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At least 775 records · Page 43

Jamming, fragility and pinning phenomena in superconducting vortex systems

Abstract We examine driven superconducting vortices interacting with quenched disorder under a sequence of perpendicular drive pulses. As a function of disorder strength, we find four types of behavior distinguished by the presence or absence of memory effects. The fragile and jammed states exhibit memory, while the elastic and pinning dominated regimes do not. In the fragile regime, the system organizes into a pinned state during the first pulse, flows during the second perpendicular pulse, and then returns to a pinned state during the third pulse which is parallel to the first pulse. This behavior is the hallmark of the fragility proposed for jamming in particulate matter. For stronger disorder, we observe a robust jamming state with memory where the system reaches a pinned or reduced flow state during the perpendicular drive pulse, similar to the shear jamming of granular systems. We show signatures of the different states in the spatial vortex configurations, and find that memory effects arise from coexisting elastic and pinned components of the vortex assembly. The sequential perpendicular driving protocol we propose for distinguishing fragile, jammed, and pinned phases should be general to the broader class of driven interacting particles in the presence of quenched disorder.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Coherently coupled quantum oscillators for quantum reservoir computing

Here, we analyze the properties of a quantum system composed of two coherently coupled quantum oscillators and show through simulations that it fulfills the two properties required for reservoir computing: non-linearity and fading memory. We first show that the basis states of this system apply a set of nonlinear transformations on the input signals and thus can implement neurons. We then show that the system exhibits a fading memory that can be controlled by its dissipation rates. Finally we show that a strong coupling between the oscillators is important in order to ensure complex dynamics and to populate a number of basis state neurons that is exponential in the number of physical devices.

Dudas, Julien↗

Feature Classification for Control System Devices

Control systems are used to automate industrial processes, smart grids, and smart cities. Unfortunately, cyber attacks on control systems are on the rise. Additionally, control systems lack the plethora of tools available for commodity systems for forensic investigation. An important step towards the proper forensic investigation is to analyze device memory. To assist in identifying features of device memory, we present a machine learning-based technique that integrates ontology information for feature classification in a control system device’s memory.

ahmed mithu, M Rayhan↗

Experimental evaluation of shape memory alloy actuation technique in adaptive antenna design concepts

Creation of an antenna system that could autonomously adapt contours of reflecting surfaces to compensate for structural loads induced by a variable environment would maximize performance of space-based communication systems. Design of such a system requires the comprehensive development and integration of advanced actuator, sensor, and control technologies. As an initial step in this process, a test has been performed to assess the use of a shape memory alloy as a potential actuation technique. For this test, an existing, offset, cassegrain antenna system was retrofit with a subreflector equipped with shape memory alloy actuators for surface contour control. The impacts that the actuators had on both the subreflector contour and the antenna system patterns were measured. The results of this study indicate the potential for using shape memory alloy actuation techniques to adaptively control antenna performance; both variations in gain and beam steering capabilities were demonstrated. Future development effort is required to evolve this potential into a useful technology for satellite applications.

Kefauver, W. Neill↗

Effects of Palladium Content, Quaternary Alloying, and Thermomechanical Processing on the Behavior of Ni-Ti-Pd Shape Memory Alloys for Actuator Applications

The need for compact, solid-state actuation systems for use in the aerospace, automotive, and other transportation industries is currently driving research in high-temperature shape memory alloys (HTSMA) having transformation temperatures above 100 C. One of the basic high temperature systems under investigation to fill this need is NiTiPd. Prior work on this alloy system has focused on phase transformations and respective temperatures, no-load shape memory behavior (strain recovery), and tensile behavior for selected alloys. In addition, a few tests have been done to determine the effect of boron additions and thermomechanical treatment on the aforementioned properties. The main properties that affect the performance of a solid state actuator, namely work output, transformation strain, and permanent deformation during thermal cycling under load have mainly been neglected. There is also no consistent data representing the mechanical behavior of this alloy system over a broad range of compositions. For this thesis, ternary NiTiPd alloys containing 15 to 46 at.% palladium were processed and the transformation temperatures, basic tensile properties, and work characteristics determined. However, testing reveals that at higher levels of alloying addition, the benefit of increased transformation temperature begins to be offset by lowered work output and permanent deformation or "walking" of the alloy during thermal cycling under load. In response to this dilemma, NiTiPd alloys have been further alloyed with gold, platinum, and hafnium additions to solid solution strengthen the martensite and parent austenite phases in order to improve the thermomechanical behavior of these materials. The tensile properties, work behavior, and dimensional stability during repeated thermal cycling under load for the ternary and quaternary alloys were compared and discussed. In addition, the benefits of more advanced thermomechanical processing or training on the dimensional stability of these alloys during repeated actuation were investigated. Finally, the effect of quaternary alloying on the thermal stability of NiTiPdX alloys is determined via thermal cycling of the materials to increasing temperatures under load. It was found that solid solution additions of platinum and gold resulted in about a 30 C increase in upper use temperature compared to the baseline NiTiPd alloy, providing an added measure of over-temperature protection.

Bigelow, Glen↗

Advanced eLectrical Bus (ALBus) CubeSat: From Build to Flight

Advanced eLectrical Bus (ALBus) CubeSat is a technology demonstration mission of a 3-U CubeSat with an advanced digitally controlled electrical power system and novel use of Shape Memory Alloy (SMA) technology for reliable deployable solar array mechanisms. The primary objective was to advance the power management and distribution (PMAD) capabilities to enable future missions requiring more flexible and reliable power systems with higher output power capabilities. Goals included demonstration of 100W distribution to a target electrical load, response to continuous and fast transient power requirements, and exhibition of reliable deployment of solar arrays and antennas utilizing re-settable SMA mechanisms. The power distribution function of the ALBus PMAD system is unique in the total power to target load capability, as power is distributed from batteries to provide 100W of power directly to a resistive load. The deployable solar arrays utilize NASA’s Nickel-Titanium-Palladium-Platinum (NiTiPdPt) high-temperature SMAs for the retention and release mechanism, and a superelastic binary NiTi alloy for the hinge component. The project launched as part of the CubeSat Launch Initiative (CLI) Educational Launch of Nanosatellites (ELaNa) XIX mission on Rocket Lab’s Electron in December 2018. This paper summarizes the final launched design and the lessons learned from build to flight.

Deboshri Sadhukhan↗

Study Design to Test the Hypothesis That Long-Term Space Travel Harms the Human and Animal Immune Systems

The potential threat of immunosuppression and abnormal inflammatory responses in long-term space travel, leading to unusual predilection for opportunistic infections, malignancy, and death, is of ma or concern to the National Aeronautics and Space Administration (NASA) Program. This application has been devised to seek answers to questions of altered immunity in space travel raised by previous investigations spanning 30-plus years. We propose to do this with the help of knowledge gained by the discovery of the molecular basis of many primary and secondary immunodeficiency diseases and by application of molecular and genetic technology not previously available. Two areas of immunity that previously received little attention in space travel research will be emphasized: specific antibody responses and non-specific inflammation and adhesion. Both of these areas of research will not only add to the growing body of information on the potential effects of space travel on the immune system, but be able to delineate any functional alterations in systems important for antigen presentation, specific immune memory, and cell:cell and cell:endothelium interactions. By more precisely defining molecular dysfunction of components of the immune system, it is hoped that targeted methods of prevention of immune damage in space could be devised.

Shearer, William T.↗

Redirecting data to improve page locality in a scalable data fabric

A data processing system includes a host processor, a local memory coupled to the host processor, a plurality of remote memory media, and a scalable data fabric coupled to the host processor and to the plurality of remote memory media. The scalable data fabric includes a filter for storing information indicating a location of data that is stored by the data processing system. The host processor includes a hardware sequencer coupled to the filter for selectively moving data stored by the filter to the local memory.

97 MATHEMATICS AND COMPUTING↗

Precisely computing phonons via irreducible derivatives

Computing phonons from first principles is typically considered a solved problem, yet inadequacies in existing techniques continue to yield deficient results in systems with sensitive phonons. Here, in this study, we circumvent this issue using the lone irreducible derivative (LID) and bundled irreducible derivative (BID) approaches to computing phonons via finite displacements, where the former optimizes precision via energy derivatives and the latter provides the most efficient algorithm using force derivatives. A condition number optimized basis for BID is derived which guarantees the minimum amplification of error. Additionally, a hybrid LID-BID approach is formulated, in which select irreducible derivatives computed using LID replace BID results. We illustrate our approach on two prototypical systems with sensitive phonons: the shape memory alloy AuZn and metallic lithium. Comparing our resulting phonons in the aforementioned crystals to calculations in the literature reveals nontrivial inaccuracies. Our approaches can be fully automated, making them well suited for both niche systems of interest and high-throughput approaches.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Toward Performance Portable Programming for Heterogeneous System-on-Chips: Case Study with Qualcomm Snapdragon SoC

Future heterogeneous Domain-Specific System-on-Chips (DSSoC) will be extraordinarily complex in terms of processors, memory hierarchies, and interconnection networks.To manage this complexity, architects, system software designers, and application developers need programming technologies that are flexible, accurate, efficient, and productive. These technologies will need to be as independent of any one specific architecture as is practical, because the sheer dimensionality and scale of the complexity will not allow porting and optimizing applications foreach given DSSoC. To address these issues, we are developing Cosmic Castle, a performance portable programming toolchain for streaming applications on heterogeneous architectures. The primary focus of Cosmic Castle is on enabling efficient and performant code generation through the smart compiler and intelligent runtime system. This paper presents the preliminary evaluation of our ongoing work toward Cosmic Castle. Specifically, we detail our code porting efforts and evaluate various benchmarks on the Qualcomm Snapdragon SoC using tools developed through Cosmic Castle.

Cabrera, Anthony↗

Cycle accurate and cycle reproducible memory for an FPGA based hardware accelerator

A method, system and computer program product are disclosed for using a Field Programmable Gate Array (FPGA) to simulate operations of a device under test (DUT). The DUT includes a device memory having a number of input ports, and the FPGA is associated with a target memory having a second number of input ports, the second number being less than the first number. In one embodiment, a given set of inputs is applied to the device memory at a frequency Fd and in a defined cycle of time, and the given set of inputs is applied to the target memory at a frequency Ft. Ft is greater than Fd and cycle accuracy is maintained between the device memory and the target memory. In an embodiment, a cycle accurate model of the DUT memory is created by separating the DUT memory interface protocol from the target memory storage array.

Asaad, Sameh W.↗

Cricket: A Mapped, Persistent Object Store

This paper describes Cricket, a new database storage system that is intended to be used as a platform for design environments and persistent programming languages. Cricket uses the memory management primitives of the Mach operating system to provide the abstraction of a shared, transactional single-level store that can be directly accessed by user applications. In this paper, we present the design and motivation for Cricket. We also present some initial performance results which show that, for its intended applications, Cricket can provide better performance than a general-purpose database storage system.

Shekita, Eugene↗

Generative memory for lifelong machine learning

Techniques are disclosed for training machine learning systems. An input device receives training data comprising pairs of training inputs and training labels. A generative memory assigns training inputs to each archetype task of a plurality of archetype tasks, each archetype task representative of a cluster of related tasks within a task space and assigns a skill to each archetype task. The generative memory generates, from each archetype task, auxiliary data comprising pairs of auxiliary inputs and auxiliary labels. A machine learning system trains a machine learning model to apply a skill assigned to an archetype task to training and auxiliary inputs assigned to the archetype task to obtain output labels corresponding to the training and auxiliary labels associated with the training and auxiliary inputs assigned to the archetype task to enable scalable learning to obtain labels for new tasks for which the machine learning model has not previously been trained.

Nadamuni Raghavan, Aswin↗

Combustion control using spiking neural networks

A system that controls a combustion engine stores network vectors in a memory that represent diverse and distinct spiking neural networks. The system decodes the network vectors and trains and evaluates the spiking neural networks. The system duplicates selected network vectors and crosses-over the duplicated network vectors that represent modified spiking neural networks. The system mutates the crossed-over duplicated network vectors by randomly modifying one or more portions of the crossing-over duplicated network vectors. The system meter exhaust gas into an intake manifold when an engine temperature exceeds a threshold, an engine load exceeds a threshold, an engine's rotation-per-minute rate exceeds a threshold, and a fuel flow exceeds a threshold. The system modifies fuel flow into an engine's combustion chamber on a cycle-to-cycle basis by the trained spiking neural network.

Puente, Brian P. Maldonado↗

Sparse Approximate Multifrontal Factorization with Composite Compression Methods

This article presents a fast and approximate multifrontal solver for large sparse linear systems. In a recent work by Liu et al., we showed the efficiency of a multifrontal solver leveraging the butterfly algorithm and its hierarchical matrix extension, HODBF (hierarchical off-diagonal butterfly) compression to compress large frontal matrices. The resulting multifrontal solver can attain quasi-linear computation and memory complexity when applied to sparse linear systems arising from spatial discretization of high-frequency wave equations. To further reduce the overall number of operations and especially the factorization memory usage to scale to larger problem sizes, in this article we develop a composite multifrontal solver that employs the HODBF format for large-sized fronts, a reduced-memory version of the nonhierarchical block low-rank format for medium-sized fronts, and a lossy compression format for small-sized fronts. This allows us to solve sparse linear systems of dimension up to 2.7 × larger than before and leads to a memory consumption that is reduced by 70% while ensuring the same execution time. The code is made publicly available in GitHub.

97 MATHEMATICS AND COMPUTING↗

Study of interconnect errors, network congestion, and applications characteristics for throttle prediction on a large scale HPC system

Today’s High Performance Computing (HPC) systems contain thousand of nodes which work together to provide performance in the order of petaflops. The performance of these systems depends on various components like processors, memory, and interconnect. Among all, interconnect plays a major role as it glues together all the hardware components in an HPC system. A slow interconnect can impact a scientific application running on multiple processes severely as they rely on fast network messages to communicate and synchronize frequently. Unfortunately, the HPC community lacks a study that explores different interconnect errors, congestion events and applications characteristics on a large-scale HPC system. In our previous work, we process and analyze interconnect data of the Titan supercomputer to develop a thorough understanding of interconnects faults, errors, and congestion events. In this work, we first show how congestion events can impact application performance. We then investigate application characteristics interaction with interconnect errors and network congestion to predict applications encountering congestion with more than 90% accuracy.

97 MATHEMATICS AND COMPUTING↗