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At least 127 records · Page 7

OpenK: An Open Infrastructure for the Accumulation, Sharing and Reuse of High Performance Computing Knowledge

In high performance computing (HPC), often a wide range of knowledge about the particular domains, software applications, and hardware architectures are necessary for applying the right optimizations in the appropriate contexts. In today’s practice, however, such knowledge has been expressed and managed in an ad-hoc manner by each individual. Systematic accumulation, sharing and reuse of the knowledge across a broad community has been difficult. This paper introduces OpenK, an ontology-based open infrastructure for solving the problem. By centering around ontology – a generic knowledge representation – and extensible designs, it offers a promising support for lowering the barriers.

97 MATHEMATICS AND COMPUTING↗

The design of high-performance gliders

A high-performance glider is defined as a glider which has been designed to carry the pilot in a minimum of time a given distance, taking into account conditions which are as conveniently as possible. The present investigation has the objective to show approaches for enhancing the cross-country flight cruising speed, giving attention to the difficulties which the design engineer will have to overcome. The characteristics of the cross-country flight and their relation to the cruising speed are discussed, and a description is provided of mathematical expressions concerning the cruising speed, the sinking speed, and the optimum gliding speed. The effect of aspect ratio and wing loading on the cruising speed is illustrated with the aid of a graph. Trends in glider development are explored, taking into consideration the design of laminar profiles, the reduction of profile-related drag by plain flaps, and the variation of wing loading during the flight. A number of suggestions are made for obtaining gliders with improved performance.

Mueller, B.↗

High performance sapphire windows

High-quality, wide-aperture optical access is usually required for the advanced laser diagnostics that can now make a wide variety of non-intrusive measurements of combustion processes. Specially processed and mounted sapphire windows are proposed to provide this optical access to extreme environment. Through surface treatments and proper thermal stress design, single crystal sapphire can be a mechanically equivalent replacement for high strength steel. A prototype sapphire window and mounting system have been developed in a successful NASA SBIR Phase 1 project. A large and reliable increase in sapphire design strength (as much as 10x) has been achieved, and the initial specifications necessary for these gains have been defined. Failure testing of small windows has conclusively demonstrated the increased sapphire strength, indicating that a nearly flawless surface polish is the primary cause of strengthening, while an unusual mounting arrangement also significantly contributes to a larger effective strength. Phase 2 work will complete specification and demonstration of these windows, and will fabricate a set for use at NASA. The enhanced capabilities of these high performance sapphire windows will lead to many diagnostic capabilities not previously possible, as well as new applications for sapphire.

Bates, Stephen C.↗

On Performance Prediction of Big Data Transfer in High-performance Networks

Big data generated by large-scale scientific and industrial applications need to be transferred between different geographical locations for remote storage, processing, and analysis. High-speed dedicated connections provisioned in High-performance Networks (HPNs) are increasingly utilized to carry out such big data transfer. HPN management highly relies on an important capability of performance (mainly throughput) prediction to reserve sufficient bandwidth and meanwhile avoid over-provisioning that may result in unnecessary resource waste. This capability is critical to improving the resource (mainly bandwidth) utilization of dedicated connections and meeting various user requests for data transfer. Conventional methods conduct performance prediction by fitting prior observed transfer history with predefined loss functions, without considering unobservable latent factors such as competing loads on end hosts. Such latent factors also have a significant impact on the application-level data transfer performance, which may result in an inaccurate prediction model. In this paper, we first investigate the impact of latent factors and propose a clustering-based method to eliminate their negative impact on performance prediction. We then develop a robust machine learning-based performance predictor by: i) incorporating the proposed latent factor elimination method into data preprocessing, and ii) adopting a customized domain guided loss function. Extensive experimental results show that our predictor achieves significantly higher prediction accuracy than several other state-of-the-art methods.

Liu, Wuji↗

High performance computing and communications program

A review of the High Performance Computing and Communications (HPCC) program is provided in vugraph format. The goals and objectives of this federal program are as follows: extend U.S. leadership in high performance computing and computer communications; disseminate the technologies to speed innovation and to serve national goals; and spur gains in industrial competitiveness by making high performance computing integral to design and production.

Holcomb, Lee↗

High-performance deployable structures for the support of high-concentration ratio solar array modules

A study conducted on high-performance deployable structures for the support of high-concentration ratio solar array modules is discussed. Serious consideration is being given to the use of high-concentration ratio solar array modules or applications such as space stations. These concentrator solar array designs offer the potential of reduced cost, reduced electrical complexity, higher power per unit area, and improved survivability. Arrays of concentrators, such as the miniaturized Cassegrainian concentrator modules, present a serious challenge to the structural design because their mass per unit area (5.7 kg/square meters) is higher than that of flexible solar array blankets, and the requirement for accurate orientation towards the Sun (plus or minus 0.5 degree) requires structures with improved accuracy potentials. In addition, use on a space station requires relatively high structural natural frequencies to avoid deleterious interactions with control systems and other large structural components. The objective here is to identify and evaluate conceptual designs of structures suitable for deploying and accurately supporting high-concentration ratio solar array modules.

Mobrem, M.↗

Data Center Immersion Cooling: A Case Study and Summary of High-Performance Computing Cooling Technologies

The future of High Performance Computing (HPC) is carved out for all high-performance facilities. As computer processing increases exponentially, especially with the demand for AI training, more speed will equate to more computing density and ultimately more power draw and resource demand. Sandia National Laboratories has not seen or known of anything that would lead us to think this might change in the next 5 to 10 years.

97 MATHEMATICS AND COMPUTING↗

The High Performance Computing Initiative

The paper discusses NASA High Performance Computing Initiative (HPCI), an essential component of the Federal High Performance Computing Program. The HPCI program is designed to provide a thousandfold increase in computing performance, and apply the technologies to NASA 'Grand Challenges'. The Grand Challenges chosen include integrated multidisciplinary simulations and design optimizations of aerospace vehicles throughout the mission profiles; the multidisciplinary modeling and data analysis of the earth and space science physical phenomena; and the spaceborne control of automated systems, handling, and analysis of sensor data and real-time response to sensor stimuli.

Holcomb, Lee B.↗

High-Performance Accelerator Modeling: Toward Improving Controls and Diagnostics for High-Brightness Beams in Experiment

One of the main charges of beam physics is to improve the overall beam quality delivered to experiments and applications, which is generally quantified by the beam brightness. High brightness beams have numerous applications, including x-ray free electron lasers and ultrafast electron diffraction (UED). To these ends, this thesis details efforts to use high-performance models --- high-fidelity models that execute quickly --- for controls and diagnostics. To demonstrate the generality of these techniques, this thesis focuses on three of the most successful photoinjector designs currently used worldwide: the UCLA/SLAC/BNL-type high-gradient S-band gun, the continuous-wave high-repetition rate VHF APEX gun and the L-band DESY-PITZ-type gun. Work will be shown from Pegasus (UCLA), HiRES (LBNL) and FAST (FNAL).Specifically, data-driven models for online virtual diagnostics are presented, in this case, in the context of UED at HiRES, leading to a temporal resolution improvement. Methods for improving the fidelity of physics-based models are discussed, with examples at HiRES, Pegasus and FAST. Markov-chain Monte Carlo analysis is applied to match simulations, in the context of photocathode studies at HiRES and Pegasus. Lastly, the augmentation of online model-based predictions with model-independent optimization is explored in a fluctuating environment at Pegasus and HiRES. A central theme of this dissertation is working with parameter fluctuations when modeling an accelerator beamline. Long-term drifts and shot-to-shot jitter exist in every accelerator to a varying degree and therefore play an important role in every chapter of this dissertation. This thesis attempts to address the issues associated with these fluctuations when trying to develop faithful model representations of the system.

43 PARTICLE ACCELERATORS↗

A Queue Simulation Tool for a High Performance Scientific Computing Center

The NASA Center for Computational Sciences (NCCS) at the Goddard Space Flight Center provides high performance highly parallel processors, mass storage, and supporting infrastructure to a community of computational Earth and space scientists. Long running (days) and highly parallel (hundreds of CPUs) jobs are common in the workload. NCCS management structures batch queues and allocates resources to optimize system use and prioritize workloads. NCCS technical staff use a locally developed discrete event simulation tool to model the impacts of evolving workloads, potential system upgrades, alternative queue structures and resource allocation policies.

Spear, Carrie↗

Exploratory analysis and performance prediction of big data transfer in High-performance Networks

Big data transfer in large-scale scientific and business applications is increasingly carried out over connections with guaranteed bandwidth provisioned in High-performance Networks (HPNs) via advance bandwidth reservation. Provisioning agents need to carefully schedule data transfer requests, compute network paths, and allocate appropriate bandwidths. Such reserved bandwidths, if not fully utilized, could be simply wasted due to the exclusive access during the approved time window, and cause extra overhead and complexity for resource management. This calls for accurate performance prediction to reserve bandwidths that match actual needs and avoid over-provisioning. We employ machine learning algorithms to predict big data transfer performance based on extensive performance measurements collected in the past several years from data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated testbeds. We first analyze the performance patterns in response to a comprehensive list of parameters in end-host systems, network connections, and data transfer applications, which motivate the use of machine learning and also help us identify the effects of latent factors. We then propose threshold- and clustering-based methods to eliminate negative effects of latent factors in data preprocessing and build a robust performance predictor based on customized domain-oriented loss functions. The performance of the proposed methods is verified by extensive experiments using SVR and RFR as well as theoretical analysis of the general performance bound.

97 MATHEMATICS AND COMPUTING↗

High-performance mass storage system for workstations

Reduced Instruction Set Computer (RISC) workstations and Personnel Computers (PC) are very popular tools for office automation, command and control, scientific analysis, database management, and many other applications. However, when using Input/Output (I/O) intensive applications, the RISC workstations and PC's are often overburdened with the tasks of collecting, staging, storing, and distributing data. Also, by using standard high-performance peripherals and storage devices, the I/O function can still be a common bottleneck process. Therefore, the high-performance mass storage system, developed by Loral AeroSys' Independent Research and Development (IR&D) engineers, can offload a RISC workstation of I/O related functions and provide high-performance I/O functions and external interfaces. The high-performance mass storage system has the capabilities to ingest high-speed real-time data, perform signal or image processing, and stage, archive, and distribute the data. This mass storage system uses a hierarchical storage structure, thus reducing the total data storage cost, while maintaining high-I/O performance. The high-performance mass storage system is a network of low-cost parallel processors and storage devices. The nodes in the network have special I/O functions such as: SCSI controller, Ethernet controller, gateway controller, RS232 controller, IEEE488 controller, and digital/analog converter. The nodes are interconnected through high-speed direct memory access links to form a network. The topology of the network is easily reconfigurable to maximize system throughput for various applications. This high-performance mass storage system takes advantage of a 'busless' architecture for maximum expandability. The mass storage system consists of magnetic disks, a WORM optical disk jukebox, and an 8mm helical scan tape to form a hierarchical storage structure. Commonly used files are kept in the magnetic disk for fast retrieval. The optical disks are used as archive media, and the tapes are used as backup media. The storage system is managed by the IEEE mass storage reference model-based UniTree software package. UniTree software will keep track of all files in the system, will automatically migrate the lesser used files to archive media, and will stage the files when needed by the system. The user can access the files without knowledge of their physical location. The high-performance mass storage system developed by Loral AeroSys will significantly boost the system I/O performance and reduce the overall data storage cost. This storage system provides a highly flexible and cost-effective architecture for a variety of applications (e.g., realtime data acquisition with a signal and image processing requirement, long-term data archiving and distribution, and image analysis and enhancement).

Chiang, T.↗

Development of high-performance long-pulse discharge in KSTAR

High-performance long-pulse plasma operation is essential for producing economically viable fusion energy in tokamak devices. To achieve such discharges in KSTAR, firstly, the rapid increase in the temperature of plasma-facing components was mitigated. The temperature increase of the poloidal limiter, especially, was associated with beam-driven fast ion orbit loss and the discrepancy of the equilibrium reconstructed with heated magnetic probes of signal drift. The fast ions lost to the poloidal limiter were reduced by optimizing the plasma shape and the composition of neutral beam injection (NBI). This nonlinear signal drift was successfully reduced by a new thermal shielding protector on the magnetic probes. Secondly, a lower loop voltage approach was implemented to reduce a poloidal flux consumption rate. A plasma current of 400 kA and a line-averaged electron density of ~2.0 × 10 19 m –3 were chosen by considering the L–H power threshold, fast ion orbit loss, and beam shine-through power loss for low loop voltage in KSTAR. In addition, the application of electron cyclotron heating also helped maintain the plasma with low loop voltage (~25 mV) by enhancing the NBI-driven current and achieving a high poloidal beta (β P ) state. KSTAR has achieved a long pulse (~90 s) operation with the high performance of β P $\leqslant$ 2.7, thermal energy confinement enhancement factor (H 98y2 ) ~ 1.1, and fraction of non-inductive current (f NI ) $\leqslant$ 0.96. Still, gradual degradation of the plasma performance has been observed over time in the discharges. In one of the long-pulse discharges, β P reduced by ~18% over the time of ~8τ R (current relaxation time, τ R ~5 s) and ~1067τ E,th (thermal energy confinement time, τ E,th ~45 ms). The degradation may be closely associated with weak, yet growing, and persistent toroidal Alfvén eigenmodes and their effect on fast ion confinement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High-performance-vehicle technology

Propulsion needs of high performance military aircraft are discussed. Inlet performance, nozzle performance and cooling, and afterburner performance are covered. It is concluded that nonaxisymmetric nozzles provide cleaner external lines and enhanced maneuverability, but the internal flows are more complex. Swirl afterburners show promise for enhanced performance in the high altitude, low Mach number region.

Povinelli, L. A.↗

Impact of Selected High-Performance Fuel Blends on Three-Way Catalyst Light Off under Synthetic Spark-Ignition Engine-Exhaust Conditions

The U.S. Department of Energy funded Co-Optimization of Fuels and Engines initiative aims to simultaneously develop advanced engines along with high-performance fuels to reduce petroleum consumption. The engine exhaust of spark-ignited light-duty vehicles contains pollutants such as nitrogen oxides, carbon monoxide (CO), and non-methane organic gases. When operated above their “light-off” temperature, three-way catalysts (TWCs) efficiently control the emissions of these pollutants from the vehicle exhaust. However, below the catalyst light-off temperature, during cold start, the TWCs are not effective. Thus, the stringent environmental regulations necessitate cold-start compliance of advanced engines operating on novel fuels for commercialization. Exhaust composition strongly impacts the effectiveness of TWCs. Hence, ensuring that the high-performance fuels under consideration do not have detrimental effects on current emissions control technology is necessary. To mitigate cold-start emissions, a low light-off temperature of the fuel on the TWC is desirable. As real-world fuels are multicomponent blends, we conducted investigations into the light-off behavior of representative fuel mixtures on a three-mode redox-aged commercial TWC under synthetic engine-exhaust conditions. The high-performance fuels in this study included 10–30% volumetric levels of ethanol, isobutanol, diisobutylene, and an aromatic mixture. Each of these high-performance fuel components was mixed into a gasoline surrogate blendstock for oxygenate blending (BOB). Our results showed that aromatics and alkenes in the surrogate BOB inhibit low-temperature reactivity of alkanes, alcohols, and CO on the TWC and dominate the blend light-off behavior. All the high-performance fuel blends had a very similar light-off behavior to the surrogate gasoline BOB, indicating that blending up to 30% (by vol.) of high-performance blendstocks in a gasoline base fuel can potentially reduce greenhouse gas emissions through improved engine efficiency and petroleum displacement without jeopardizing the ability to meet emissions regulations. While some high-performance blendstocks demonstrated lower light-off temperatures than a surrogate gasoline blend, taking advantage of the higher catalytic reactivity of these blendstocks to reduce cold-start emissions would require reducing the aromatic content in petroleum-based market fuels.

33 ADVANCED PROPULSION SYSTEMS↗

Nonlinear stability and control study of highly maneuverable high performance aircraft

This project is intended to research and develop new nonlinear methodologies for the control and stability analysis of high-performance, high angle-of-attack aircraft such as HARV (F18). Past research (reported in our Phase 1, 2, and 3 progress reports) is summarized and more details of final Phase 3 research is provided. While research emphasis is on nonlinear control, other tasks such as associated model development, system identification, stability analysis, and simulation are performed in some detail as well. An overview of various models that were investigated for different purposes such as an approximate model reference for control adaptation, as well as another model for accurate rigid-body longitudinal motion is provided. Only a very cursory analysis was made relative to type 8 (flexible body dynamics). Standard nonlinear longitudinal airframe dynamics (type 7) with the available modified F18 stability derivatives, thrust vectoring, actuator dynamics, and control constraints are utilized for simulated flight evaluation of derived controller performance in all cases studied.

Mohler, R. R.↗

Performance Analysis of an Optimization Algorithm for Metamaterial Design on the Integrated High-Performance Computing and Quantum Systems

Optimizing metamaterials with complex geometries is a big challenge. Although an active learning algorithm, combining machine learning (ML), quantum computing, and optical simulation, has emerged as an efficient optimization tool, it still faces difficulties in optimizing complex structures that have potentially high performance. In this work, we comprehensively analyze the performance of an optimization algorithm for metamaterial design on the integrated HPC and quantum systems. We demonstrate significant time advantages through message-passing interface (MPI) parallelization on the high-performance computing (HPC) system showing approximately 54% faster ML tasks and 67 times faster optical simulation against serial workloads. Furthermore, we analyze the performance of a quantum algorithm designed for optimization, which runs with various quantum simulators on a local computer or HPC-quantum system. Results showcase ~24 times speedup when executing the optimization algorithm on the HPC-quantum hybrid system. This study paves a way to optimize complex metamaterials using the integrated HPC-quantum system.

Kim, Seongmin↗

High performance, inexpensive solar cell process capable of a high degree of automation

This paper proposes a process for inexpensive high performance solar cell fabrication that can be automated for further cost reduction and higher throughputs. The unique feature of the process is the use of oxides as doping sources for simultaneous n(+) junction formation and back p(+) layer, as a mask for metallization and as an in situ AR coating for spectrum matching. Cost analysis is performed to show that significant cost reductions over the conventional process is possible using the proposed scheme and the cost intensive steps are identified which can be further reduced to make the process compatible with the needed price goals of 50 cents/watt. The process was demonstrated by fabricating n(+)-p cells using Arsenic doped oxides. Simple n(+)-p structure cells showed corrected efficiencies of 14.5% (AMO) and 12% with doped oxide as an in situ antireflection coating.

Shah, P.↗