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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 379 records · Page 21

Data-Intensive Memory-Map simulator and runtime

DI-MMAP is a simulator for modeling the performance of next generation non-volatile random access memory technologies (NVRAM) and a high-perfromance memory-map runtime for the Linux operating system. It is implemented as a device driver for the Linux operating system. It will be used by algorithm designers to unserstand the impact of future NVRAM on their algorithms and will be used by application developers for high-performance access to NVRAM storage.

Essen, B.B.↗

Livermore Random I/O Testbench

LRIOT is a test bench framework that is designed to generate sophisticated I/O rates that can stress high-performance memory and storage systems, such as non-volatile random access memories (NVRAM)and storage class memory. Furthermore, LRIOT provides the capabilities to mix multiple types of concurrency, namely threading and task parallelism, as well as distributed execution using Message Passing Interface (MPI) libraries. It will be used by algorithm designers to generate access patterns that mimic their application's behavior, and by system designers to test high-performance NVRAM storage.

Source record↗

Livermore Random I/O Testbench

LRIOT is a test bench framework that is designed to generate sophisticated I/O rates that can stress high-performance memory and storage systems, such as non-volatile random access memories (NVRAM)and storage class memory. Furthermore, LRIOT provides the capabilities to mix multiple types of concurrency, namely threading and task parallelism, as well as distributed execution using Message Passing Interface (MPI) libraries. It will be used by algorithm designers to generate access patterns that mimic their application's behavior, and by system designers to test high-performance NVRAM storage.

Van Essen, Brian↗

Exascale Programming Approaches for Accelerated Climate Modeling for Energy

The Accelerated Climate Modeling for Energy (ACME) program is a leading-edge climate and Earth system model designed to address the U.S. Department of Energy (DOE) mission needs. The ACME project involves collaboration between seven National Laboratories, the National Center for Atmospheric Research, four academic institutions, and one private-sector company. The ACME project funds ongoing efforts to ensure the model continues to make efficient use of DOE Leadership Computing Facilities (LCFs) in order to best address the three driving grand challenge science questions:Water cycle: How will more realistic portrayals of features important to the water cycle (resolution, clouds, aerosols, snowpack, river routing, land use) affect river flow and associated freshwater supplies at the watershed scale?Cryosphere systems: Could a dynamical instability in the Antarctic ice sheet be triggered within the next 40 years?Biogeochemistry: What are the contributions and feedbacks from natural and managed systems to current greenhouse gas fluxes, and how will those factors and associated fluxes evolve in the future?

Norman, Matthew↗

Evaluation of the Leon3 Soft-Core Processor Within a Xilinx Radiation-Hardened Field-Programmable Gate Array

The purpose of this document is to summarize the work done to evaluate the performance of the Leon3 soft-core processor in a radiation environment while instantiated in a radiation-hardened static random-access memory based field-programmable gate array. This evaluation will look at the differences between two soft-core processors: the open-source Leon3 core and the fault-tolerant Leon3 core. Radiation testing of these two cores was conducted at the Texas A&M University Cyclotron facility and Lawrence Berkeley National Laboratory. The results of these tests are included within the report along with designs intended to improve the mitigation of the open-source Leon3. The test setup used for evaluating both versions of the Leon3 is also included within this document.

97 MATHEMATICS AND COMPUTING↗

Spin-Torque in Systems with Inhomogeneous Magnetization

The work performed during the grant period focused on the phenomenon of spin-transfer torque. This is a quantum mechanical effect whereby the angular momentum of conduction electrons is transferred to the magnetization of ferromagnetic structures. Our work on this subject began with phenomenological drift-diffusion and Landau-Lifshitz-Gilbert equations to demonstrate unambiguously that unpolarized current flow from a nonmagnet into a ferromagnet can produce a precession-type instability of the magnetization. We then used Boltzmann calculations appropriate to spin-valve type magnetic heterostructures composed of a non-magnetic thin film sandwiched between two thin film layers with uniform magnetization. Perhaps our most important paper dealt with quantum and semi-classical calculations of spin-transfer torque in systems with domain walls and other inhomogeneous distributions of magnetization. The latter work caused us to suggest that the Landau-Lifshitz approach to magnetic damping provided a clearer picture of the physics than the more popular (but formally equivalent) Gilbert approach to damping. Finally, we returned to our Boltzmann calculations and made a serious effort to analyze experimental data on current-induced magnetization in switching in magnetic spin-valve structures. Our work was part of a world-wide effort to study and harness the transport of the electron's spin and was one of the first sustained theoretical efforts in this direction in the United States. The payoff is just now being seen. In November of 2012, the Everspin Corporation announced the release of the first commercial spin-torque magnetoresistive random access memory.

36 MATERIALS SCIENCE↗

On-line vs. Off-line Coupling of Meteorological and Transport & Dispersion Models: Background, Advantages, Limitations, and Issues

This report discusses the advantages and limitations of on-line coupling of meteorological (Met) or computational fluid dynamics (CFD) codes with transport and dispersion (T&D) models for the simulation of chemical, biological, radiological, and nuclear (CBRN) plume dispersion at the meso- and urban-scales as compared to the more standard off-line coupling approach. In an off-line modeling system the Met/CFD and T&D codes are separate executables, the Met/CFD code is first run to completion, output files are written to hard disk, and then the T&D model reads in the Met/CFD files and is run to completion. An on-line modeling system is defined as having the T&D and Met/CFD codes running concurrently, sharing input and output between the models via computer random access memory (RAM) and in many cases the Met/CFD and T&D models are embedded in the same code.

54 ENVIRONMENTAL SCIENCES↗

Battery Monitoring System

The component that is powered by the battery pack being monitored is a valuable asset and must be in working condition at all times. Battery chemistry and characteristics have a major role in how to evaluate the state of the battery. The battery monitoring system has many parts that lead to an accurate battery reading. The components consist of a coulomb counting device, end of life voltage detection, a consideration of use for a real-time clock (RTC), temperature sensor, and non-volatile random-access memory (NVRAM). The combination of these elements allows the monitoring system to be highly reliant. Moving forward a better implementation of the ideas in this paper and further testing should ensure a high-quality battery monitoring system.

25 ENERGY STORAGE↗

Nanosecond Gated CMOS Camera (NSGCC) ICD (Rev. 2.1)

The Ultra-Fast X-ray Imager (UXI) program is an ongoing effort at Sandia National Laboratories to create high speed, multi-frame, time-gated Read Out Integrated Circuits (ROICs), and a corresponding suite of photodetectors to image a wide variety of High Energy Density (HED) physics experiments on both Sandia’s Z-Machine and LLNL’s National Ignition Facility (NIF). Several cameras have been designed over the length of the program; one of the most recent is the Icarus, which is an improvement on past imagers (Furi and Hippogriff). A second sensor that can be connected is the Daedalus sensor. The Icarus is a 1024 × 512-pixel array with either 25 μm or 8 µm spatial resolution containing four frames of storage per pixel and has improved timing generation and distribution components while achieved 2 ns time gating. The Daedalus sensor is also a 1024 x 512-pixel array with 25 µm special resolution containing three frames of storage per pixel and has an increased set of features for a wider variety of applications from interlacing of rows in each frame to configurability of all shutters. See Section 14 for details regarding the Icarus implementation of the firmware and Section 15 for details regarding the Daedalus implementation. Due to the unique test environments UXI sensors are targeted for, full custom hardware was required to physically mount an Icarus or Daedalus sensor, manage its various functions, and read out pixel data for transfer to a host computer. Beyond experimental functionality, the hardware also needed to accommodate sensor characterization requirements. Lawrence Livermore National Laboratory’s ‘Version 4.0 Board’ was the result of these efforts. It mounts all the components required to fully utilize the Icarus and Daedalus sensors including analog to digital converters to convert pixel data and various system voltages to digital form for readout and analysis, DAC channels for remote configuration of critical bias voltages, static random-access memories to buffer pixel data, RS422 and Gigabit Ethernet communications for remote access, and an FPGA to tie these components together. This document describes the FPGA electrical interfaces in detail to allow the reader a greater understanding of the device, and to facilitate implementation of custom software to control and manage it. The Version 4.0 Board is a continuation of the Nano-second Gated CMOS hardware design that retains much of the functionality of the Version 1.0 Board while adding features including a DAC instead of digital potentiometers, as well as sensors for pressure and radiation. The Version 4.0 board is intended for applications requiring tight form-factor enclosures. It is composed of two stacking boards; one holds the FPGA and regulators to power the various components of the board while the other contains the mating connector to the sensor, image-readoff ADCs, the DAC, and other components.

42 ENGINEERING↗

Computing Sparse Tensor Decompositions via Chapel and C++/MPI Interoperability without Intermediate I/O

We extend an existing approach for efficient use of shared mapped memory across Chapel and C++ for graph data stored as 1-D arrays to sparse tensor data stored using a combination of 2-D and 1-D arrays. We describe the specific extensions that provide use of shared mapped memory tensor data for a particular C++ tensor decomposition tool called GentenMPI. We then demonstrate our approach on several real-world datasets, providing timing results that illustrate minimal overhead incurred using this approach. Finally, we extend our work to improve memory usage and provide convenient random access to sparse shared mapped memory tensor elements in Chapel, while still being capable of leveraging high performance implementations of tensor algorithms in C++.

97 MATHEMATICS AND COMPUTING↗

Controlling reversible phase transitions in rare-earth nickelates for novel memory devices

Resistive switching in correlated complex oxides is lucrative for emerging applications in neuromorphic computing, and densely scaled non-volatile memory. Electrical conductance of such complex oxides can be controllable switched across multiple orders of magnitude by either (a) electroforming a conduction channel (e.g., in tungsten oxide), or (b) inducing Mott-Hubbard transition (e.g., in rare-earth nickelates)– both via controlled migration of defects (such as oxygen vacancies) under applied bias. Nevertheless, the promise of such defect-driven electronic transitions are far from realized due to a lack of fundamental understanding of the atomic-scale processes that underlie migration and spatiotemporal evolution of oxygen vacancies over nano-to-mesoscopic length/timescales under applied electric field. In this project, we employ a synergistic integration of density functional theory (DFT) calculations, ab initio/classical molecular dynamics (AIMD/CMD) simulations, machine learning (ML), precision synthesis, and multi-modal X-ray imaging experiments to address this knowledge gap. Such an integrated approach offers to elucidate the correlations between subtle structural distortion and oxidation states; treat localized charge carriers; describe defect/ion transport in the presence of electric field; and, in turn, greatly advance the current understanding of microstructural evolution in complex oxides under applied bias. The fundamental knowledge gained from this work will enable precise control over hierarchical defect structures and unravel new routes to manipulate resistance states in complex oxides. This, in turn, will accelerate design of novel devices with desired set of neural functionalities, and high-speed densely-scaled resistive random access memory technologies.

36 MATERIALS SCIENCE↗

Prediction of Alpha-Particle-Immune Gate-All-Around Field-Effect Transistors (GAA-FET) Based SRAM Design

Alpha particles are known to be a major source of particles creating soft errors in semiconductor devices, such as content flipping in Static Random-Access Memory (SRAM). Recent advancements in transistor nodes have led to the introduction of Gate-All-Around Field Effect Transistors (GAA-FETs), which have better gate control, thus better electrostatics. Moreover, the introduction of bottom dielectric isolation (BDI) eliminates substrate leakage and thus is expected to enhance its radiation hardness. It is thus important to explore if one can design an SRAM that is completely radiation-hard to alpha particles. In this paper, using 3D Technology Computer-Aided-Design (TCAD) simulations, we show that it is possible to design an SRAM using GAA-FET technology so that it is immune to single alpha particle radiation error. In other words, with the design, there will be no single-event upset (SEU) due to alpha particles. We first use ab initio calculations in PHITS to show that there is a maximum linear energy transfer (LET), LET max , for the alpha particle in Si and Si x Ge 1-x . Based on that, by de signing a sub-7nm GAA-FET-based SRAM with BDI, we show that the SRAM does not flip even if the particle strike is in the worst-case scenario for LET > LET max .

42 ENGINEERING↗

Characterization of ECRAM materials and devices

As the limits of Moore’s Law approaches, new computing paradigms are developing to breakthrough this bottleneck. One such computer architecture is neuromorphic computing, which models the brain. Electrochemical random-access memory (ECRAM) is a low power and energy efficient memory due to characteristics, such as in-memory compute, ion modulation of the channel conductance, and computation distribution with large scale array integration.

97 MATHEMATICS AND COMPUTING↗

The Evolution of Volatile Memory Forensics

The collection and analysis of volatile memory is a vibrant area of research in the cybersecurity community. The ever-evolving and growing threat landscape is trending towards fileless malware, which avoids traditional detection but can be found by examining a system’s random access memory (RAM). Additionally, volatile memory analysis offers great insight into other malicious vectors. It contains fragments of encrypted files’ contents, as well as lists of running processes, imported modules, and network connections, all of which are difficult or impossible to extract from the file system. For these compelling reasons, recent research efforts have focused on the collection of memory snapshots and methods to analyze them for the presence of malware. However, to the best of our knowledge, no current reviews or surveys exist that systematize the research on both memory acquisition and analysis. We fill that gap with this novel survey by exploring the state-of-the-art tools and techniques for volatile memory acquisition and analysis for malware identification. For memory acquisition methods, we explore the trade-offs many techniques make between snapshot quality, performance overhead, and security. For memory analysis, we examined the traditional forensic methods used, including signature-based methods, dynamic methods performed in a sandbox environment, as well as machine learning-based approaches. We summarize the currently available tools, and suggest areas for more research.

Nyholm, Hannah↗

Femtosecond Laser-Induced Nano-Joining of Volatile Tellurium Nanotube Memristor

Nanowire/nanotube memristor devices provide great potential for random-access high-density resistance storage. However, fabricating high-quality and stable memristors is still challenging. This paper reports multileveled resistance states of tellurium (Te) nanotube based on the clean-room free femtosecond laser nano-joining method. The temperature for the entire fabrication process was maintained below 190 °C. A femtosecond laser joining technique was used to form nanowire memristor units with enhanced properties. Femtosecond (fs) laser-irradiated silver-tellurium nanotube-silver structures resulted in plasmonic-enhanced optical joining with minimal local thermal effects. This produced a junction between the Te nanotube and the silver film substrate with enhanced electrical contacts. Noticeable changes in memristor behavior were observed after fs laser irradiation. Capacitor-coupled multilevel memristor behavior was observed. Compared to previous metal oxide nanowire-based memristors, the reported Te nanotube memristor system displayed a nearly two-order stronger current response. The research displays that the multileveled resistance state is rewritable with a negative bias.

42 ENGINEERING↗

Effects of Interface Induced Natural Strains on Magnetic Properties of FeRh

FeRh is a unique alloy which shows temperature dependent phase transition magnetic properties. The lattice parameter (a) of this CsCl-type (B2) structure is 4.1712 Å. It undergoes a first order transition from antiferromagnetic (AFM) to ferromagnetic (FM) order at around 370K and hysteretic behavior while cooling and heating. This meta-magnetic transition of FeRh is accompanied by an isotropic expansion in the unit cell volume, which indicates strong coupling between magnetic and structural properties of FeRh. Consequently, the magnetic and transport properties, such as magnetoresistance (MR), are changed during the transition. Due to its unique thermo-magnetic behaviors, FeRh is very important for future spintronic devices. The structure could be applicable for MR devices such as memory, sensors, and many other applications. It is critical to understand how to systematically influence phase transition of FeRh from naturally applied strains. Here, we investigate magnetic properties of FeRh in different strain environments induced by the substrates with different lattice parameters. The study was performed using synchrotron radiation, temperature dependent magnetometry, and magnetic scanning probe microscopy in addition to Landau theory calculations. We found that the naturally induced strains could modulate the magnetic phase locally and globally. The presence of the segments from the nucleation of the ferromagnetic domains, with a very thin layer in the antiferromagnetic matrix and the domain growth, were observed gradually. Using the systematic phenomena, it could be used for immediate applications in the future generation of phase change random access memory (PC-RAM) devices.

36 MATERIALS SCIENCE↗