LcB were detected in 3 h with limits of detection of 0.2 and 2 ng/mL, respectively. The specificity of the sensor was evaluated, and no cross-reactivity from nontarget serotypes was observed with 2 h of incubation. Because each serotype-specific peptide is conjugated to a QD with a unique emission wavelength, multiple biologically active BoNT serotypes could be detected in one PL spectrum. The sensor was also shown to be responsive to BoNT/A and BoNT/B holotoxins. Good performance of this sensor implies its potential application as a rapid screening method for biologically active BoNT/A and BoNT/B in the laboratory and in the field.

botulinum neurotoxin↗

DOE OSTI2018

Laser-Induced Carbon-Based Smart Flexible Sensor Array for Multiflavors Detection

We report a flexible sensor array electronic tongue system that is fabricated on a polymer substrate by the laser direct writing process for multiflavor detection. Electronic tongue is a sensing system that is applied to detect different elements with the same sensor array. By analyzing responses from different measurement units, it enables a cross-sensitivity, namely, the ability of the system to responding to a range of different analytes in solution without specific functionalization of sensors. In this article, a six-unit sensing array system was fabricated by a laser direct writing process. Sensing units were introduced on a flexible polyamide surface. A high surface–volume ratio porous carbon structure was created by a laser-induced carbonization process, which provides stable conductive carbon electrodes with high sensitivity. Different surface treatments, such as gold plating, reduced-graphene oxide coating, and polyaniline coating, were accomplished for different measurement units. By applying principal component analysis, this sensing system shows a promising result for the detection of multiple flavors. The detection limit for each element is about 0.1 mM for NaCl and sugar solutions. Also, it is able to detect 10 –4 times diluted commercial table vinegar solution, which originally contains 5% acetic acid. The detection limit is theoretically lower than the human threshold of 10 mM for NaCl and sugar. Besides, the sensing system shows a high sensitivity and selectivity for mixed elements. Here, by mapping the data points, the sensor system could detect flavor combinations and provide a reliable prediction of analyte concentration ratios.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Determination of X-ray detection limit and applications in perovskite X-ray detectors

X-ray detection limit and sensitivity are important figure of merits for perovskite X-ray detectors, but literatures lack a valid mathematic expression for determining the lower limit of detection for a perovskite X-ray detector. In this work, we present a thorough analysis and new method for X-ray detection limit determination based on a statistical model that correlates the dark current and the X-ray induced photocurrent with the detection limit. The detection limit can be calculated through the measurement of dark current and sensitivity with an easy-to-follow practice. Alternatively, the detection limit may also be obtained by the measurement of dark current and photocurrent when repeatedly lowering the X-ray dose rate. While the material quality is critical, we show that the device architecture and working mode also have a significant influence on the sensitivity and the detection limit. Our work establishes a fair comparison metrics for material and detector development.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Light-powered end-to-end neutron detection and imaging with an edge-deployed optical AI chip

Neutron detection is widely used in many applications including nuclear physics, nuclear energy, nuclear technologies and nuclear safeguards. Developing an end-to-end neutron detection and imaging workflow paves way towards fully automated processes for many applications. We implemented an automated workflow for neutron detection experiments which use a solid state image sensor to capture neutron hits as a digital image. We deploy the workflow to an edge-based optical neural network (ONN) to increase the radiation-hardness and lifetime of neutron detection instruments. We present a two-stage neural network framework for detection of neutrons at sub-pixel resolution. The first stage uses a region proposal network to efficiently detect and extract neutron hits from the input camera image. The second stage feeds the extracted hits into a fully connected neural network to predict the sub-pixel hit position. The performance of the two-stage framework is evaluated using the edge-based ONN. The results show that we can achieve above 96% neutron detection accuracy as well as sub-pixel and sub-micron position resolution, while enjoying the advantages of the ONN hardware including radiation-hardness, low energy consumption and high computing speed for integrated edge camera and hardware deployment, when compared with electronic counterparts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

Electrochemical detection of leukemia oncogenes using enzyme-loaded carbon nanotube labels

Here we describe an ultrasensitive electrochemical nucleic acids assay amplified by carbon nanotubes (CNTs)-based labels for the detection of human acute lymphocytic leukemia (ALL) related p185 BCR-ABL fusion transcript. The carboxylated CNTs were functionalized with horseradish peroxidase (HRP) molecules and target-specific detection probes (DP) via diimide-activated amidation, and used to label and amplify target hybridization signal. The activity of captured HRP was monitored by square-wave voltammetry measuring the electroactive enzymatic product in the presence of 2-aminophenol and hydrogen peroxide substrate solution. The effect of DP and HRP loading of the CNT-based labels on its signal-to-noise ratio of electrochemical detection was studied systematically for the first time. Under optimized conditions, the signal-amplified assay achieved a detection limit of 83 fM targets oligonuecleotides and a 4-order wide dynamic range of target concentration. The resulting assay allowed a robust discrimination between the perfect match and a three-base mismatch sequence. When subjected to full-length (491 bp) DNA oncogene, the approach demonstrated a detection limit of approximately 33 pg of the target gene. The high sensitivity and specificity of assay enabled PCR-free detection of target transcripts in as little as 65 ng of mRNA extracted from positive ALL cell lines SUP-B15, in comparison to those obtained from negative cell lines HL-60. The approach holds promise for simple, low cost and ultrasensitive electrochemical nucleic acids detection in portable devices, point-of-care and early disease diagnostic applications.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2022

Boron nitride neutron detector with the ability for detecting both thermal and fast neutrons

The detection of fast neutrons is regarded technically challenging because the interaction probability of fast neutron with matter is extremely low. Based on our recent development of hexagonal boron nitride (BN) semiconductor thermal neutron detectors with a record high efficiency of 59%, we report here the feasibility studies of BN detectors for detecting fast neutrons. A BN detector with a detection area of 2.1 cm 2 was fabricated from a 90 $μ$m thick BN epilayer. In the presence of a bare Cf-252 source emitting fast neutrons ranging from 1 to 9 MeV, the detection efficiency was estimated to be about 0.1%. Furthermore, the measured mean free path of fast neutron in BN is about 7.6 cm. Together with the capability of BN for thermal neutron detection, the present results indicate that by incorporating BN with a large thickness, BN neutron detectors are expected to possess the unique capability of directly detecting thermal to fast neutrons as well as outstanding features resulting from the ultrawide bandgap of BN. The identification of a single material that is sensitive to both thermal and fast neutrons is valuable for the development of novel neutron detection technologies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Systematic Source Determination and X-Ray Radiography Detection of Nonuniformities on High-Density Carbon Ablators

Recent deuterium-tritium (D-T)–layered implosion experiments at the National Ignition Facility have achieved a burning plasma and >1-MJ neutron yield. A series of repeat experiments have shown that the degree of performance is very likely dependent on capsule quality, including the quantity of what are collectively termed “high- Z particles.” These particles are detected on a custom-built radiography system, known as the Sagometer, during the final target qualification process. The term particles is misleading, as the source of these nonuniformities in the capsule images is uncertain; the term detection will be used instead. An increased number of D-T targets have been rejected at the final stages of production due to Sagometer detections. Late detections are deleterious in terms of loss of production parts, effort, and overall operating efficiency. In response, we undertook an effort to determine the origin of these detections and to ultimately mitigate target losses caused by them. Through careful testing and analysis, we have determined neither insufficient production cleanliness nor hohlraum shedding is responsible for the detections on the capsule. Here, we determined that the detections are inherent to the capsule and have made efforts to use the Zeiss Xradia to identify them earlier in the production process. While testing revealed the Xradia is not currently sufficient for identifying such particles using radiography images, we continue to look to other forms of metrology to down select the capsules early in the process.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

CORC $^{\circledR}$ cable terminations with integrated Hall arrays for quench detection

ReBCO superconducting cables have the potential to enable compact thermonuclear fusion reactors that operate at magnetic fields exceeding 20 T and allow operation at temperatures far exceeding the boiling point of liquid helium, potentially allowing for demountable magnets. Normal zone detection remains a challenge, and while novel quench detection techniques are an active area of research, few are non-invasive, provide real-time quench detection, and have been demonstrated with current ramp rates relevant for fusion reactors. To address this problem, a CORC$^{\circledR}$ cable termination is developed with integrated Hall sensors to monitor current redistribution as a proxy for quench detection. The methodology exploits the current sharing and layered topology in CORC$^{\circledR}$ cables, and allows quench detection using a localized sensor instead of co-wound voltage wires or optical fibers. Furthermore, experiments are presented where current redistribution is measured from induced quenches, and in a 0.2 meter CORC$^{\circledR}$ sample it is found that the Hall sensors detect normal zone transitions with a similar magnitude and temporal resolution as voltage measurements. To emulate the conditions of dynamic poloidal and central solenoidal fields, experiments are repeated with ramp rates up to 10 kA s -1 that demonstrate the potential to detect normal zone development over a range of experimental parameters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Quench detection using Hall sensors in high-temperature superconducting CORC ® -based cable-in-conduit-conductors for fusion applications

Advanced magnet systems for fusion applications would greatly benefit from the use of high-temperature superconductors (HTS). These materials allow fusion magnets to operate at higher magnetic fields, allowing for more compact fusion machines, and allow for operation at elevated temperatures, enabling demountable coils that provide access for maintenance of the fusion reactor. Quench detection remains a major challenge in the protection of HTS magnets that are vulnerable to localized conductor burnout due to their low quench propagation velocities. One of the methods explored is the use of Hall sensors that are incorporated in or near the magnet terminations that can detect local field variations that occur as a result of current redistribution within the conductor to bypass a hotspot within the magnet winding. This method is potentially well suited for Cable in Conduit Conductors, such as those made from Conductor on Round Core (CORC) cables, in which sub-cables containing HTS tapes are connected to the terminations at a low resistance. Here, to demonstrate the technique, a CORC ® triplet consisting of three sub-cables, rated for 4 kA operation at 77 K, was manufactured and Hall sensors were used to measure local field variations next to the terminations due to current redistribution between the cables. The Hall response was compared to voltages that developed over the cables and terminations as a local hotspot was applied to different cables in the triplet. It was found that the Hall sensors were faster and more sensitive than voltage contact measurements and were able to reliably detect current redistribution of only a few amperes caused by a hotspot, well before the triplet exceeded its critical current. The method also allowed the detection of heater-induced hotspots during high ramp rates of 2 kA s<:sup>–1 relevant for fusion applications. Hall sensors have a distinct benefit of being less sensitive to inductive pickup of AC interference compared to voltage contact measurements that make quench detection through voltage measurements in magnets especially challenging. The method can also be used for diagnostic measurements of current redistribution caused by other sources such as inhomogeneous current injection from faulty joints, or localized conductor damage. The Hall sensors are likely capable of detecting the onset of a quench that may occur a far distance away from the sensor location, presenting a breakthrough in HTS quench detection that potentially removes one of the remaining barriers to reliable operation of large HTS magnet systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Confident detection of doubly ionized thorium in the extreme Ap star CPD-62° 2717

Despite the Universe containing primordial thorium (Th) of sufficient abundance to appear in stellar spectra, detection of Th has to date been tentative and based on just a few weak and blended lines. Here, we present convincing evidence not only for the first Th detection in a magnetic chemically peculiar Ap star but also for the first detection of Th iii in a stellar spectrum. CPD-62° 2717 was initially recognized as a highly magnetized Ap star due to resolved magnetically split lines captured in H-band spectra from the SDSS/APOGEE survey. The star was subsequently pinpointed as extraordinarily peculiar when careful inspection of the H-band line content revealed the presence of five lines of Th iii, none of which are detected in the other ∼1500 APOGEE-observed Ap stars. Follow-up with the VLT + UVES confirmed a similarly peculiar optical spectrum featuring dozens of Th iii lines, among other peculiarities. Unlike past claims of Th detection, and owing to high-resolution observations of the strong (∼8–12 kG) magnetic field of CPD-62° 2717, the detection of Th iii can in this case be supported by matches between the observed and theoretical magnetic splitting patterns. Comparison of CPD-62° 2717 to stars for which Th overabundances have been previously reported (e.g. Przybylski’s Star) indicates that only for CPD-62° 2717 is the Th detection certain. Along with the focus on Th iii, we use time series measurements of the magnetic field modulus to constrain the rotation period of CPD-62° 2717 to ∼4.8 yr, thus establishing it as a new example of a superslowly rotating Ap star.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Quantitative evaluation of an air-monitoring network using atmospheric transport modeling and frequency of detection methods

A methodology to quantify the performance of an air monitoring network in terms of frequency of detection has been developed. The methodology utilizes an atmospheric transport model to predict air concentrations of radionuclides at the samplers for a given release time and duration. Frequency of detection is defined as the fraction of “events” that result in a detection at either a single sampler or network of samplers. An “event” is defined as a release of finite duration that begins on a given day and hour of the year from a facility with the potential to emit airborne radionuclides. Another metric of interest is the network intensity, which is defined as the fraction of samplers in the network that have a positive detection for a given event. The frequency of detection methodology allows for evaluation of short-term releases that include effects of short-term variability in meteorological conditions. The methodology was tested using the U.S. Department of Energy Idaho National Laboratory (INL) Site ambient air monitoring network consisting of 37 low-volume air samplers in 31 different locations covering a 17,630 km 2 region. Releases from six major INL facilities distributed over an area of 1,435 km 2 were modeled and included three stack sources and eight ground-level sources. A Lagrangian Puff air dispersion model (CALPUFF) was used to model atmospheric transport. The model was validated using historical 125 Sb releases and measurements. Relevant one-week release quantities from each emission source were calculated based on a dose of 1.9 × 10 –4 mSv at a public receptor (0.01 mSv assuming release persists over a year). Important radionuclides considered include 241 Am, 137 Cs, 238 Pu, 239 Pu, 90 Sr, and tritium. Results show the detection frequency is over 97.5% for the entire network considering all sources and radionuclides. Network intensities ranged from 3.75% to 62.7%. Evaluation of individual samplers indicated some samplers were poorly situated and add little to the overall effectiveness of the network. As a result, using the frequency of detection methods, optimum sampler placements were simulated that could substantially improve the performance and efficiency of the network.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Adaptive Anomaly Detection for Dynamic Clinical Event Sequences

Over the past decade, health information technology (IT) has enabled the amount of digital information stored in electronic health records (EHRs) to expand greatly. However, according to some studies, hazards in health IT can lead to changes in clinical decisions, care processes, and care outcomes, as well as other issues. Thus, the effects of health IT hazards on patient safety have been at the forefront of recent patient safety research. Nonetheless, hazard detection in health IT remains a challenge. In this paper, the authors assume that safety-related issues in health IT would exhibit anomalous characteristics in EHR data. Although all hazards will exhibit some anomalous characteristics, not all anomalies can be regarded as hazards. The authors hypothesize that errors in health IT could lead to interruptions in the sequence of clinical actions. To this end, the problem of detecting anomalous sequences in big EHR data is considered. This paper focuses on dynamic event sequences, which are a series of clinical actions in motion. The authors propose an adaptive anomaly detection approach that uses higher-order network representation to detect anomalous sequences. Furthermore, the authors propose a contiguous subsequence anomaly detection approach that identifies abnormal subsequences in the detected anomalous sequences. The proposed approaches are tested by using synthetic and real-world EHR data. The proposed methods outperform existing state of the art anomaly detection techniques. To reduce the computational complexity associated with the operational implementation of the proposed approaches, the Apache Spark environment was leveraged, and a much shorter run time together with improved performance were achieved, especially for data with more than 60,000 sequences.

Niu, Haoran↗

DOE OSTI2023

Signal Processing Based Method for Real-Time Anomaly Detection in High-Performance Computing

Performance anomalies can manifest as irregular execution times or abnormal execution events for many reasons, including network congestion and resource contention. Detecting such anomalies in real-time by analyzing the details of performance traces at scale is impractical due to the sheer volume of data High-Performance Computing (HPC) applications produce. In this paper, we propose formulating HPC performance anomaly detection as a signal-processing problem where anomalies can be treated as noise. We evaluate our proposed method in comparison with two other commonly used anomaly detection techniques of varying complexity based on their detection accuracy and scalability. Since real-time in-situ anomaly detection at a large scale requires lightweight methods that can handle a large volume of streaming data, we find that our proposed method provides the best trade-off. We then implement the proposed method in Chimbuko, the first online, distributed, and scalable workflow-level performance trace analysis framework. We compare our proposed signal-based anomaly detection algorithm with two other methods using a function of their accuracy, F1 score, and detection overhead. Our experiments demonstrate that our proposed approach achieves a 99% improvement for the benchmark datasets and a 93% improvement with Chimbuko traces.

99 GENERAL AND MISCELLANEOUS↗