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At least 883 records · Page 49

Manufacturing of Smart Structures Using Fiber Placement Manufacturing Processes

Smart structures research and development, with the ultimate aim of rapid commercial and military production of these structures, are at the forefront of the Synthesis and Processing of Intelligent Cost-Effective Structures (SPICES) program. As part of this ARPA-sponsored program, MDA-E is using fiber placement processes to manufacture integrated smart structure systems. These systems comprise advanced composite structures with embedded fiber optic sensors, shape memory alloys, piezoelectric actuators, and miniature accelerometers. Cost-effective approaches and solutions to smart material synthesis in the fiber-placement process, based upon integrated product development, are discussed herein.

Thomas, Matthew M.↗

Study of self-compliance behaviors and internal filament characteristics in intrinsic SiO{sub x}-based resistive switching memory

Self-compliance characteristics and reliability optimization are investigated in intrinsic unipolar silicon oxide (SiO{sub x})-based resistive switching (RS) memory using TiW/SiO{sub x}/TiW device structures. The program window (difference between SET voltage and RESET voltage) is dependent on external series resistance, demonstrating that the SET process is due to a voltage-triggered mechanism. The program window has been optimized for program/erase disturbance immunity and reliability for circuit-level applications. The SET and RESET transitions have also been characterized using a dynamic conductivity method, which distinguishes the self-compliance behavior due to an internal series resistance effect (filament) in SiO{sub x}-based RS memory. By using a conceptual “filament/resistive gap (GAP)” model of the conductive filament and a proton exchange model with appropriate assumptions, the internal filament resistance and GAP resistance can be estimated for high- and low-resistance states (HRS and LRS), and are found to be independent of external series resistance. Our experimental results not only provide insights into potential reliability issues but also help to clarify the switching mechanisms and device operating characteristics of SiO{sub x}-based RS memory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Contributions of major tau kinase activation and phospho-tau accumulation to cortical and hippocampal tangle formation and cognition in older adults

Aberrant activation of tau kinases (tauK) has been proposed as a major step in tau hyperphosphorylation and misfolding, and subsequent formation of neurofibrillary tangles (NFT) in Alzheimer's disease (AD). However, evidence of tauK hyperactivation in actual AD brains is scarce and inconsistent, and their role in age-related cognitive decline remains undocumented. We evaluated activated/inhibited species of CDK5/p35/p25, GSK3a/ß, and ERK1/2 as well as ten tau/phospho-tau (ptau) peptides (mapping Ser 202 , Thr 217 , Ser 262 , Ser 305 , and Ser 404 phospho-residues) by Western blot or selected reaction monitoring proteomics, respectively, in postmortem dorsolateral prefrontal cortex (DLPFC) and hippocampal samples of 150 participants from the Rush Memory and Aging Project (MAP). Regression models and mediation analyses assessed the contributions of these variables to tau phosphorylation, NFT deposition and antemortem cognitive status of MAP participants. Surprisingly, greater p25 and p35 (indices for CDK5 activation) and lower pSer 21/9 -GSK3a/ß (inhibited species) immunodensities were associated with lower ptau peptide amounts. Individuals with higher p25 cortical densities displayed better cognitive outcomes, particularly working memory. Statistical mediation analyses indicated that the beneficial effect of CDK5/p25 on cognition was mediated by lower densities of phospho-Thr 217 -tau and NFT deposition in DLPFC, and also identified Thr 217 and Ser 262 as the ptau sites with greatest influence in both NFT accumulation and cognitive impairment. The present data suggest that tau hyperphosphorylation, tangle deposition, and the subsequent cognitive impairment do not rely on aberrant activation of major tauKs. Additionally, novel evidence was provided for the beneficial contribution of cortical CDK5/p25 to the maintenance of working memory.

60 APPLIED LIFE SCIENCES↗

Injecting Errors for Testing Built-In Test Software

Two algorithms have been conceived to enable automated, thorough testing of Built-in test (BIT) software. The first algorithm applies to BIT routines that define pass/fail criteria based on values of data read from such hardware devices as memories, input ports, or registers. This algorithm simulates effects of errors in a device under test by (1) intercepting data from the device and (2) performing AND operations between the data and the data mask specific to the device. This operation yields values not expected by the BIT routine. This algorithm entails very small, permanent instrumentation of the software under test (SUT) for performing the AND operations. The second algorithm applies to BIT programs that provide services to users application programs via commands or callable interfaces and requires a capability for test-driver software to read and write the memory used in execution of the SUT. This algorithm identifies all SUT code execution addresses where errors are to be injected, then temporarily replaces the code at those addresses with small test code sequences to inject latent severe errors, then determines whether, as desired, the SUT detects the errors and recovers

Gender, Thomas K.↗

Practical Aspects of Krylov Subspace Iterative Methods in CFD

Implementation issues associated with the application of Krylov subspace iterative methods, such as Newton-GMRES, are presented within the framework of practical computational fluid dynamic (CFD) applications. This paper categorizes, evaluates, and contrasts the major ingredients (function evaluations, matrix-vector products, and preconditioners) of Newton-GMRES Krylov subspace methods in terms of their effect on the local linear and global nonlinear convergence, memory requirements, and accuracy. The discussion focuses on Newton-GMRES in both a structured multi-zone incompressible Navier-Stokes solver and an unstructured mesh finite-volume Navier-Stokes solver. Approximate versus exact matrix-vector products, effective preconditioners, and other pertinent issues are addressed.

Pulliam, Thomas H.↗

A modified approach for simulating electronically nonadiabatic dynamics via the generalized quantum master equation

We present a modified approach for simulating electronically nonadiabatic dynamics based on the Nakajima-Zwanzig generalized quantum master equation (GQME). The modified approach utilizes the fact that the Nakajima-Zwanzig formalism does not require casting the overall Hamiltonian in system-bath form, which is arguably neither natural nor convenient in the case of the Hamiltonian that governs nonadiabatic dynamics. Within the modified approach, the effect of the nuclear degrees of freedom on the time evolution of the electronic reduced density operator is fully captured by a memory kernel super-operator. A methodology for calculating the memory kernel from projection-free inputs is developed. Simulating the electronic dynamics via the modified approach, with a memory kernel obtained using exact or approximate methods, can be more cost effective and/or lead to more accurate results than direct application of those methods. The modified approach is compared to previously proposed GQME-based approaches, and its robustness and accuracy are demonstrated on a benchmark spin-boson model with a memory kernel which is calculated within the Ehrenfest method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimizing Data Movement for GPU-Based In-Situ Workflow Using GPUDirect RDMA

The extreme-scale computing landscape is increasingly dominated by GPU-accelerated systems. At the same time, in-situ workflows that employ memory-to-memory inter-application data exchanges have emerged as an effective approach for leveraging these extreme-scale systems. In the case of GPUs, GPUDirect RDMA enables third-party devices, such as network interface cards, to access GPU memory directly and has been adopted for intra-application communications across GPUs. In this paper, we present an interoperable framework for GPU-based in-situ workflows that optimizes data movement using GPUDirect RDMA. Specifically, we analyze the characteristics of the possible data movement pathways between GPUs from an in-situ workflow perspective, and design a strategy that maximizes throughput. Furthermore, we implement this approach as an extension of the DataSpaces data staging service, and experimentally evaluate its performance and scalability on a current leadership GPU cluster. The performance results show that the proposed design reduces data-movement time by up to 53% and 40% for the sender and receiver, respectively, and maintains excellent scalability for up to 256 GPUs.

Zhang, Bo↗

A Byzantine resilient processor with an encoded fault-tolerant shared memory

The memory requirements for ultra-reliable computers are expected to increase due to future increases in mission functionality and operating-system requirements. This increase will have a negative effect on the reliability and cost of the system. Increased memory size will also reduce the ability to reintegrate a channel after a transient fault, since the time required to reintegrate a channel in a conventional fault-tolerant processor is dominated by memory realignment time. A Byzantine Resilient Fault-Tolerant Processor with Fault-Tolerant Shared Memory (FTP/FTSM) is presented as a solution to these problems. The FTSM uses an encoded memory system, which reduces the memory requirement by one-half compared to a conventional quad-FTP design. This increases the reliability and decreases the cost of the system. The realignment problem is also addressed by the FTSM. Because any single error is corrected upon a read from the FTSM, a faulty channel's corrupted memory does not need realignment before reintegration of the faulty channel. A combination of correct-on-access and background scrubbing is proposed to prevent the accumulation of transient errors in the memory. With a hardware-implemented scrubber, the scrubbing cycle time, and therefore the memory fault latency, can be upper-bounded at a small value. This technique increases the reliability of the memory system and facilitates validation of its reliability model.

Butler, Bryan↗

On the Efficacy of Source Code Optimizations for Cache-Based Systems

Obtaining high performance without machine-specific tuning is an important goal of scientific application programmers. Since most scientific processing is done on commodity microprocessors with hierarchical memory systems, this goal of "portable performance" can be achieved if a common set of optimization principles is effective for all such systems. It is widely believed, or at least hoped, that portable performance can be realized. The rule of thumb for optimization on hierarchical memory systems is to maximize temporal and spatial locality of memory references by reusing data and minimizing memory access stride. We investigate the effects of a number of optimizations on the performance of three related kernels taken from a computational fluid dynamics application. Timing the kernels on a range of processors, we observe an inconsistent and often counterintuitive impact of the optimizations on performance. In particular, code variations that have a positive impact on one architecture can have a negative impact on another, and variations expected to be unimportant can produce large effects. Moreover, we find that cache miss rates - as reported by a cache simulation tool, and confirmed by hardware counters - only partially explain the results. By contrast, the compiler-generated assembly code provides more insight by revealing the importance of processor-specific instructions and of compiler maturity, both of which strongly, and sometimes unexpectedly, influence performance. We conclude that it is difficult to obtain performance portability on modern cache-based computers, and comment on the implications of this result.

VanderWijngaart, Rob F.↗

On the Efficacy of Source Code Optimizations for Cache-Based Systems

Obtaining high performance without machine-specific tuning is an important goal of scientific application programmers. Since most scientific processing is done on commodity microprocessors with hierarchical memory systems, this goal of "portable performance" can be achieved if a common set of optimization principles is effective for all such systems. It is widely believed, or at least hoped, that portable performance can be realized. The rule of thumb for optimization on hierarchical memory systems is to maximize temporal and spatial locality of memory references by reusing data and minimizing memory access stride. We investigate the effects of a number of optimizations on the performance of three related kernels taken from a computational fluid dynamics application. Timing the kernels on a range of processors, we observe an inconsistent and often counterintuitive impact of the optimizations on performance. In particular, code variations that have a positive impact on one architecture can have a negative impact on another, and variations expected to be unimportant can produce large effects. Moreover, we find that cache miss rates-as reported by a cache simulation tool, and confirmed by hardware counters-only partially explain the results. By contrast, the compiler-generated assembly code provides more insight by revealing the importance of processor-specific instructions and of compiler maturity, both of which strongly, and sometimes unexpectedly, influence performance. We conclude that it is difficult to obtain performance portability on modern cache-based computers, and comment on the implications of this result.

VanderWijngaart, Rob F.↗

Microglia are implicated in the development of paclitaxel chemotherapy-associated cognitive impairment in female mice

Chemotherapy remains a mainstay in the treatment of many types of cancer even though it is associated with debilitating behavioral side effects referred to as “chemobrain,” including difficulty concentrating and memory impairment. The predominant hypothesis in the field is that systemic inflammation drives these cognitive impairments, although the brain mechanisms by which this occurs remain poorly understood. Here, we hypothesized that microglia are activated by chemotherapy and drive chemotherapy-associated cognitive impairments. To test this hypothesis, we treated female C57BL/6 mice with a clinically-relevant regimen of a common chemotherapeutic, paclitaxel (6 i.p. doses at 30 mg/kg), which impairs memory of an aversive stimulus as assessed via a contextual fear conditioning (CFC) paradigm. In this work, paclitaxel increased the percent area of IBA1 staining in the dentate gyrus of the hippocampus. Moreover, using a machine learning random forest classifier we identified immunohistochemical features of reactive microglia in multiple hippocampal subregions that were distinct between vehicle- and paclitaxel-treated mice. Paclitaxel treatment also increased gene expression of inflammatory cytokines in a microglia-enriched population of cells from mice. Lastly, a selective inhibitor of colony stimulating factor 1 receptor, PLX5622, was employed to deplete microglia and then assess CFC performance following paclitaxel treatment. PLX5622 significantly reduced hippocampal gene expression of paclitaxel-induced proinflammatory cytokines and restored memory, suggesting that microglia play a critical role in the development of chemotherapy-associated neuroinflammation and cognitive impairments. This work provides critical evidence that microglia drive paclitaxel-associated cognitive impairments, a key mechanistic detail for determining preventative and intervention strategies for these burdensome side effects.

60 APPLIED LIFE SCIENCES↗

Unique properties of SBN and their use in a layered optical memory

Holographic storage experiments using crystal Sr(0.75)Ba(0.25)Nb2O6 (SBN 75/25) as a volume-phase holographic medium show that this material is the most sensitive crystalline storage medium yet discovered. An exposure level of 0.003 J/sq cm at 0.488 micron produces a 1% diffraction efficiency in a 5-mm length of crystal. In addition to high recording sensitivity, SBN 75/25 exhibits interesting electric-field induced effects that include electric-field enhanced recording sensitivity and voltage-switchable latent-to-active holographic reconstruction efficiency. These effects are explained in terms of drift and diffusion of photoionized carriers coupled with the nonlinear electrooptic behavior characteristic of this low Curie temperature ferroelectric crystal. A mechanism is proposed that correlates the observed electrically controlled holographic response with the dielectric behavior of the crystal. These interesting effects are used to implement a novel, layered optical memory having no moving parts and having electrical access for writing or reading selected layers.

Thaxter, J. B.↗

Voltage induced magnetostrictive switching of nanomagnets: Strain assisted strain transfer torque random access memory

A spintronic device, called the “strain assisted spin transfer torque (STT) random access memory (RAM),” is proposed by combining the magnetostriction effect and the spin transfer torque effect which can result in a dramatic improvement in the energy dissipation relative to a conventional STT-RAM. Magnetization switching in the device which is a piezoelectric-ferromagnetic heterostructure via the combined magnetostriction and STT effect is simulated by solving the Landau-Lifshitz-Gilbert equation incorporating the influence of thermal noise. The simulations show that, in such a device, each of these two mechanisms (magnetostriction and spin transfer torque) provides in a 90° rotation of the magnetization leading a deterministic 180° switching with a critical current significantly smaller than that required for spin torque alone. Such a scheme is an attractive option for writing magnetic RAM cells.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Performance model-directed data sieving for high-performance I/O

Many scientific computing applications and engineering simulations exhibit noncontiguous I/O access patterns. Data sieving is an important technique to improve the performance of noncontiguous I/O accesses by combining small and noncontiguous requests into a large and contiguous request. It has been proven effective even though more data are potentially accessed than demanded. In this study, we propose a new data sieving approach namely performance model-directed data sieving, or PMD data sieving in short. It improves the existing data sieving approach from two aspects: (1) dynamically determines when it is beneficial to perform data sieving; and (2) dynamically determines how to perform data sieving if beneficial. It improves the performance of the existing data sieving approach considerably and reduces the memory consumption as verified by both theoretical analysis and experimental results. Given the importance of supporting noncontiguous accesses effectively and reducing the memory pressure in a large-scale system, the proposed PMD data sieving approach in this research holds a great promise and will have an impact on high-performance I/O systems.

97 MATHEMATICS AND COMPUTING↗

A Heterogeneity-Aware Task Scheduler for Spark

Big data processing systems such as Spark are employed in an increasing number of diverse applications-such as machine learning, graph computation, and scientific computing-each with dynamic and different resource needs. These applications increasingly run on heterogeneous hardware, e.g., with out-of-core accelerators. However, big data platforms do not factor in the multi-dimensional heterogeneity of applications and hardware. This leads to a fundamental mismatch between the application and hardware characteristics, and the resource scheduling adopted in big data platforms. For example, Hadoop and Spark consider only data locality when assigning tasks to nodes, and typically disregard the hardware capabilities and suitability to specific application requirements. In this paper, we present RUPAM, a heterogeneity-aware task scheduling system for big data platforms, which considers both task-level resource characteristics and underlying hardware characteristics, as well as preserves data locality. RUPAM adopts a simple yet effective heuristic to decide the dominant scheduling factor (e.g., CPU, memory, or I/O), given a task in a particular stage. Our experiments show that RUPAM is able to improve the performance of representative applications by up to 62.3% compared to the standard Spark scheduler.

Computer Science↗

New dynamic FET logic and serial memory circuits for VLSI GaAs technology

The complexity of GaAs field effect transistor (FET) very large scale integration (VLSI) circuits is limited by the maximum power dissipation while the uniformity of the device parameters determines the functional yield. In this work, digital GaAs FET circuits are presented that eliminate the DC power dissipation and reduce the area to 50% of that of the conventional static circuits. Its larger tolerance to device parameter variations results in higher functional yield.

Eldin, A. G.↗

Radiation effects assessment of MRAM devices

The Magneto-resistive Random Access Memory (MRAM) from Freescale Semiconductor, MR2A16A, was subjected to heavy ion single event testing. Test results show that this device is sensitive to Single Event Latchup (SEL). The sensitivity of the MRAM was attributed to the complementary metal oxide semiconductor (CMOS) process in which the active portion of this device is constructed. Therefore, the device must be used with caution and may require mitigation techniques if used in a space environment. There was no indication that the MRAM technology itself, the memory element construction, is subject to damage from heavy ions.

McClure, Steve↗

Rosiglitazone attenuates inflammation and CA3 neuronal loss following traumatic brain injury in rats

Rosiglitazone, a potent peroxisome proliferator-activated receptor (PPAR)-γ agonist, has been shown to confer neuroprotective effects in stroke and spinal cord injury, but its role in the traumatic brain injury (TBI) is still controversial. Using a controlled cortical impact model in rats, the current study was designed to determine the effects of rosiglitazone treatment (6 mg/kg at 5 min, 6 h and 24 h post injury) upon inflammation and histological outcome at 21 d after TBI. In addition, the effects of rosiglitazone upon inflammatory cytokine transcription, vestibulomotor behavior and spatial memory function were determined at earlier time points (24 h, 1–5 d, 14–20 d post injury, respectively). Compared with the vehicle-treated group, rosiglitazone treatment suppressed production of TNFα at 24 h after TBI, attenuated activation of microglia/macrophages and increased survival of CA3 neurons but had no effect on lesion volume at 21 d after TBI. Rosiglitazone-treated animals had improved performance on beam balance testing, but there was no difference in spatial memory function as determined by Morris water maze. In summary, this study indicates that rosiglitazone treatment in the first 24 h after TBI has limited anti-inflammatory and neuroprotective effects in rat traumatic injury. Further study using an alternative dosage paradigm and more sensitive behavioral testing may be warranted. - Highlights: • Effects of rosiglitazone after CCI were evaluated using a rat TBI model. • Rosiglitazone suppressed production of TNFα at 24 h after CCI. • Rosiglitazone inhibited microglial activation at 21 d after CCI. • Rosiglitazone increased survival of CA3 neurons at 21 d after CCI. • Rosiglitazone-treated animals had improved performance in beam balance testing.

60 APPLIED LIFE SCIENCES↗