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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Analyzing a Five-Year Failure Record of a Leadership-Class Supercomputer

Extreme-scale computing systems are required to solve some of the grand challenges in science and technology. From astrophysics to molecular biology, supercomputers are an essential tool to accelerate scientific discovery. However, large computing systems are prone to failures due to their complexity. It is crucial to develop an understanding of how these systems fail to design reliable supercomputing platforms for the future. This paper examines a five-year failure and workload record of a leadership-class supercomputer. To the best of our knowledge, five years represents the vast majority of the lifespan of a supercomputer. This is the first time such analysis is performed on a top 10 modern supercomputer. We performed a failure categorization and found out that: i) most errors are GPU-related, with roughly 37% of them being double-bit errors on the cards; ii) failures are not evenly spread across the physical machine, with room temperature presumably playing a major role; and iii) software errors of the system bring down several nodes concurrently. Our failure rate analysis unveils that: i) the system consistently degrades, being at least twice as reliable at the beginning, compared to the end of the period; ii) Weibull distribution closely fits the mean-time-between-failure data; and iii) hardware and software errors show a markedly different pattern. Finally, we correlated failure and workload records to reveal that: i) failure and workload records are weakly correlated, except for certain types of failures when segmented by the hours of the day; ii) several categories of failures make jobs crash within the first minutes of execution; and iii) a significant fraction of failed jobs exhaust the requested time with a disregard of when the failure occurred during execution.

Rojas, Elvis↗
DOE OSTI2024

An Evaluation of the Effect of Network Cost Optimization for Leadership Class Supercomputers

Dragonfly-based networks are an extensively deployed network topology in large-scale high-performance computing due to their cost-effectiveness and efficiency. The US will soon have three Exascale supercomputers for leadership class workloads deployed using dragonfly networks. Compared to indirect networks of similar scale, the dragonfly network has considerably reduced cable lengths, cable counts, and switch counts, resulting in significant network cost savings for a given system size, however, these cost reductions result in reduced global minimal paths and more challenging routing. Additionally, large scale dragonfly networks often require a taper at the global link level, resulting in less bisection bandwidth than is achievable in other traditional non-blocking topologies of equivalent scale. While dragonfly networks have been extensively studied, they have yet to be fully evaluated in an extreme scale (i.e., exascale) system that targets capability workloads. In this paper, we present the results of the first large scale evaluation of a dragonfly network on an exascale system (Frontier) and compare its behavior to a similar scale fat-tree network on a previous generation TOP500 system (Summit). This evaluation aims to determine the effect of network cost optimizations by measuring a tapered topology’s impact on capability workloads. Our evaluation is based on a collection of synthetic microbenchmarks, mini-apps, and full scale applications. It compares the scaling efficiencies of each benchmark between the dragonfly-based Frontier and the fat-tree-based Summit systems. Our results show that a dragonfly network is $\sim \mathbf{3 0 \%}$ more cost efficient than a fat-tree topology, which amortizes to $\sim 3 \%$ of an exascale system cost. Furthermore, while tapered dragonfly networks impose significant tradeoffs, the impacts are not as broad as initially thought and are mostly seen in applications with global communication patterns, particularly all-to-all (e.g., FFT-based algorithms), but also local communication patterns (e.g., nearest-neighbor algorithms) that are sensitive to network performance variability.

Khan, Awais↗
DOE OSTI2016

Output Feedback Stabilization for a Class of Multi-Variable Bilinear Stochastic Systems with Stochastic Coupling Attenuation

In this paper, stochastic coupling attenuation is investigated for a class of multi-variable bilinear stochastic systems and a novel output feedback m-block backstepping controller with linear estimator is designed, where gradient descent optimization is used to tune the design parameters of the controller. It has been shown that the trajectories of the closed-loop stochastic systems are bounded in probability sense and the stochastic coupling of the system outputs can be effectively attenuated by the proposed control algorithm. Moreover, the stability of the stochastic systems is analyzed and the effectiveness of the proposed method has been demonstrated using a simulated example.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

RBFNN-based Minimum Entropy Filtering for a Class of Stochastic Nonlinear Systems

This paper presents a novel minimum entropy filter design for a class of stochastic nonlinear systems which are subjected to non-Gaussian noises. Motivated by stochastic distribution control, an output entropy model is developed using RBF neural network while the parameters of the model can be identified by the collected data. Based upon the presented model, the filtering problem has been investigated while the system dynamics have been represented. As the model output is the entropy of the estimation error, the optimal nonlinear filter is obtained based on the Lyapunov design which makes the model output minimum. Moreover, the entropy assignment problem has been discussed as an extension of the presented approach. To verify the presented design procedure, a numerical example is given which illustrates the effectiveness of the presented algorithm. The contributions of this paper can be included as 1) an output entropy model is presented using neural network; 2) a nonlinear filter design algorithm is developed as the main result and 3) a solution of entropy assignment problem is obtained which is an extension of the presented framework.

42 ENGINEERING↗
DOE OSTI2018

Nonlinear Decoupling Control with ANFIS-based Unmodeled Dynamics Compensation for A Class of Complex Industrial Processes

Complex industrial processes are multivariable and generally exhibit strong coupling among their control loops with heavy nonlinear nature that make it very difficult to obtain an accurate model. As a result, the conventional and data driven control methods are difficulty to apply. Using a twin-tank level control system as an example, a novel multivariable decupling control algorithm with adaptive neural fuzzy inference system (ANFIS) based unmodeled dynamics (UD) compensation is proposed in this paper for a class of complex industrial processes. At first, a nonlinear multivariable decupling controller with UD compensation is introduced. Different from the general method, the decomposition estimation algorithm by ANFIS is used to estimate the UD, and the desired estimating and decoupling control effects are achieved. Secondly, the proposed method does not require the complex switching mechanism which has been commonly used in the literature. This simplifies the obtained decoupling algorithm and its realization. Thirdly, based on some new lemmas and theorems, the conditions on the stability and convergence of the closed-loop system are analyzed to show the uniform boundedness of all the variables. Finally, experimental tests on a heavily coupled nonlinear twin-tank system are carried out to demonstrate the effectiveness and the practicability of the proposed method.

Complex industrial process, ANFIS, multivariable a↗
DOE OSTI2022

Design and Performance Characterization of RADICAL-Pilot on Leadership-Class Platforms

Many extreme scale scientific applications have workloads comprised of a large number of individual highperformance tasks. The Pilot abstraction decouples workload specification, resource management, and task execution via job placeholders and late-binding. As such, suitable implementations of the Pilot abstraction can support the collective execution of large number of tasks on supercomputers. We introduce RADICAL-Pilot (RP) as a portable, modular and extensible Pilot enabled runtime system. We describe RP's design, architecture and implementation. We characterize its performance and show its ability to scalably execute workloads comprised of tens of thousands heterogeneous tasks on DOE and NSF leadership-class HPC platforms. Specifically, we investigate RP's weak/strong scaling with CPU/GPU, single/multi core, (non)MPI tasks and python functions when using most of ORNL Summit and TACC Frontera. RADICAL-Pilot can be used stand-alone, as well as the runtime for third-party workflow systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Rapid determination of soil classes in soil profiles using vis–NIR spectroscopy and multiple objectives mixed support vector classification

Summary Visible‐near infrared (vis–NIR) spectroscopy can reveal various soil properties and facilitate soil classification. However, few studies have attempted to classify vertical soil profiles that contain several genetic horizons. Here, we propose the ‘multiple objectives mixed support vector classification’ (MOM–SVC) method to classify soil profiles. A total of 130 soil profiles were collected from genetic horizons in Zhejiang Province, China. After laboratory analysis, soil profiles were classified according to the Chinese Soil Taxonomy system. Vis–NIR spectra were recorded from each genetic horizon of each soil profile and were then pre‐processed. We performed the MOM–SVC method as follows: (i) created a support vector machine (SVM) model (one‐versus‐one approach) using spectral data from all soil horizons in calibration profiles, (ii) applied the SVM model on each horizon of the profile to be predicted, (iii) extracted ‘votes’ from each horizon and mixed (or summarized) them into the votes of each profile to be predicted and (iv) classified each profile by the majority‐voting method. We also investigated whether the additional input of auxiliary soil information (e.g. moist soil colour, soil organic matter and soil texture), which could be measured easily or be well predicted by vis–NIR spectroscopy, could improve the accuracy of soil classification when combined with it. Independent validation results showed that the MOM–SVC method performed better at the soil order level than at the suborder level. Adding auxiliary soil information to the classification model improved the overall accuracy of classification at the soil order level. The proposed MOM–SVC method provides a fast objective diagnostic of soil classes for use in soil surveys and can help to update soil databases when a more objective soil classification system is developed. Highlights The MOM–SVC method can be used to classify soil profiles objectively with a variety of soil horizons. Stratified random sampling was used to quantify prediction uncertainty in classification MOM–SVC can predict soil orders with greater accuracy than suborders. Adding auxiliary soil information into the classification model improved prediction accuracy.

Chen, S.↗
DOE OSTI2015

A Novel Class of Strain Measures for Digital Image Correlation

Abstract We propose a novel class strain measures for use with digital image correlation (DIC). Whereas the traditional notion of compatibility (strain as the derivative of the displacement field) is problematic when the displacement field varies substantially because of either measurement noise or material irregularity, the proposed measure remains robust, well defined and invariant under rigid body motion. Moreover, when the displacement field is smooth, the classical and proposed strain measures are approximations of each other. We demonstrate, via several numerical examples, the potential of this new strain measure for problems with steep gradients. We also show how the non‐local strain provides an intrinsic mechanism for filtering high‐frequency content from the strain profile and so has a high signal to noise ratio. This is a convenient feature considering image noise and its impact on strain calculations.

Lehoucq, R. B.↗
DOE OSTI2016

Laser-induced damage of intrinsic and extrinsic defects by picosecond pulses on multilayer dielectric coatings for petawatt-class lasers

Here, we describe a damage testing system and its use in investigating laser-induced optical damage initiated by both intrinsic and extrinsic precursors on multilayer dielectric coatings suitable for use in high-energy, large-aperture petawatt-class lasers. We employ small-area damage test methodologies to evaluate the intrinsic damage resistance of various coatings as a function of deposition methods and coating materials under simulated use conditions. In addition, we demonstrate that damage initiation by raster scanning at lower fluences and growth threshold testing are required to probe the density of extrinsic defects, which will limit large-aperture optics performance.

42 ENGINEERING↗
DOE OSTI2014

SU-E-T-172: Evaluation of the Exradin A26 Ion Chamber in Megavoltage Photon Beams as a Reference Class Instrument

Purpose: The Exradin A26 is a new design of micro-ionization ion chamber that externally resembles the Exradin A16 model but has significant internal changes to address measurement issues reported in the literature for the A16. This project involved the characterization of two versions of the A26 chamber in high energy x-rays with particular reference to the performance specification laid out in the imminent Addendum to TG-51. Methods: The Exradin A26 was investigated in a range of megavoltage photon beams (6–25 MV). Investigations looked at chamber settling, ion recombination and polarity. Since it has been previously shown that non-ideal performance is most easily identified through ion recombination measurements, the focus was on the determination of Pion. Results: i) Chamber settling - the chamber response stabilizes very quickly (within 3 minutes), even after a large change in the polarizing voltage.ii) The polarity correction was found to be small (within 0.2% of unity)iii) The chamber showed linear behavior for a Jaffe plot (1/reading vs 1/polarizing voltage) for applied voltages ≤ 200 V.iv) The recombination correction showed a linear variation with the doseper- pulse, was not significantly dependent on the polarity of the collecting voltage and was consistent with the chamber dimensions (i.e. agreed with Boag theory). Conclusion: An initial investigation of the Exradin A26 micro chamber suggests that although its performance exceeds the AAPM specification for a reference-class ion chamber for use in megavoltage photon beams it is a significant improvement over the previous A16 design. Further work is required to evaluate long-term stability and determine kQ factors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

New classes of topological crystalline insulators having surface rotation anomaly

We discover new types of quantum anomalies in two-dimensional systems with time-reversal symmetry (T) and discrete rotation symmetry with order of n = 2, 4, and 6 (C n ). The new anomalous states have n flavors of massless Dirac fermions protected by T and C n , whereas any two-dimensional lattices having the two symmetries must have a multiple of 4, 8, and 12 Dirac cones for n = 2, 4, and 6, respectively. We show that these anomalous states are physically realized on the surface of new classes of topological crystalline insulators, normal to the rotation axis. Moreover, these topological crystalline insulators support n gapless one-dimensional helical mode on the otherwise fully gapped side surface, connecting the anomalous two-dimensional states on the top and bottom surfaces. The presence of these helical modes enables a new quantum device made from a topological crystalline insulator nanorod, a “helical nanorod,” which has a quantized longitudinal conductance of ne 2 /h.

Science & Technology - Other Topics↗
DOE OSTI2011

Novel Insights Into The Mode of Inhibition of Class A SHV-1 Beta-Lactamases Revealed by Boronic Acid Transition State Inhibitors

Boronic acid transition state inhibitors (BATSIs) are potent class A and C {beta}-lactamase inactivators and are of particular interest due to their reversible nature mimicking the transition state. Here, we present structural and kinetic data describing the inhibition of the SHV-1 {beta}-lactamase, a clinically important enzyme found in Klebsiella pneumoniae, by BATSI compounds possessing the R1 side chains of ceftazidime and cefoperazone and designed variants of the latter, compounds 1 and 2. The ceftazidime and cefoperazone BATSI compounds inhibit the SHV-1 {beta}-lactamase with micromolar affinity that is considerably weaker than their inhibition of other {beta}-lactamases. The solved crystal structures of these two BATSIs in complex with SHV-1 reveal a possible reason for SHV-1's relative resistance to inhibition, as the BATSIs adopt a deacylation transition state conformation compared to the usual acylation transition state conformation when complexed to other {beta}-lactamases. Active-site comparison suggests that these conformational differences might be attributed to a subtle shift of residue A237 in SHV-1. The ceftazidime BATSI structure revealed that the carboxyl-dimethyl moiety is positioned in SHV-1's carboxyl binding pocket. In contrast, the cefoperazone BATSI has its R1 group pointing away from the active site such that its phenol moiety moves residue Y105 from the active site via end-on stacking interactions. To work toward improving the affinity of the cefoperazone BATSI, we synthesized two variants in which either one or two extra carbons were added to the phenol linker. Both variants yielded improved affinity against SHV-1, possibly as a consequence of releasing the strain of its interaction with the unusual Y105 conformation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Active-Site Protonation States in an Acyl-Enzyme Intermediate of a Class A β-Lactamase with a Monobactam Substrate

ABSTRACT The monobactam antibiotic aztreonam is used to treat cystic fibrosis patients with chronic pulmonary infections colonized by Pseudomonas aeruginosa strains expressing CTX-M extended-spectrum β-lactamases. The protonation states of active-site residues that are responsible for hydrolysis have been determined previously for the apo form of a CTX-M β-lactamase but not for a monobactam acyl-enzyme intermediate. Here we used neutron and high-resolution X-ray crystallography to probe the mechanism by which CTX-M extended-spectrum β-lactamases hydrolyze monobactam antibiotics. In these first reported structures of a class A β-lactamase in an acyl-enzyme complex with aztreonam, we directly observed most of the hydrogen atoms (as deuterium) within the active site. Although Lys 234 is fully protonated in the acyl intermediate, we found that Lys 73 is neutral. These findings are consistent with Lys 73 being able to serve as a general base during the acylation part of the catalytic mechanism, as previously proposed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

The Complexity Classes of Angular Diagrams of the Metal Conductivity in Strong Magnetic Fields

We consider angular diagrams describing the dependence of the magnetic conductivity of metals on the direction of the magnetic field in rather strong fields. As it can be shown, all angular conductivity diagrams can be divided into a finite number of classes with different complexities. The greatest interest among such diagrams is represented by diagrams with the maximal complexity, which can occur for metals with rather complicated Fermi surfaces. In describing the structure of complex diagrams, in addition to the description of the conductivity itself, the description of the Hall conductivity for different directions of the magnetic field plays very important role. For the evaluation of the complexity of angular diagrams of the conductivity of metals, it is also convenient to compare such diagrams with the full mathematical diagrams that are defined (formally) for the entire dispersion relation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Optimal-Order Preconditioners for Linear Systems Arising in the Semismooth Newton Solution of a Class of Control-Constrained Problems

We present a new multigrid preconditioner for the linear systems arising in the semismooth Newton method solution of certain control-constrained, quadratic distributed optimal control problems. Using a piecewise constant discretization of the control space, each semismooth Newton iteration essentially requires inverting a principal submatrix of the matrix entering the normal equations of the associated unconstrained optimal control problem, the rows (and columns) of the submatrix representing the constraints deemed inactive at the current iteration. Previously developed multigrid preconditioners for the aforementioned submatrices were based on constructing a sequence of conforming coarser spaces and proved to be of suboptimal quality for the class of problems considered. Instead, the multigrid preconditioner introduced in this work uses nonconforming coarse spaces, and it is shown that, under reasonable geometric assumptions on the constraints that are deemed inactive, the preconditioner approximates the inverse of the desired submatrix to optimal order. The preconditioner is tested numerically on a classical elliptic-constrained optimal control problem and further on a constrained image-deblurring problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A New Class of AMG Interpolation Methods Based on Matrix-Matrix Multiplications

A new class of distance-two interpolation methods for algebraic multigrid (AMG) that can be formulated in terms of sparse matrix-matrix multiplications is presented and analyzed. Compared with similar distance-two prolongation operators, the proposed algorithms exhibit improved efficiency and portability to various computing platforms, since they allow one to easily exploit existing high-performance sparse matrix kernels. The new interpolation methods have been implemented in hypre, a widely used parallel multigrid solver library. With the proposed interpolations, the overall time of hypre's BoomerAMG setup can be considerably reduced, while sustaining equivalent, sometimes improved, convergence rates. Numerical results for a variety of test problems on parallel machines are presented that support the superiority of the proposed interpolation operators over the existing ones in hypre.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Enabling event tracing at leadership-class scale through I/O forwarding middleware. In: HPDC '12 Proceedings of the 21st international symposium on High-Performance Parallel and Distributed Computing

Event tracing is an important tool for understanding the performance of parallel applications. As concurrency increases in leadership-class computing systems, the quantity of performance log data can overload the parallel file system, perturbing the application being observed. In this work we present a solution for event tracing at leadership scales. We enhance the I/O forwarding system software to aggregate and reorganize log data prior to writing to the storage system, significantly reducing the burden on the underlying file system for this type of traffic. Furthermore, we augment the I/O forwarding system with a write buffering capability to limit the impact of artificial perturbations from log data accesses on traced applications. To validate the approach, we modify the Vampir tracing toolset to take advantage of this new capability and show that the approach increases the maximum traced application size by a factor of 5x to more than 200,000 processes.

Ilsche, Thomas↗