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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 181 records · Page 10

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.↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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.↗

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↗

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.↗

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↗

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.↗

Implementation of Self-Align Local Poly Interconnection on 0.25 Micron Flash Memory

For ETOX Flash technology. the self-aligned source module plays a critical role in minimizing cell size. For advanced Flash technology using the shallow-trench isolation (STI) scheme, however, it is difficult to form a stable source line. The Flash process in this experiment features an ETOX structure and with SIN spacer. Poly-Si (implanted poly) is used as the local interconnection material connecting the source line and was successfully implemented in the ETOX flash array in this paper.

C H Lee↗

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

Modeling of single-event upset in bipolar integrated circuits

The results of work done on the quantitative characterization of single-event upset (SEU) in bipolar random-access memories (RAMs) have been obtained through computer simulation of SEU in RAM cells that contain circuit models for bipolar transistors. The models include current generators that emulate the charge collected from ion tracks. The computer simulation results are compared with test data obtained from a RAM in a bipolar microprocessor chip. This methodology is applicable to other bipolar integrated circuit constructions in addition to RAM cells.

Zoutendyk, J. A.↗