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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

TH-E-BRF-03: A Multivariate Interaction Model for Assessment of Hippocampal Vascular Dose-Response and Early Prediction of Radiation-Induced Neurocognitive Dysfunction

Purpose: Vascular injury could be a cause of hippocampal dysfunction leading to late neurocognitive decline in patients receiving brain radiotherapy (RT). Hence, our aim was to develop a multivariate interaction model for characterization of hippocampal vascular dose-response and early prediction of radiation-induced late neurocognitive impairments. Methods: 27 patients (17 males and 10 females, age 31–80 years) were enrolled in an IRB-approved prospective longitudinal study. All patients were diagnosed with a low-grade glioma or benign tumor and treated by 3-D conformal or intensity-modulated RT with a median dose of 54 Gy (50.4–59.4 Gy in 1.8− Gy fractions). Six DCE-MRI scans were performed from pre-RT to 18 months post-RT. DCE data were fitted to the modified Toft model to obtain the transfer constant of gadolinium influx from the intravascular space into the extravascular extracellular space, Ktrans, and the fraction of blood plasma volume, Vp. The hippocampus vascular property alterations after starting RT were characterized by changes in the hippocampal mean values of, μh(Ktrans)τ and μh(Vp)τ. The dose-response, Δμh(Ktrans/Vp)pre->τ, was modeled using a multivariate linear regression considering integrations of doses with age, sex, hippocampal laterality and presence of tumor/edema near a hippocampus. Finally, the early vascular dose-response in hippocampus was correlated with neurocognitive decline 6 and 18 months post-RT. Results: The μh(Ktrans) increased significantly from pre-RT to 1 month post-RT (p<0.0004). The multivariate model showed that the dose effect on Δμh(Ktrans)pre->1M post-RT was interacted with sex (p<0.0007) and age (p<0.00004), with the dose-response more pronounced in older females. Also, the vascular dose-response in the left hippocampus of females was significantly correlated with memory function decline at 6 (r = − 0.95, p<0.0006) and 18 (r = −0.88, p<0.02) months post-RT. Conclusion: The hippocampal vascular response to radiation could be sex and age dependent. The early hippocampal vascular dose-response could predict late neurocognitive dysfunction. (Support: NIH-RO1NS064973)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A long short-term memory embedding for hybrid uplifted reduced order models

In this paper, we introduce an uplifted reduced order modeling (UROM) approach through the integration of standard projection based methods with long short-term memory (LSTM) embedding. Our approach has three modeling layers or components. In the first layer, we utilize an intrusive projection approach to model dynamics represented by the largest modes. The second layer consists of an LSTM model to account for residuals beyond this truncation. This closure layer refers to the process of including the residual effect of the discarded modes into the dynamics of the largest scales. However, the feasibility of generating a low rank approximation tails off for higher Kolmogorov n -width systems due to the underlying nonlinear processes. The third uplifting layer, called super-resolution, addresses this limited representation issue by expanding the span into a larger number of modes utilizing the versatility of LSTM. Therefore, our model integrates a physics-based projection model with a memory embedded LSTM closure and an LSTM based super-resolution model. In several applications, we exploit the use of Grassmann manifold to construct UROM for unseen conditions. We performed numerical experiments by using the Burgers and Navier-Stokes equations with quadratic nonlinearity. Finally, our results show robustness of the proposed approach in building reduced order models for parameterized systems and confirm the improved trade-off between accuracy and efficiency.

42 ENGINEERING↗
DOE OSTI2017

Optimizing checkpoint data placement with guaranteed burst buffer endurance in large-scale hierarchical storage systems

Non-volatile devices, such as SSDs, will be an integral part of the deepening storage hierarchy on large-scale HPC systems. These devices can be on the compute nodes as part of a distributed burst buffer service or they can be external. Wherever they are located in the hierarchy, one critical design issue is the SSD endurance under the write-heavy workloads, such as the checkpoint I/O for scientific applications. For these environments, it is widely assumed that checkpoint operations can occur once every 60 min and for each checkpoint step as much as half of the system memory can be written out. Unfortunately, for large-scale HPC applications, the burst buffer SSDs can be worn out much more quickly given the extensive amount of data written at every checkpoint step. One possible solution is to control the amount of data written by reducing the checkpoint frequency. However, a direct effect caused by reduced checkpoint frequency is the increased vulnerability window of system failures and therefore potentially wasted computation time, especially for large-scale compute jobs.

Computer Science↗
DOE OSTI2016

Critical Points Based Register-Concurrency Autotuning for GPUs

The unprecedented prevalence of GPGPU is largely attributed to its abundant on-chip register resources, which allow massively concurrent threads and extremely fast context switch. However, due to internal memory capacity constraints, there is a tradeoff between the per-thread register usage and the overall concurrency. This becomes a design problem in terms of performance tuning, since the performance “sweet spot” which can be significantly affected by these two factors is generally unknown beforehand. In this paper, we propose an effective autotuning solution to quickly and efficiently select the optimal number of registers perthread for delivering the best GPU performance. Experiments on three generations of GPUs (Nvidia Fermi, Kepler and Maxwell) demonstrate that our simple strategy can achieve an average of 10% performance improvement while a max of 50% over the original version without modifying the user program. Additionally, to reduce local cache misses due to register spilling and further improve performance, we explore three optimization schemes (i.e. bypass L1 for global memory access, enlarge local L1 cache and spill into shared memory) and discuss their impact on performance on a Kepler GPU.

auto-tuning↗
NASA NTRS1932

Wind-Tunnel Tests on Airfoil Boundary Layer Control Using a Backward-Opening Slot

This report presents the results of an investigation to determine the effect of boundary layer control on the lift and drag of an airfoil. Boundary layer control was accomplished by means of a backward-opening slot in the upper surface of the hollow airfoil. Air was caused to flow through this slot by a pressure which was maintained inside the airfoil by a blower. Various slot locations, slot openings, and wing pressures were used. The tests were conducted in the 5-foot atmospheric wind tunnel of the Langley Memorial Aeronautical Laboratory. Under the test conditions, the maximum lift coefficient was increased about 96 per cent for one slot arrangement, and the minimum drag coefficient was decreased about 27 per cent for another, both being compared with the results obtained with the unslotted airfoil. It is believed from this investigation that the above effects may be increased by the use of larger slot openings, better slot locations, multiple slots, improved airfoil profiles, and trailing edge flaps.

Bamber, Millard J↗
DOE OSTI2017

Degradation of superconducting Nb/NbN films by atmospheric oxidation

Niobium and niobium nitride thin films are transitioning from fundamental research toward wafer scale manufacturing with technology drivers that include superconducting circuits and electronics, optical single photon detectors, logic, and memory. Successful microfabrication requires precise control over the properties of sputtered superconducting films, including oxidation. Previous work has demonstrated the mechanism in oxidation of Nb and how film structure could have deleterious effects upon the superconducting properties. This study provides an examination of atmospheric oxidation of NbN films. By examination of the room temperature sheet resistance of NbN bulk oxidation was identified and confirmed by secondary ion mass spectrometry. As a result, Meissner magnetic measurements confirmed the bulk oxidation not observed with simple cryogenic resistivity measurements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Energy Conservation Through Cloned Execution Of Simulations

High-performance computing facilities used for scientific computing draw enormous energy, some of them consuming many megawatt-hours. Saving the energy consumption of computations on such facilities can dramatically reduce the total cost of their operation and help reduce environmental effects. Here, we focus on a way to reduce energy consumption in many ensembles of simulations. Using the method of simulation cloning to exploit parallelism while also significantly conserving the computational and memory requirements, we perform a detailed empirical study of energy consumed on a large supercomputer consisting of hardware accelerator cards (graphical processing units, GPUs). We build on previous insights from mathematical analysis and implementation of cloned simulations that result in computational and memory savings by several orders-of-magnitude. Using instrumentation to track the power drawn by thousands of accelerator cards, we report significant aggregate energy savings from cloned simulations.

Yoginath, Srikanth↗
NASA NTRS1982

Fault-tolerance memory system architecture for radiation induced errors

A fault-tolerant memory (FTM) architecture is presented which can be used to overcome soft memory errors induced by alpha particles, cosmic radiation, or other random sources. The characteristics of the FTM are presented, a mathematical model is developed, and numerical examples are considered to illustrate the effectiveness of the approach. The FTM architecture has been incorporated in the NASA Standard Spacecraft Computer (NSSC-II) which will be employed in a variety of future space payloads and experiments.

White, J. B., Jr.↗
NASA NTRS1988

Portable inference engine: An extended CLIPS for real-time production systems

The present C-Language Integrated Production System (CLIPS) architecture has not been optimized to deal with the constraints of real-time production systems. Matching in CLIPS is based on the Rete Net algorithm, whose assumption of working memory stability might fail to be satisfied in a system subject to real-time dataflow. Further, the CLIPS forward-chaining control mechanism with a predefined conflict resultion strategy may not effectively focus the system's attention on situation-dependent current priorties, or appropriately address different kinds of knowledge which might appear in a given application. Portable Inference Engine (PIE) is a production system architecture based on CLIPS which attempts to create a more general tool while addressing the problems of real-time expert systems. Features of the PIE design include a modular knowledge base, a modified Rete Net algorithm, a bi-directional control strategy, and multiple user-defined conflict resolution strategies. Problems associated with real-time applications are analyzed and an explanation is given for how the PIE architecture addresses these problems.

Le, Thach↗
NASA NTRS1999

Satellite Remote Sensing of Aerosol Forcing

Aerosol and cloud impacts on the earth's climate become a recent hot topic in climate studies. Having near future earth observing satellites, EOS-AM1 (Earth Observing System-AM1), ENVISAT (Environmental Satellites) and ADEOS-2 (Advanced Earth Observation Satellite-2), it will be a good timing to discuss how to obtain and use the microphysical parameters of aerosols and clouds for studying their climate impacts. Center for Climate System Research (CCSR) of the University of Tokyo invites you to 'Symposium on synergy between satellite-remote sensing and climate modeling in aerosol and cloud issues.' Here, we like to discuss the current and future issues in the remote sensing of aerosol and cloud microphysical parameters and their climate modeling studies. This workshop is also one of workshop series on aerosol remote sensing held in 1996, Washington D. C., and Meribel, France in 1999. It should be reminded that NASDA/ADEOS-1 & -2 (National Space Development Agency of Japan/Advanced Earth Observation Satellite-1 & -2) Workshop will be held in the following week (Dec. 6-10, 1999), so that this opportunity will be a perfect period for you to attend two meetings for satellite remote sensing in Japan. A weekend in Kyoto, the old capital of Japan, will add a nice memory to your visiting Japan. *Issues in the symposium: 1) most recent topics in aerosol and cloud remot sensing, and 2) utility of satellite products on climate modeling of cloud-aerosol effects.

Remer, Lorraine↗
NASA NTRS2001

Non-Volatile Memory Technology Symposium 2001: Proceedings

This publication contains the proceedings for the Non-Volatile Memory Technology Symposium 2001 that was held on November 7-8, 2001 in San Diego, CA. The proceedings contains a a wide range of papers that cover current and new memory technologies including Flash memories, Magnetic Random Access Memories (MRAM and GMRAM), Ferro-electric RAM (FeRAM), and Chalcogenide RAM (CRAM). The papers presented in the proceedings address the use of these technologies for space applications as well as radiation effects and packaging issues.

Aranki, Nazeeh↗
NASA NTRS2011

Characteristics of a Nonvolatile SRAM Memory Cell Utilizing a Ferroelectric Transistor

The SRAM cell circuit is a standard for volatile data storage. When utilizing one or more ferroelectric transistors, the hysteresis characteristics give unique properties to the SRAM circuit, providing for investigation into the development of a nonvolatile memory cell. This paper discusses various formations of the SRAM circuit, using ferroelectric transistors, n-channel and p-channel MOSFETs, and resistive loads. With varied source and supply voltages, the effects on the timing and retention characteristics are investigated, including retention times of up to 24 hours.

Mitchell, Cody↗
NASA NTRS2009

Comparison of TID Response and SEE Characterization of Single and Multi Level High Density NAND Flash Memories

Heavy ion single-event measurements and TID response for 8Gb commercial NAND flash memories are reported. Radiation results of multi-level flash technology are compared with results from single-level flash technology. In general, these commercial high density memories appear to be much less susceptible to SEE and have better TID response compared to older generations of flash memories. The charge pump survived up to 600 krads.

nonvolatile memory↗
DOE OSTI2014

Modeling the Virtual Machine Launching Overhead under Fermicloud

FermiCloud is a private cloud developed by the Fermi National Accelerator Laboratory for scientific workflows. The Cloud Bursting module of the FermiCloud enables the FermiCloud, when more computational resources are needed, to automatically launch virtual machines to available resources such as public clouds. One of the main challenges in developing the cloud bursting module is to decide when and where to launch a VM so that all resources are most effectively and efficiently utilized and the system performance is optimized. However, based on FermiCloud’s system operational data, the VM launching overhead is not a constant. It varies with physical resource (CPU, memory, I/O device) utilization at the time when a VM is launched. Hence, to make judicious decisions as to when and where a VM should be launched, a VM launch overhead reference model is needed. The paper is to develop a VM launch overhead reference model based on operational data we have obtained on FermiCloud and uses the reference model to guide the cloud bursting process.

Garzoglio, Gabriele↗
DOE OSTI2016

On the origin of resistive switching volatility in Ni/TiO{sub 2}/Ni stacks

Resistive switching and resistive random access memories have attracted huge interest for next generation nonvolatile memory applications, also thought to be able to overcome flash memories limitations when arranged in crossbar arrays. A cornerstone of their potential success is that the toggling between two distinct resistance states, usually a High Resistive State (HRS) and a Low Resistive State (LRS), is an intrinsic non-volatile phenomenon with the two states being thermodynamically stable. TiO{sub 2} is one of the most common materials known to support non-volatile RS. In this paper, we report a volatile resistive switching in a titanium dioxide thin film sandwiched by two nickel electrodes. The aim of this work is to understand the underlying physical mechanism that triggers the volatile effect, which is ascribed to the presence of a NiO layer at the bottom interface. The NiO layer alters the equilibrium between electric field driven filament formation and thermal enhanced ion diffusion, resulting in the volatile behaviour. Although the volatility is not ideal for non-volatile memory applications, it shows merit for access devices in crossbar arrays due to its high LRS/HRS ratio, which are also briefly discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Implementing efficient data compression and encryption in a persistent key-value store for HPC

Recently, persistent data structures, like key-value stores (KVSs), which are stored in a high-performance computing (HPC) system’s nonvolatile memory, provide an attractive solution for a number of emerging challenges like limited I/O performance. Data compression and encryption are two well-known techniques for improving several properties of such data-oriented systems. This article investigates how to efficiently integrate data compression and encryption into persistent KVSs for HPC with the ultimate goal of hiding their costs and complexity in terms of performance and ease of use. Our compression technique exploits deep memory hierarchy in an HPC system to achieve both storage reduction and performance improvement. Our encryption technique provides a practical level of security and enables sharing of sensitive data securely in complex scientific workflows with nearly imperceptible cost. We implement the proposed techniques on top of a distributed embedded KVS to evaluate the benefits and costs of incorporating these capabilities along different points in the dataflow path, illustrating differences in effective bandwidth, latency, and additional computational expense on Swiss National Supercomputing Centre’s Grand Tavé and National Energy Research Scientific Computing Center’s Cori.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

CoREC: Scalable and Resilient In-memory Data Staging for In-situ Workflows

The dramatic increase in the scale of current and planned high-end HPC systems is leading new challenges, such as the growing costs of data movement and IO, and the reduced mean time between failures (MTBF) of system components. In-situ workflows, i.e., executing the entire application workflows on the HPC system, have emerged as an attractive approach to address data-related challenges by moving computations closer to the data, and staging-based frameworks have been effectively used to support in-situ workflows at scale. However, the resilience of these staging-based solutions has not been addressed, and they remain susceptible to expensive data failures. Furthermore, naive use of data resilience techniques such as n-way replication and erasure codes can impact latency and/or result in significant storage overheads. In this article, we present CoREC, a scalable and resilient in-memory data staging runtime for large-scale in-situ workflows. CoREC uses a novel hybrid approach that combines dynamic replication with erasure coding based on data access patterns. It also leverages multiple levels of replications and erasure coding to support diverse data resiliency requirements. Furthermore, the article presents optimizations for load balancing and conflict-avoiding encoding, and a low overhead, lazy data recovery scheme. We have implemented the CoREC runtime and have deployed with the DataSpaces staging service on leadership class computing machines and present an experimental evaluation in the article. Here, the experiments demonstrate that CoREC can tolerate in-memory data failures while maintaining low latency and sustaining high overall storage efficiency at large scales.

97 MATHEMATICS AND COMPUTING↗