Results for “Memory cell” — Page 13

NASA NTRS1985

Advances in rechargeable lithium molybdenum disulfide batteries

The lithium molybdenum disulfide system as demonstrated in a C size cell, offers performance characteristics for applications where light weight and low volume are important. A gravimetric energy density of 90 watt hours per kilogram can be achieved in a C size cell package. The combination of charge retention capabilities, high energy density and a state of charge indicator in a rechargeable cell provides power package for a wide range of devices. The system overcomes the memory effect in Nicads where the full capacity of the battery cannot be utilized unless it was utilized on previous cycles. The development of cells with an advanced electrolyte formulation led to an improved rate capability especially at low temperatures and to a significantly improved life cycle.

Brandt, K.↗

NASA NTRS1995

Implementation and Characterization of Three-Dimensional Particle-in-Cell Codes on Multiple-Instruction-Multiple-Data Massively Parallel Supercomputers

A three-dimensional electrostatic particle-in-cell (PIC) plasma simulation code has been developed on coarse-grain distributed-memory massively parallel computers with message passing communications. Our implementation is the generalization to three-dimensions of the general concurrent particle-in-cell (GCPIC) algorithm. In the GCPIC algorithm, the particle computation is divided among the processors using a domain decomposition of the simulation domain. In a three-dimensional simulation, the domain can be partitioned into one-, two-, or three-dimensional subdomains ("slabs," "rods," or "cubes") and we investigate the efficiency of the parallel implementation of the push for all three choices. The present implementation runs on the Intel Touchstone Delta machine at Caltech; a multiple-instruction-multiple-data (MIMD) parallel computer with 512 nodes. We find that the parallel efficiency of the push is very high, with the ratio of communication to computation time in the range 0.3%-10.0%. The highest efficiency (> 99%) occurs for a large, scaled problem with 64(sup 3) particles per processing node (approximately 134 million particles of 512 nodes) which has a push time of about 250 ns per particle per time step. We have also developed expressions for the timing of the code which are a function of both code parameters (number of grid points, particles, etc.) and machine-dependent parameters (effective FLOP rate, and the effective interprocessor bandwidths for the communication of particles and grid points). These expressions can be used to estimate the performance of scaled problems--including those with inhomogeneous plasmas--to other parallel machines once the machine-dependent parameters are known.

Lyster, P. M.↗

NASA NTRS1992

Content addressable memory project

A parameterized version of the tree processor was designed and tested (by simulation). The leaf processor design is 90 percent complete. We expect to complete and test a combination of tree and leaf cell designs in the next period. Work is proceeding on algorithms for the computer aided manufacturing (CAM), and once the design is complete we will begin simulating algorithms for large problems. The following topics are covered: (1) the practical implementation of content addressable memory; (2) design of a LEAF cell for the Rutgers CAM architecture; (3) a circuit design tool user's manual; and (4) design and analysis of efficient hierarchical interconnection networks.

Hall, J. Storrs↗

NASA NTRSDate not supplied

Passive fuel-Cell Surface power System (PaCeSS)

This effort produces a fully-passive surface power generation capability for fuel cell technology. The concept replaces the actively pumped thermal management of a state of the art (SOA) fuel cell/electrolyzer stack with a passive 2-phase thermosyphon for heat transport and a passive shape memory actuating radiator for temperature management.

Fuel Cell↗

DOE OSTI2021

Localized strain profile in surface electrode array for programmable composite multiferroic devices

In this work, we investigate localized in-plane strains on the microscale, induced by arrays of biased surface electrodes patterned on piezoelectrics. Particular focus is given to the influence that adjacent electrode pairs have on one another to study the impact of densely packed electrode arrays. We present a series of X-ray microdiffraction studies to reveal the spatially resolved micrometer-scale strain distribution. The strain maps with micrometer-scale resolution highlight how the local strain profile in square regions up to 250 x 250 lm 2 in size is affected by the surface electrodes that are patterned on ferroelectric single-crystal [Pb(Mg 1/3 Nb 2/3 )O 3 ] x -[PbTiO 3 ] 1-x . The experimental measurements and simulation results show the influence of electrode pair distance, positioning of the electrode pair, including the angle of placement, and neighboring electrode pair arrangements on the strength and direction of the regional strain. Our findings are relevant to the development of microarchitected strain-mediated multiferroic devices. The electrode arrays could provide array-addressable localized strain control for applications including straintronic memory, probabilistic computing platforms, microwave devices, and magnetic-activated cell sorting platforms.

42 ENGINEERING↗

DOE OSTI2023

A Fast Butterfly-Compressed Hadamard–Babich Integrator for High-Frequency Helmholtz Equations in Inhomogeneous Media with Arbitrary Sources

Here we present a butterfly-compressed representation of the Hadamard-Babich (HB) ansatz for the Green's function of the high-frequency Helmholtz equation in smooth inhomogeneous media. For a computational domain discretized with Nv discretization cells, the proposed algorithm first solves and tabulates the phase and HB coefficients via eikonal and transport equations with observation points and point sources located at the Chebyshev nodes using a set of much coarser computation grids, and then butterfly compresses the resulting HB interactions from all Nv cell centers to each other. The overall CPU time and memory requirement scale as O(Nv log2 Nv) for any bounded two-dimensional (2D) domains with arbitrary excitation sources. A direct extension of this scheme to bounded 3D domains yields an O(Nv4/3) CPU complexity, which can be further reduced to quasi-linear complexities with proposed remedies. The scheme can also efficiently handle scattering problems involving inclusions in inhomogeneous media. Although the current construction of our HB integrator does not accommodate caustics, the resulting HB integrator itself can be applied to certain sources, such as concave-shaped sources, to produce caustic effects. Compared to finite-difference frequency domain methods, the proposed HB integrator is free of numerical dispersion and requires fewer discretization points per wavelength. As a result, it can solve wave propagation problems well beyond the capability of existing solvers. Remarkably, the proposed scheme can accurately model wave propagation in 2D domains with 640 wavelengths per direction and in 3D domains with 54 wavelengths per direction on a state-of-the-art supercomputer at Lawrence Berkeley National Laboratory.

Hadamard--Babich ansatz↗

NASA NTRS1969

An integrated nonvolatile read-write memory with addressing.

Integrated nonvolatile read-write memory with addressing using variable threshold field effect transistor including cell operation, channel shielding and circuit

Koig, M. B.↗

NASA NTRS2010

Flash Memory Reliability: Read, Program, and Erase Latency Versus Endurance Cycling

This report documents the efforts and results of the fiscal year (FY) 2010 NASA Electronic Parts and Packaging Program (NEPP) task for nonvolatile memory (NVM) reliability. This year's focus was to measure latency (read, program, and erase) of NAND Flash memories and determine how these parameters drift with erase/program/read endurance cycling.

latency↗

NASA NTRSDate not supplied

Edge-Based Viscous Method for Mixed-Element Node-Centered Finite-Volume Solvers

A novel, efficient, edge-based viscous (EBV) discretization method has been recently developed, implemented in a practical, unstructured-grid, node-centered, finite-volume flow solver, and applied to viscous-kernel computations that include evaluations of meanflow viscous fluxes, turbulence-model and chemistry-model diffusion terms, and the corresponding Jacobian contributions. Initially, the EBV method had been implemented for tetrahedral grids and demonstrated multifold acceleration of all viscous-kernel computations. This paper presents an extension of the EBV method for mixed-element grids. In addition to the primal edges of a given mixed-element grid, virtual edges are introduced to connect cell nodes that are not connected by a primal edge. The EBV method uses an efficient loop over all (primal and virtual) edges and features a compact discretization stencil based on the nearest neighbors. This study verifies the EBV method and assesses its efficiency on mixed-element grids by comparing the EBV solution accuracy and iterative convergence with those of well-established solutions obtained using a cell-based viscous (CBV) discretization method. The EBV solver’s memory footprint is optimized and often smaller than the memory footprint of the CBV solver. A multifold speedup is demonstrated for all viscous-kernel computations resulting in significant reduction of the time to solutions for several benchmark mixed-element-grid computations, including simulations of a flow around NASA’s juncture-flow model and a hypersonic, chemically reacting flow around a blunt body.

CFD↗

NASA NTRSDate not supplied

Edge-Based Viscous Method for Mixed-Element Node-Centered Finite-Volume Solvers

A novel, efficient, edge-based viscous (EBV) discretization method has been recently developed, implemented in a practical, unstructured-grid, node-centered, finite-volume flow solver, and applied to viscous-kernel computations that include evaluations of meanflow viscous fluxes, turbulence-model and chemistry-model diffusion terms, and the corresponding Jacobian contributions. Initially, the EBV method had been implemented for tetrahedral grids and demonstrated multifold acceleration of all viscous-kernel computations. This paper presents an extension of the EBV method for mixed-element grids. In addition to the primal edges of a given mixed-element grid, virtual edges are introduced to connect cell nodes that are not connected by a primal edge. The EBV method uses an efficient loop over all (primal and virtual) edges and features a compact discretization stencil based on the nearest neighbors. This study verifies the EBV method and assesses its efficiency on mixed-element grids by comparing the EBV solution accuracy and iterative convergence with those of well-established solutions obtained using a cell-based viscous (CBV) discretization method. The EBV solver’s memory footprint is optimized and often smaller than the memory footprint of the CBV solver. A multifold speedup is demonstrated for all viscous-kernel computations resulting in significant reduction of the time to solutions for several benchmark mixed-element-grid computations, including simulations of a flow around NASA’s juncture-flow model and a hypersonic, chemically reacting flow around a blunt body.

Edge-based viscous method↗

NASA NTRS1973

The 1973 GSFC battery workshop, second day

Technological progress in the development, testing, and manufacturing of nickel-cadmium battery cells as well as hydrogen cells is presented. The following major topics were discussed: (1) carbonate analysis; (2) nickel-cadmium memory effect; (3) use of batteries in an automatic acquisition and control system; (4) accelerated testing; (5) formulation of a mathematical odel for a nickel-cadmium cell; (6) development of a light weight nickel-cadmium battery capable of delivering 20 watt hours per pound; (7) magnetic testing of nickel-cadmium cells; (8) design and performance characteristics of nickel-hydrogen and silver-hydrogen cells; and (9) development of a semiprismatic cell design. For Vol. 1, see N75-15152.

Source record↗

DOE OSTI2026

The Memory Scaling of Reverse-Mode Differentiation in Particle Accelerator Simulations with Space Charge

The recent development of differentiable simulation codes for particle accelerators has enabled gradient-based workflows that promise finer control and more realistic modeling of accelerator facilities. However, when using reverse-mode automatic differentiation, the memory usage continuously increases during the simulation, and can potentially exceed the available hardware memory - especially when costly space charge computation is included. To study the memory requirements for differentiable simulations, we have implemented space charge in Cheetah, a PyTorch-based beam tracking code that supports reverse-mode differentiation. We find that the memory usage for reverse-mode differentiation grows linearly with the number of macroparticles and cells, and that it is proportional to the number of space charge kicks involved in the simulation. This general scaling can be used to evaluate whether a given differentiable simulation is feasible given hardware memory constraints.

Dhamrait, Arjun↗

NASA NTRS2012

Non Volatile Flash Memory Radiation Tests

Commercial flash memory industry has experienced a fast growth in the recent years, because of their wide spread usage in cell phones, mp3 players and digital cameras. On the other hand, there has been increased interest in the use of high density commercial nonvolatile flash memories in space because of ever increasing data requirements and strict power requirements. Because of flash memories complex structure; they cannot be treated as just simple memories in regards to testing and analysis. It becomes quite challenging to determine how they will respond in radiation environments.

single event upset results↗

NASA NTRS1992

A DRAM compiler algorithm for high performance VLSI embedded memories

In many applications, the limited density of the embedded SRAM does not allow integrating the memory on the same chip with other logic and functional blocks. In such cases, the embedded DRAM provides the optimum combination of very high density, low power, and high performance. For ASIC's to take full advantage of this design strategy, an efficient and highly reliable DRAM compiler must be used. The embedded DRAM architecture, cell, and peripheral circuit design considerations and the algorithm of a high performance memory compiler are presented .

Eldin, A. G.↗

NASA NTRS2012

Radiation Tests of Highly Scaled, High-Density, Commercial, Nonvolatile NAND Flash Memories - Update 2012

The space radiation environment poses a certain risk to all electronic components on Earth-orbiting and planetary mission spacecraft. In recent years, there has been increased interest in the use of high-density, commercial, nonvolatile flash memories in space because of ever-increasing data volumes and strict power requirements. They are used in a wide variety of spacecraft subsystems. At one end of the spectrum, flash memories are used to store small amounts of mission-critical data such as boot code or configuration files and, at the other end, they are used to construct multi-gigabyte data recorders that record mission science data. This report examines single-event effect (SEE) and total ionizing dose (TID) response in single-level cell (SLC) 32-Gb, multi-level cell (MLC) 64-Gb, and Triple-level (TLC) 64-Gb NAND flash memories manufactured by Micron Technology with feature size of 25 nm.

Irom, Farokh↗

NASA NTRS2012

Radiation tests of highly scaled, high-density, commercial, nonvolatile NAND flash memories— update 2012

The space radiation environment poses a certain risk to all electronic components on Earth-orbiting and planetary mission spacecraft. In recent years, there has been increased interest in the use of high-density, commercial, nonvolatile flash memories in space because of ever-increasing data volumes and strict power requirements. They are used in a wide variety of spacecraft subsystems. At one end of the spectrum, flash memories are used to store small amounts of mission-critical data such as boot code or configuration files and, at the other end, they are used to construct multi-gigabyte data recorders that record mission science data. This report examines single-event effect (SEE) and total ionizing dose (TID) response in single-level cell (SLC) 32-Gb, multi-level cell (MLC) 64-Gb, and Triple-level (TLC) 64-Gb NAND flash memories manufactured by Micron Technology with feature size of 25 nm.

Allen, Gregory R.↗

NASA NTRSDate not supplied

Performance Optimization Methods for a Memory-Bound, Unstructured-Grid CFD Application on Massively Parallel GPU Platforms

Computational performance of the FUN3D unstructured-grid computational fluid dynamics (CFD) application on massively parallel GPU environments is memory-bound and highly dependent upon efficient reads from and atomic updates to the irregular cell-, edge-, and node-based data structures. In this talk, we present recent efforts into optimizing select performance-critical kernels on NVIDIA Tesla V100 and A100 GPUs and AMD CDNA MI100 GPUs. A novel use of L2 cache residency controls and asynchronous loads into on-chip shared memory are explored on the A100 GPU for the sparse iterative solver, which is dominated by mixed-precision, sparse matrix vector multiplication. Demonstrations show that these methods improve global memory bandwidth utilization by 13.5% on the A100 GPU. Several techniques are also presented that use registers and/or shared memory to facilitate array transposition and aggregation which combine to reduce the frequency and increase the cache efficiency of floating-point atomic updates to the irregular data structures. These methods are demonstrated to improve the kernel throughput by nearly 500% on select kernels on the AMD MI100 over atomic updates directly to global memory. Overall, both V100 and A100 GPUs outperformed the MI100 GPU on kernels dominated by double-precision atomic updates; however, the techniques demonstrated here reduced the performance gap and improved the MI100 performance.

GPU CPU unstructured CFD memory↗

NASA NTRS2001

A Parallel Cartesian Approach for External Aerodynamics of Vehicles with Complex Geometry

This workshop paper presents the current status in the development of a new approach for the solution of the Euler equations on Cartesian meshes with embedded boundaries in three dimensions on distributed and shared memory architectures. The approach uses adaptively refined Cartesian hexahedra to fill the computational domain. Where these cells intersect the geometry, they are cut by the boundary into arbitrarily shaped polyhedra which receive special treatment by the solver. The presentation documents a newly developed multilevel upwind solver based on a flexible domain-decomposition strategy. One novel aspect of the work is its use of space-filling curves (SFC) for memory efficient on-the-fly parallelization, dynamic re-partitioning and automatic coarse mesh generation. Within each subdomain the approach employs a variety reordering techniques so that relevant data are on the same page in memory permitting high-performance on cache-based processors. Details of the on-the-fly SFC based partitioning are presented as are construction rules for the automatic coarse mesh generation. After describing the approach, the paper uses model problems and 3- D configurations to both verify and validate the solver. The model problems demonstrate that second-order accuracy is maintained despite the presence of the irregular cut-cells in the mesh. In addition, it examines both parallel efficiency and convergence behavior. These investigations demonstrate a parallel speed-up in excess of 28 on 32 processors of an SGI Origin 2000 system and confirm that mesh partitioning has no effect on convergence behavior.

Aftosmis, M. J.↗