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At least 199 records · Page 11

Measurement-based performance evaluation technique for high-performance computers

A measurement-based performance evaluation technique has been used to characterize the OS performance of Cedar, a hierarchical shared-memory multiprocessor system. Thirteen OS performance meters were used to capture the operating system activities for compute-bound workloads. Three representative applications from the Perfect Benchmark Suite were used to measure the OS performance in a dedicated system and in multiprogrammed workloads. It was found that 13-23 percent of the total execution time on a dedicated system was spent in executing OS-related activities. Under multiprogramming, 12-14 percent of the total execution time was used by the OS. The impact of multiprogramming on the operating system performance meters was also measured.

Sharma, S.↗

Facilitating NASA's Use of GEIA-STD-0005-1, Performance Standard for Aerospace and High Performance Electronic Systems Containing Lead-Free Solder

GEIA-STD-0005-1 defines the objectives of, and requirements for, documenting processes that assure customers and regulatory agencies that AHP electronic systems containing lead-free solder, piece parts, and boards will satisfy the applicable requirements for performance, reliability, airworthiness, safety, and certify-ability throughout the specified life of performance. It communicates requirements for a Lead-Free Control Plan (LFCP) to assist suppliers in the development of their own Plans. The Plan documents the Plan Owner's (supplier's) processes, that assure their customer, and all other stakeholders that the Plan owner's products will continue to meet their requirements. The presentation reviews quality assurance requirements traceability and LFCP template instructions.

Plante, Jeannete↗

High-performance corrosion-resistant high-entropy alloys

This disclosure provides alloy compositions comprising the main constituent elements iron, nickel, cobalt, molybdenum, and chromium. In one embodiment, the alloy comprises 10.0 to 30.0 wt % iron; 30.0 to 60.0 wt % nickel; 10.0 to 25.0 wt % cobalt; 1.0 to 15.0 wt % molybdenum; 15.0 to 25.0 wt % chromium by weight; where the sum of iron and nickel is at least 50 wt %; and, where the balance comprises minor elements, the total amount of minor elements being about 5% or less by weight. The alloy compositions have use as coatings to protect metals and alloys from corrosion in extreme environments where corrosion is a major concern such as with exposure to sea water or sea water with CO 2 .

Hawk, Jeffrey A.↗

US Department of Energy, Office of Science High Performance Computing Facility Operational Assessment 2019 Oak Ridge Leadership Computing Facility

Oak Ridge National Laboratory's (ORNL's) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable computational ecosystems; creating innovative solutions for high performance computing (HPC) needs; and managing risks, safety, and security associated with operating some of the most powerful computers in the world. The results can be seen in the cutting-edge science conducted by users and the praise from the research community. Calendar year (CY) 2019 was a big year as OLCF staff ran five world-class resources (the leadershipclass computers Titan and Summit, the large analysis cluster called Eos, and the massive parallel filesystems called Atlas and Alpine)) and also began power and cooling upgrades for a 2021 exascale system called Frontier. While continuing exceptional operation of Titan, Eos, and Rhea, the OLCF released the Summit supercomputer for production on January 1, 2019. Summit debuted as the most capable and efficient system in its class and has been recognized as the most powerful system in the world for its performance on both the high performance linpack (HPL) and conjugate gradient (HPCG) benchmark applications since June 2018 according to TOP500. Summit represents the culmination of a multiyear effort between the OLCF, IBM, NVIDIA, and Mellanox to deliver a system that is unmatched for modeling, simulation, data analysis, and learning. To hit the ground running with science-ready applications on day one, application teams worked closely with the OLCF through the Center for Accelerated Application Readiness (CAAR) program for years in advance of the Summit deployment. CY 2019 was filled with outstanding results and accomplishments: a very high rating from users on overall satisfaction for the sixth year in a row; a tremendous amount of core-hours delivered to researchers from two leadership-class systems; and success in delivering on the allocation split of roughly 60%, 30%, and 10% of core-hours offered for the Innovative and Novel Computational Impact on Theory and Experiment (INCITE), Advanced Scientific Computing Research Leadership Computing Challenge (ALCC), and Director's Discretionary (DD) programs, respectively (see Operational Performance section). These accomplishments, coupled with the high utilization rates (overall and capability usage), represent the fulfillment of the promise of both leadership-class machines: efficient facilitation of leadership-class computational applications. Table ES.1 presents a summary of the 2019 OLCF metric targets and the associated results. More information can be found in the Operational Performance section for each OLCF resource. The scientific accomplishments of OLCF users are a strong indication of long-term operational success, with publications this year in such notable journals and publications as Nature, Nature Physics, Nature Plants, Physical Review X, Journal of the American Physical Society, Cell, Nano Letters, and Trends in Biotechnology. Crucial domain-specific discoveries facilitated by resources at the OLCF are described in the High Performance Computing Facility Operational Assessment 2019 Oak Ridge Leadership Computing Facility (OAR) Strategic Results section. For example, researchers used Summit to pinpoint and understand the production of proteins from genetic information, including mutations and the functional expression of disease (Section 8.2).

97 MATHEMATICS AND COMPUTING↗

Rotordynamic Instability Problems in High-Performance Turbomachinery

Rotordynamics and predictions on the stability of characteristics of high performance turbomachinery were discussed. Resolutions of problems on experimental validation of the forces that influence rotordynamics were emphasized. The programs to predict or measure forces and force coefficients in high-performance turbomachinery are illustrated. Data to design new machines with enhanced stability characteristics or upgrading existing machines are presented.

Source record↗

Saddle-Shaped Third Component with Out-of-Plane Electrostatic Dipole for Realizing High-Performance Photovoltaic Donor Terpolymers

Terpolymer fabrication is an effective methodology for molecular engineering and generating high-performance organic photovoltaic materials to construct highly efficient polymer solar cells. Modification of the polymer PM6 by incorporating a third component resulting in the formation of a ternary copolymer is reported to outperform PM6 in achieving enhanced device performances. However, one of the major challenges in constructing high-performance terpolymers is to counter the molecular disorder caused by the backbone entropy induced by the third moiety. Here, in this work, double B←N bridged bipyridine (BNBP) is used as the third component, which possesses a strong out-of-plane electrostatic dipole owing to the saddle-shaped B←N fused ring structure. The out-of-plane dipole moment introduced in the modified PM6 terpolymer can be used as a means for tuning and optimizing the nanostructures of the blended films. The prepared PM6-BNBP-4 blend polymer with 4% of the benzodithiophene dione monomers replaced by BNBP results in excellent power conversion efficiency of 19.13%. This work demonstrates that the out-of-plane electrostatic dipole moment in saddle-shaped molecules is valuable for achieving high-performance organic photovoltaic donor materials.

36 MATERIALS SCIENCE↗

A tough high performance composite matrix

This invention is a semi-interpenetrating polymer network which includes a high performance thermosetting polyimide having a nadic end group acting as a crosslinking site and a high performance linear thermoplastic polyimide. An improved high temperature matrix resin is provided which is capable of performing in the 200 to 300 C range. This resin has significantly improved toughness and microcracking resistance, excellent processability, mechanical performance and moisture and solvent resistances.

Pater, Ruth H.↗

New Insights into the High‐Performance Black Phosphorus Anode for Lithium‐Ion Batteries

Abstract Black phosphorus (BP) is a promising anode material in lithium‐ion batteries (LIBs) owing to its high electrical conductivity and capacity. However, the huge volume change of BP during cycling induces rapid capacity fading. In addition, the unclear electrochemical mechanism of BP hinders the development of rational designs and preparation of high‐performance BP‐based anodes. Here, a high‐performance nanostructured BP–graphite–carbon nanotubes composite (BP/G/CNTs) synthesized using ball‐milling method is reported. The BP/G/CNTs anode delivers a high initial capacity of 1375 mA h g −1 at 0.15 A g −1 and maintains 1031.7 mA h g −1 after 450 cycles. Excellent high‐rate performance is demonstrated with a capacity of 508.1 mA h g −1 after 3000 cycles at 2 A g −1 . Moreover, for the first time, direct evidence is provided experimentally to present the electrochemical mechanism of BP anodes with three‐step lithiation and delithiation using ex situ X‐ray diffraction (XRD), ex situ X‐ray absorption spectroscopy (XAS), ex situ X‐ray emission spectroscopy, operando XRD, and operando XAS, which reveal the formation of Li 3 P 7 , LiP, and Li 3 P. Furthermore, the study indicates an open‐circuit relaxation effect of the electrode with ex situ and operando XAS analyses.

Li, Minsi↗

High performance forward swept wing aircraft

A high performance aircraft capable of subsonic, transonic and supersonic speeds employs a forward swept wing planform and at least one first and second solution ejector located on the inboard section of the wing. A high degree of flow control on the inboard sections of the wing is achieved along with improved maneuverability and control of pitch, roll and yaw. Lift loss is delayed to higher angles of attack than in conventional aircraft. In one embodiment the ejectors may be advantageously positioned spanwise on the wing while the ductwork is kept to a minimum.

Koenig, David G.↗

New Synthesis Of High-Performance Bismaleimides

New general synthesis of tough and easy-to-process high-performance bismaleimides (BMI's) developed. Involves reaction of acetylene-terminated compounds with BMI's or biscitraconimides. Offers matrix resins and adhesives having combined advantages of toughness characteristic of thermoplastics and easy processability characteristic of thermosetting materials. Scheme has potential for providing high-performance matrix resins surviving well at high temperatures and absorb little moisture.

Pater, Ruth H.↗

The Novel Hybrid Ab Initio Model of High-Performance Structural Alloys Design for Fossil Energy Power Plants

The current project developed a novel HT-CALPHAD/DFT approach, which can quickly design new high-performance structural alloys for the application of FE power plants. The PI will mainly take charge of high-throughput DFT simulations and computational thermodynamics of the selected multicomponent alloy systems for the FE power plant applications. At the end of the project, a novel hybrid model based on high throughput CALPHAD/DFT simulations and computational thermodynamics will be developed to provide guidance on how to identify multi-component new high-performance structural alloys with much less computational effort needed. It will address the extensive computation time needed for DFT on the new alloys design. In addition, it will also address the well-known headache of DFT, i.e. how to make the accurate prediction of the high-temperature equilibria. The novel hybrid model the PI proposed will not only be applied to the design of high-performance structural alloys in FE power plants but in many different applications, such as nuclear reactors. This hybrid modeling approach includes four sections: 1) HT-CALPHAD modeling of Al-Co-Cr-Ni-Fe system with FCC and BCC phase. In this section, 3561 non-equiatomic compositions were randomly generated in order to investigate the phase stability of single FCC and BCC phases. Meanwhile, we proposed a data screening procedure to screen out the good candidates within these compositions, considering the temperature range, average density, and melting temperature, etc. 2) Investigation of FCC-Cr lattice stability in Fe-Cr system. We systematically assessed the reliability of FCC-Cr lattice stability derived by DFT and CALPHAD approaches. Meanwhile, the Fe-Cr binary system was chosen as a case study to verify the Cr lattice stability obtained by both approaches. 3) High-throughput DFT modeling on elastic properties of Al-Co-Cr-Ni-Fe systems. We predicted and established the FCC quinary elastic constant database of the Al-Co-Cr-Fe-Ni systems at 0K by using special quasi-random structure (SQS) approach. The predictions will start with pure elements of Al-Co-Cr-Fe-Ni system and will be continued with binaries, ternaries, quaternaries, and finally the quinary compositions. 3) Modeling of temperature-dependent elastic properties in Al-Co-Cr-Ni-Fe systems. In this part, we predict the thermal expansion coefficient and elastic stiffness coefficient as a function of temperature by applying quasiharmonic approximation. With this approach, the elastic properties of HEAs at elevate temperature can be estimated.

01 COAL, LIGNITE, AND PEAT↗

Tough high performance composite matrix

This invention is a semi-interpentrating polymer network which includes a high performance thermosetting polyimide having a nadic end group acting as a crosslinking site and a high performance linear thermoplastic polyimide. Provided is an improved high temperature matrix resin which is capable of performing in the 200 to 300 C range. This resin has significantly improved toughness and microcracking resistance, excellent processability, mechanical performance, and moisture and solvent resistances.

Pater, Ruth H.↗

Decoding Li + /Na + Exchange Route Toward High-Performance Mn-Based Layered Cathodes for Li-Ion Batteries

Li + /Na + exchange has been extensively explored as an effective method to prepare high-performance Mn-based layered cathodes for Li-ion batteries, since the first report in 1996 by P. G. Bruce (Nature, 1996. 381, 499–500). Understanding the detailed structural changes during the ion-exchange process is crucial to implement the synthetic control of high-performance layered Mn-based cathodes, but less studied. Herein, in situ synchrotron X-ray diffraction, density functional theory calculations, and electrochemical tests are combined to conduct the systemic studies into the structural changes during the ion-exchange process of an Mn-only layered cathode O3-type Li 0.67 [Li 0.22 Mn 0.78 ]O 2 (LLMO) from the corresponding counterpart P3-type Na 0.67 [Li 0.22 Mn 0.78 ]O 2 (NLMO). The temperature-resolved observations combined with theoretical calculations reveal that the Li + /Na + exchange is favorable thermodynamically and composited with two tandem topotactic phase transitions: 1) from NLMO to a layered intermediate through ≈60% of Li + /Na + exchange. 2) then to the final layered product LLMO through further Li insertion. Moreover, the intermediate-dominate composite is obtained by slowing down the exchange kinetics below room temperature, showing better electrochemical performance than LLMO obtained by the traditional molten-salt method. Finally, the findings provide guides for the synthetic control of high-performance Mn-based cathodes under mild conditions.

25 ENERGY STORAGE↗

High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated with the monitoring architecture to reduce the volume of event traffic flow in the system, and thereby reduce the intrusiveness of the monitoring process. We are developing an event filtering architecture to efficiently process the large volume of event traffic generated by LSD systems (such as distributed interactive applications). This filtering architecture is used to monitor collaborative distance learning application for obtaining debugging and feedback information. Our architecture supports the dynamic (re)configuration and optimization of event filters in large-scale distributed systems. Our work represents a major contribution by (1) survey and evaluating existing event filtering mechanisms In supporting monitoring LSD systems and (2) devising an integrated scalable high- performance architecture of event filtering that spans several kev application domains, presenting techniques to improve the functionality, performance and scalability. This paper describes the primary characteristics and challenges of developing high-performance event filtering for monitoring LSD systems. We survey existing event filtering mechanisms and explain key characteristics for each technique. In addition, we discuss limitations with existing event filtering mechanisms and outline how our architecture will improve key aspects of event filtering.

Maly, K.↗

DRAS: Deep Reinforcement Learning for Cluster Scheduling in High Performance Computing

Cluster schedulers are crucial in high-performance computing (HPC). They determine when and which user jobs should be allocated to available system resources. Existing cluster scheduling heuristics are developed by human experts based on their experience with specific HPC systems and workloads. However, the increasing complexity of computing systems and the highly dynamic nature of application workloads have placed tremendous burden on manually designed and tuned scheduling heuristics. More aggressive optimization and automation are needed for cluster scheduling in HPC. In this work, we present an automated HPC scheduling agent named DRAS (Deep Reinforcement Agent for Scheduling) by leveraging deep reinforcement learning. DRAS is built on a hierarchical neural network incorporating special HPC scheduling features such as resource reservation and backfilling. An efficient training strategy is presented to enable DRAS to rapidly learn the target environment. Once being provided a specific scheduling objective given by the system manager, DRAS automatically learns to improve its policy through interaction with the scheduling environment and dynamically adjusts its policy as workload changes. We implement DRAS into a HPC scheduling platform called CQGym. CQGym provides a common platform allowing users to flexibly evaluate DRAS and other scheduling methods such as heuristic and optimization methods. Furthermore, the experiments using CQGym with different production workloads demonstrate that DRAS outperforms the existing heuristic and optimization approaches by up to 50%.

97 MATHEMATICS AND COMPUTING↗

Damage-Mitigating Control of Space Propulsion Systems for High Performance and Extended Life

A major goal in the control of complex mechanical system such as spacecraft rocket engine's advanced aircraft, and power plants is to achieve high performance with increased reliability, component durability, and maintainability. The current practice of decision and control systems synthesis focuses on improving performance and diagnostic capabilities under constraints that often do not adequately represent the materials degradation. In view of the high performance requirements of the system and availability of improved materials, the lack of appropriate knowledge about the properties of these materials will lead to either less than achievable performance due to overly conservative design, or over-straining of the structure leading to unexpected failures and drastic reduction of the service life. The key idea in this report is that a significant improvement in service life could be achieved by a small reduction in the system dynamic performance. The major task is to characterize the damage generation process, and then utilize this information in a mathematical form to synthesize a control law that would meet the system requirements and simultaneously satisfy the constraints that are imposed by the material and structural properties of the critical components. The concept of damage mitigation is introduced for control of mechanical systems to achieve high performance with a prolonged life span. A model of fatigue damage dynamics is formulated in the continuous-time setting, instead of a cycle-based representation, for direct application to control systems synthesis. An optimal control policy is then formulated via nonlinear programming under specified constraints of the damage rate and accumulated damage. The results of simulation experiments for the transient upthrust of a bipropellant rocket engine are presented to demonstrate efficacy of the damage-mitigating control concept.

Ray, Asok↗

High-Performance GMRES Mixed-Precision (HPG-MxP) Benchmark

SAND2024-08539O The High Performance GMRES Mixed-Precision (HPG-MxP) is a benchmark for ranking high-performance supercomputers, allowing use of mixed-precision. Similar to HPCG benchmark, it is designed to profile the computers' capabilities to perform the computational and communication tasks that are commonly found in important classes of real-world applications. At the same time, like HPL-MxP benchmark, it allows the use of mixed-precision arithmetic, while ensuring the double-precision accuracy of the computed solution. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗