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The application of cellular arrays to NASA missions was studied. Cellular arrays are iterative logical and memory structures which can be programmed to accomplish a wide variety of logical tasks. Used in long-duration space missions, spare cellular arrays can be remotely programmed to replace faulty logical subsystems as the need arises.
A small ferroelectric ceramic element is used with an insulating gate transistor and two diodes as an electrically addressed, nonvolatile memory device which is read out nondestructively. The device uses the anomalous photovoltaic effect in ferroelectric ceramics, an effect in which the polarity and magnitude of photovoltages depend on the direction and magnitude of remanent polarization. Experimental results give memory characteristics. The device could be programmed with pulses as short as 200 ns. There is long-time retention of stored data.
Flight data systems' software development is chronicled for the period encompassing NASA's Apollo, Space Shuttle, and (ongoing) Space Station Freedom programs, with attention to the methodologies and 'development tools' employed in each case and their mutual relationships. A dominant concern in all three programs has been the accommodation of software change; it has also been noted that any such long-term program carries the additional challenge of identifying which elements of its software-related 'institutional memory' are most critical, in order to preclude their loss through the retirement, promotion, or transfer of its 'last expert'.
Method for partial matching of data makes conventional electronic memory addressable via its contents. When implemented by suitable algorithm, method enables computer system containing memory to search memory for datum making exact or best approximate match to datum in query. Advantages are: requires neither long "learning" time nor "retraining" when additional data stored and attaches to each datum relative importance that can change with time without decreasing speed of retrieval. Responses include exact or approximate recollection, indications of ambiguity, avoidance, and even forgetfulness.
Fabricated by Expanded Rubber & Plastics Corporation, Temper Foam provides better impact protection for airplane passengers and enhances passenger comfort on long flights because it distributes body weight and pressure evenly over the entire contact area. Called a "memory foam" it matches the contour of the body pressing against it and returns to its original shape once the pressure is removed. As a shock absorber, a three-inch foam pad has the ability to absorb the impact of a 10-foot fall by an adult. Applications include seat cushioning for transportation vehicles, padding for furniture and a variety of athletic equipment medical applications including wheelchair padding, artificial limb socket lining, finger splint and hand padding for burn patients, special mattresses for the bedridden and dental stools. Production and sales rights are owned by Temper Foam, Inc. Material is manufactured under license by the Dewey and Almy Division of Grace Chemical Corporation. Distributors of the product are Kees Goebel Medical Specialties, Inc. and Alimed, Inc. They sell Temper Foam in bulk to the fabricators who trim it to shapes required by their customers.
JPL and Alacron have recently developed a high performance, DUV camera with a superlattice doped CMOS imaging detector. Supperlattice doped detectors achieve nearly 100% internal quantum efficiency in the deep and far ultraviolet, and a single layer, Al2O3 antireflection coating enables 64% external quantum efficiency at 263nm. In lifetime tests performed at Applied Materials using 263 nm pulsed, solid state and 193 nm pulsed excimer laser, the quantum efficiency and dark current of the JPL/Alacron camera remained stable to better than 1% precision during long-term exposure to several billion laser pulses, with no measurable degradation, no blooming and no image memory at 1000 fps.
GPU memory corruption and in particular double-bit errors (DBEs) remain one of the least understood aspects of HPC system reliability. Albeit rare, their occurrences always lead to job termination and can potentially cost thousands of node-hours, either from wasted computations or as the overhead from regular checkpointing needed to minimize the losses. As supercomputers and their components simultaneously grow in scale, density, failure rates, and environmental footprint, the efficiency of HPC operations becomes both an imperative and a challenge. We examine DBEs using system telemetry data and logs collected from the Summit supercomputer, equipped with 27,648 Tesla V100 GPUs with 2nd-generation high-bandwidth memory (HBM2). Using exploratory data analysis and statistical learning, we extract several insights about memory reliability in such GPUs. We find that GPUs with prior DBE occurrences are prone to experience them again due to otherwise harmless factors, correlate this phenomenon with GPU placement, and suggest manufacturing variability as a factor. On the general population of GPUs, we link DBEs to short- and long-term high power consumption modes while finding no significant correlation with higher temperatures. We also show that the workload type can be a factor in memory’s propensity to corruption.
A portable electronic apparatus records electromyographic (EMG) signals in as many as 16 channels at a sampling rate of 1,024 Hz in each channel. The apparatus (see figure) includes 16 differential EMG electrodes (each electrode corresponding to one channel) with cables and attachment hardware, reference electrodes, an input/output-and-power-adapter unit, a 16-bit analog-to-digital converter, and a hand-held computer that contains a removable 256-MB flash memory card. When all 16 EMG electrodes are in use, full-bandwidth data can be recorded in each channel for as long as 8 hours. The apparatus is powered by a battery and is small enough that it can be carried in a waist pouch. The computer is equipped with a small screen that can be used to display the incoming signals on each channel. Amplitude and time adjustments of this display can be made easily by use of touch buttons on the screen. The user can also set up a data-acquisition schedule to conform to experimental protocols or to manage battery energy and memory efficiently. Once the EMG data have been recorded, the flash memory card is removed from the EMG apparatus and placed in a flash-memory- card-reading external drive unit connected to a personal computer (PC). The PC can then read the data recorded in the 16 channels. Preferably, before further analysis, the data should be stored in the hard drive of the PC. The data files are opened and viewed on the PC by use of special- purpose software. The software for operation of the apparatus resides in a random-access memory (RAM), with backup power supplied by a small internal lithium cell. A backup copy of this software resides on the flash memory card. In the event of loss of both main and backup battery power and consequent loss of this software, the backup copy can be used to restore the RAM copy after power has been restored. Accessories for this device are also available. These include goniometers, accelerometers, foot switches, and force gauges.
Spin-transparent storage rings, where any spin direction repeats after one full turn, can be used in conjunction with ion traps as a new quantum computing platform [1]. Advantages of spin-transparent rings for quantum computing include: large numbers of stored qubits; long quantum coherence times of up to several hours; long storage lifetimes; and room temperature operation. These exceptional qualities mean rings could provide a scalable way to implement algorithms with deep complexity requiring many quantum operations while simultaneously providing a large number of qubits. This new platform where the qubit has long quantum coherence time can also be used as a quantum sensor or a part of a quantum memory.
It is shown that slice or pencil-beam redshift surveys of galaxies can be simulated in a box with nonequal sides. This method saves a lot of computer time and memory while providing essentially the same results as from whole-cube simulations. A 2457.6/h Mpc-long rod (out to a redshift z = 0.58 in two opposite directions) is simulated using the standard biased cold dark matter model as an example to mimic the recent deep pencil-beam surveys by Broadhurst et al. (1990). The structures (spikes) seen in these simulated samples occur when the narrow pencil-beam pierces walls, filaments, and clusters appearing randomly along the line-of-sight. A statistical test for goodness of fit to a periodic lattice has been applied to the observations and the simulations. It is found that the statistical significance level (P = 15.4 percent) is not strong enough to reject the null hypothesis that the observations and the simulations were drawn at random from the same set.
When video replaces film the digitized video data accumulates very rapidly, leading to a difficult and costly data storage problem. One solution exists for cases when the video images represent continuously repetitive 'static scenes' containing negligible activity, occasionally interrupted by short events of interest. Minutes or hours of redundant video frames can be ignored, and not stored, until activity begins. A new, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term or short term changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pretrigger and post-trigger storage techniques are then adaptable for archiving the digital stream from only the significant video images.
We present views and analysis of the execution of several PVM codes for Computational Fluid Dynamics on a network of Sparcstations, including (a) NAS Parallel benchmarks CG and MG (White, Alund and Sunderam 1993); (b) a multi-partitioning algorithm for NAS Parallel Benchmark SP (Wijngaart 1993); and (c) an overset grid flowsolver (Smith 1993). These views and analysis were obtained using our Automated Instrumentation and Monitoring System (AIMS) version 3.0, a toolkit for debugging the performance of PVM programs. We will describe the architecture, operation and application of AIMS. The AIMS toolkit contains (a) Xinstrument, which can automatically instrument various computational and communication constructs in message-passing parallel programs; (b) Monitor, a library of run-time trace-collection routines; (c) VK (Visual Kernel), an execution-animation tool with source-code clickback; and (d) Tally, a tool for statistical analysis of execution profiles. Currently, Xinstrument can handle C and Fortran77 programs using PVM 3.2.x; Monitor has been implemented and tested on Sun 4 systems running SunOS 4.1.2; and VK uses X11R5 and Motif 1.2. Data and views obtained using AIMS clearly illustrate several characteristic features of executing parallel programs on networked workstations: (a) the impact of long message latencies; (b) the impact of multiprogramming overheads and associated load imbalance; (c) cache and virtual-memory effects; and (4significant skews between workstation clocks. Interestingly, AIMS can compensate for constant skew (zero drift) by calibrating the skew between a parent and its spawned children. In addition, AIMS' skew-compensation algorithm can adjust timestamps in a way that eliminates physically impossible communications (e.g., messages going backwards in time). Our current efforts are directed toward creating new views to explain the observed performance of PVM programs. Some of the features planned for the near future include: (a) ConfigView, showing the physical topology of the virtual machine, inferred using specially formatted IP (Internet Protocol) packets; and (b) LoadView, synchronous animation of PVM-program execution and resource-utilization patterns.
We present views and analysis of the execution of several PVM (Parallel Virtual Machine) codes for Computational Fluid Dynamics on a networks of Sparcstations, including: (1) NAS Parallel Benchmarks CG and MG; (2) a multi-partitioning algorithm for NAS Parallel Benchmark SP; and (3) an overset grid flowsolver. These views and analysis were obtained using our Automated Instrumentation and Monitoring System (AIMS) version 3.0, a toolkit for debugging the performance of PVM programs. We will describe the architecture, operation and application of AIMS. The AIMS toolkit contains: (1) Xinstrument, which can automatically instrument various computational and communication constructs in message-passing parallel programs; (2) Monitor, a library of runtime trace-collection routines; (3) VK (Visual Kernel), an execution-animation tool with source-code clickback; and (4) Tally, a tool for statistical analysis of execution profiles. Currently, Xinstrument can handle C and Fortran 77 programs using PVM 3.2.x; Monitor has been implemented and tested on Sun 4 systems running SunOS 4.1.2; and VK uses XIIR5 and Motif 1.2. Data and views obtained using AIMS clearly illustrate several characteristic features of executing parallel programs on networked workstations: (1) the impact of long message latencies; (2) the impact of multiprogramming overheads and associated load imbalance; (3) cache and virtual-memory effects; and (4) significant skews between workstation clocks. Interestingly, AIMS can compensate for constant skew (zero drift) by calibrating the skew between a parent and its spawned children. In addition, AIMS' skew-compensation algorithm can adjust timestamps in a way that eliminates physically impossible communications (e.g., messages going backwards in time). Our current efforts are directed toward creating new views to explain the observed performance of PVM programs. Some of the features planned for the near future include: (1) ConfigView, showing the physical topology of the virtual machine, inferred using specially formatted IP (Internet Protocol) packets: and (2) LoadView, synchronous animation of PVM-program execution and resource-utilization patterns.
physical conformation changes when exposed to an external stimulus, such as a change in temperature. Such materials have a permanent shape, but can be reshaped above a critical temperature and fixed into a temporary shape when cooled under stress to below the critical temperature. When reheated above the critical temperature (Tc, also sometimes called the triggering or switching temperature), the materials revert to the permanent shape. The current innovation involves a chemically treated (sulfonated, carboxylated, phosphonated, or other polar function group), high-temperature, semicrystalline thermoplastic poly(ether ether ketone) (Tg .140 C, Tm = 340 C) mix containing organometallic complexes (Zn++, Li+, or other metal, ammonium, or phosphonium salts), or high-temperature ionic liquids (e.g. hexafluorosilicate salt with 1-propyl-3- methyl imidazolium, Tm = 210 C) to form a network where dipolar or ionic interactions between the polymer and the low-molecular-weight or inorganic compound forms a complex that provides a physical crosslink. Hereafter, these compounds will be referred to as "additives". The polymer is semicrystalline, and the high-melt-point crystals provide a temporary crosslink that acts as a permanent crosslink just so long as the melting temperature is not exceeded. In this example case, the melting point is .340 C, and the shape memory critical temperature is between 150 and 250 C. PEEK is an engineering thermoplastic with a high Young fs modulus, nominally 3.6 GPa. An important aspect of the invention is the control of the PEEK functionalization (in this example, the sulfonation degree), and the thermal properties (i.e. melting point) of the additive, which determines the switching temperature. Because the compound is thermoplastic, it can be formed into the "permanent" shape by conventional plastics processing operations. In addition, the compound may be covalently cross - linked after forming the permanent shape by S-PEEK by applying ionizing radiation ( radiation, neutrons), or by chemical crosslinking to form a covalent permanent network. With respect to other shape memory polymers, this invention is novel in that it describes the use of a thermoplastic composition that can be thermally molded or solution-cast into complex "permanent" shapes, and then reheated or redissolved and recast from solution to prepare another shape. It is also unique in that the shape memory behavior is provided by a non-polymer additive.
Computation in biological neural circuits arises from the interplay of nonlinear temporal responses and spatially distributed dynamic network interactions. Replicating this richness in hardware has remained challenging, as most neuromorphic devices emulate only isolated neuron- or synapse-like functions. Here we introduce an integrated neuromorphic computing platform in which both nonlinear spatiotemporal processing and programmable memory are realized within a single perovskite nickelate material system. By engineering symmetric and asymmetric hydrogenated NdNiO 3 junction devices on the same wafer, we combine ultrafast, proton-mediated transient dynamics with stable multilevel resistance states. Networks of symmetric NdNiO 3 junctions exhibit emergent spatial interactions mediated by proton redistribution, while each node simultaneously provides short-term temporal memory, enabling nanosecond-scale operation with an energy cost of ~0.2 nJ per input. When interfaced with asymmetric output units serving as reconfigurable long-term weights, these networks allow both feature transformation and linear classification in the same material system. Leveraging these emergent interactions, the platform enables real-time pattern recognition and achieves high accuracy in spoken digit classification and early seizure detection, outperforming temporal-only or uncoupled architectures. These results position protonic nickelates as a compact, energy-efficient, CMOS-compatible platform that integrates processing and memory for scalable intelligent hardware.
We propose a family of algorithms for solving numerically a Cauchy problem for the three-dimensional wave equation. The sources that drive the equation (i.e., the right-hand side) are compactly supported in space for any given time; they, however, may actually move in space with a subsonic speed. The solution is calculated inside a finite domain (e.g., sphere) that also moves with a subsonic speed and always contains the support of the right-hand side. The algorithms employ a standard consistent and stable explicit finite-difference scheme for the wave equation. They allow one to calculate tile solution for arbitrarily long time intervals without error accumulation and with the fixed non-growing amount of tile CPU time and memory required for advancing one time step. The algorithms are inherently three-dimensional; they rely on the presence of lacunae in the solutions of the wave equation in oddly dimensional spaces. The methodology presented in the paper is, in fact, a building block for constructing the nonlocal highly accurate unsteady artificial boundary conditions to be used for the numerical simulation of waves propagating with finite speed over unbounded domains.
This paper presents Single Event Effect (SEE) in-flight data on Solid State Recorders (SSR) that have been collected over a long period of time for two NASA spacecraft: Orbview-2 and XTE. SEE flight data on solid-state memories give an opportunity to study the behavior in space of SEE sensitive commercial devices. The actual Single Event Upset (SEU) rates can be compared with the calculated rates based on environment models and ground test data. The SEE mitigation schemes can also be evaluated in actual implementation. A significant amount of data has already been published concerning observed SEE effects on memories in space. However, most of the data presented cover either a short period of time or a small number of devices. The data presented here has been collected on a large number of devices during several years. This allows statistically significant information about the effect of space weather fluctuations on SEU rates, and the effectiveness of SEE countermeasures used to be analyzed. Only Orbview-2 data is presented in this summary. XTE data will be included in the final paper.
Biological memory is the ability to develop, retain, and retrieve information over time. Currently, it is widely accepted that memories are stored in synapses (i.e., connections between brain cells throughout the brain) through a process known as synaptic plasticity, which leads to either long-term potentiation (LTP) or long-term depression (LTD). However, the strengthening (LTP) and weakening (LTD) of synapses involve post-translational modifications to neural networks requiring de novo gene expression, a lengthy and energetically expensive process. Recently, we observed that lipid bilayers in the absence of peptides/proteins are capable of LTP, not unlike what has been observed in mammals and birds. As such, this finding has prompted us to postulate that the lipid bilayer provides a good model for understanding the molecular basis of biological memory. Here, in this article, we discuss the status, challenges, and opportunities of neuronal plasma membranes as structures for biological memory and learning, therapeutic targets for various brain disorders, and platforms for neural network developments.