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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 1,657 records · Page 92

All sources NASA NTRS DOE OSTI

NASA NTRS1991

Robo-line storage: Low latency, high capacity storage systems over geographically distributed networks

Rapid advances in high performance computing are making possible more complete and accurate computer-based modeling of complex physical phenomena, such as weather front interactions, dynamics of chemical reactions, numerical aerodynamic analysis of airframes, and ocean-land-atmosphere interactions. Many of these 'grand challenge' applications are as demanding of the underlying storage system, in terms of their capacity and bandwidth requirements, as they are on the computational power of the processor. A global view of the Earth's ocean chlorophyll and land vegetation requires over 2 terabytes of raw satellite image data. In this paper, we describe our planned research program in high capacity, high bandwidth storage systems. The project has four overall goals. First, we will examine new methods for high capacity storage systems, made possible by low cost, small form factor magnetic and optical tape systems. Second, access to the storage system will be low latency and high bandwidth. To achieve this, we must interleave data transfer at all levels of the storage system, including devices, controllers, servers, and communications links. Latency will be reduced by extensive caching throughout the storage hierarchy. Third, we will provide effective management of a storage hierarchy, extending the techniques already developed for the Log Structured File System. Finally, we will construct a protototype high capacity file server, suitable for use on the National Research and Education Network (NREN). Such research must be a Cornerstone of any coherent program in high performance computing and communications.

Katz, Randy H.↗

NASA NTRS1993

Compiler-Assisted Multiple Instruction Rollback Recovery Using a Read Buffer

Multiple instruction rollback (MIR) is a technique to provide rapid recovery from transient processor failures and was implemented in hardware by researchers and slow in mainframe computers. Hardware-based MIR designs eliminate rollback data hazards by providing data redundancy implemented in hardware. Compiler-based MIR designs were also developed which remove rollback data hazards directly with data flow manipulations, thus eliminating the need for most data redundancy hardware. Compiler-assisted techniques to achieve multiple instruction rollback recovery are addressed. It is observed that data some hazards resulting from instruction rollback can be resolved more efficiently by providing hardware redundancy while others are resolved more efficiently with compiler transformations. A compiler-assisted multiple instruction rollback scheme is developed which combines hardware-implemented data redundancy with compiler-driven hazard removal transformations. Experimental performance evaluations were conducted which indicate improved efficiency over previous hardware-based and compiler-based schemes. Various enhancements to the compiler transformations and to the data redundancy hardware developed for the compiler-assisted MIR scheme are described and evaluated. The final topic deals with the application of compiler-assisted MIR techniques to aid in exception repair and branch repair in a speculative execution architecture.

Alewine, Neal Jon↗

NASA NTRS1994

Computations of Unsteady Viscous Compressible Flows Using Adaptive Mesh Refinement in Curvilinear Body-fitted Grid Systems

A methodology for accurate and efficient simulation of unsteady, compressible flows is presented. The cornerstones of the methodology are a special discretization of the Navier-Stokes equations on structured body-fitted grid systems and an efficient solution-adaptive mesh refinement technique for structured grids. The discretization employs an explicit multidimensional upwind scheme for the inviscid fluxes and an implicit treatment of the viscous terms. The mesh refinement technique is based on the AMR algorithm of Berger and Colella. In this approach, cells on each level of refinement are organized into a small number of topologically rectangular blocks, each containing several thousand cells. The small number of blocks leads to small overhead in managing data, while their size and regular topology means that a high degree of optimization can be achieved on computers with vector processors.

Steinthorsson, E.↗

NASA NTRS1999

Earth Orbiter 1 (EO-1): Wideband Advanced Recorder and Processor (WARP)

An overview of the Earth Orbitor 1 (EO1) Wideband Advanced Recorder and Processor (WARP) is presented in viewgraph form. The WARP is a spacecraft component that receives, stores, and processes high rate science data and its associated ancillary data from multispectral detectors, hyperspectral detectors, and an atmospheric corrector, and then transmits the data via an X-band or S-band transmitter to the ground station. The WARP project goals are: (1) Pathfinder for next generation LANDSAT mission; (2) Flight prove architectures and technologies; and (3) Identify future technology needs.

Smith, Terry↗

NASA NTRS1999

Sensitivity Analysis of ProSEDS (Propulsive Small Expendable Deployer System) Data Communication System

This paper discusses analytical approaches to evaluating performance of Spacecraft On-Board Computing systems, thereby ultimately achieving a reliable spacecraft data communications systems. The sensitivity analysis approach of memory system on the ProSEDS (Propulsive Small Expendable Deployer System) as a part of its data communication system will be investigated. Also, general issues and possible approaches to reliable Spacecraft On-Board Interconnection Network and Processor Array will be shown. The performance issues of a spacecraft on-board computing systems such as sensitivity, throughput, delay and reliability will be introduced and discussed.

Park, Nohpill↗

NASA NTRS1994

Parallel Processing Systems for Passive Ranging During Helicopter Flight

The complexity of rotorcraft missions involving operations close to the ground result in high pilot workload. In order to allow a pilot time to perform mission-oriented tasks, sensor-aiding and automation of some of the guidance and control functions are highly desirable. Images from an electro-optical sensor provide a covert way of detecting objects in the flight path of a low-flying helicopter. Passive ranging consists of processing a sequence of images using techniques based on optical low computation and recursive estimation. The passive ranging algorithm has to extract obstacle information from imagery at rates varying from five to thirty or more frames per second depending on the helicopter speed. We have implemented and tested the passive ranging algorithm off-line using helicopter-collected images. However, the real-time data and computation requirements of the algorithm are beyond the capability of any off-the-shelf microprocessor or digital signal processor. This paper describes the computational requirements of the algorithm and uses parallel processing technology to meet these requirements. Various issues in the selection of a parallel processing architecture are discussed and four different computer architectures are evaluated regarding their suitability to process the algorithm in real-time. Based on this evaluation, we conclude that real-time passive ranging is a realistic goal and can be achieved with a short time.

Sridhar, Bavavar↗

NASA NTRS2003

Free-Flowing Solutions for CFD

Licensed to over 1,500 customers worldwide, an advanced computational fluid dynamics (CFD) post-processor with a quick learning curve is consistently providing engineering solutions, with just the right balance of visual insight and hard data. FIELDVIEW is the premier product of JMSI, Inc., d.b.a. Intelligent Light, a woman-owned, small business founded in 1994 and located in Lyndhurst, New Jersey. In the early 1990s, Intelligent Light entered into a joint development contract with a research based company to commercialize the post-processing FIELDVIEW code. As Intelligent Light established itself, it purchased the exclusive rights to the code, and structured its business solely around the software technology. As a result, it is enjoying profits and growing at a rate of 25 to 30 percent per year. Advancements made from the earliest commercial launch of FIELDVIEW, all the way up to the recently released versions 8 and 8.2 of the program, have been backed by research collaboration with NASA's Langley Research Center, where some of the world's most progressive work in transient (also known as time-varying) CFD takes place.

Source record↗

NASA NTRS2012

The Modernization of a Long-Focal Length Fringe-Type Laser Velocimeter

A long-focal length laser velocimeter constructed in the early 1980's was upgraded using current technology to improve usability, reliability and future serviceability. The original, free-space optics were replaced with a state-of-the-art fiber-optic subsystem which allowed most of the optics, including the laser, to be remote from the harsh tunnel environment. General purpose high-speed digitizers were incorporated in a standard modular data acquisition system, along with custom signal processing software executed on a desktop computer, served as the replacement for the signal processors. The resulting system increased optical sensitivity with real-time signal/data processing that produced measurement precisions exceeding those of the original system. Monte Carlo simulations, along with laboratory and wind tunnel investigations were used to determine system characteristics and measurement precision.

Meyers, James F.↗

NASA NTRS2012

14- by 22-Foot Subsonic Tunnel Laser Velocimeter Upgrade

Meyers, James F.↗

DOE OSTI2017

Evaluating the Practicability of Multiphase CFD for BWR Fuel Assembly Analysis

Multiphase computational fluid dynamics (M-CFD) models of a boiling water reactor (BWR) fuel assembly have been generated in the commercial CFD code, STAR-CCM+ Ver.11.04.010-R8. The Eulerian multiphase approach was employed, in combination with a baseline ‘Zero Closure model’ for two-phase flow boiling, applicable to high void fraction regimes. The capability and practicability of MCFD for BWR fuel assembly were evaluated against the international OECD/NRC BWR Full-size Finemesh Bundle Test (BFBT) benchmark data. The benchmark selected, BFBT-4101-61, is a steady-state full power case, with high void fraction conditions. Geometrical modeling and mesh construction of BWR assemblies introduce challenges in generating high quality computational meshes, while retaining a low cell count to allow acceptable runtimes. In order to evaluate the scalability of the CFD code, parallel CFD simulations were carried out with the High Performance Computing (HPC) system of the Idaho National Laboratory. M-CFD results display good agreement with the experimental data for both local void fraction distribution and exit quality. The parallel speedup factor is linearly proportional to the number of processors up to 500 cores, and retains over 92% efficiency with 1000 cores. The execution time of the simulation decreased exponentially with increasing number of processors while the cost of the simulation increased linearly. The proposed baseline closure, in combination with the parallel performance of the STAR-CCM+ code demonstrated promising capabilities for analyzing BWR fuel assemblies.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1997

Tools for Analysis and Visualization of Large Time-Varying CFD Data Sets

In the second year, we continued to built upon and improve our scanline-based direct volume renderer that we developed in the first year of this grant. This extremely general rendering approach can handle regular or irregular grids, including overlapping multiple grids, and polygon mesh surfaces. It runs in parallel on multi-processors. It can also be used in conjunction with a k-d tree hierarchy, where approximate models and error terms are stored in the nodes of the tree, and approximate fast renderings can be created. We have extended our software to handle time-varying data where the data changes but the grid does not. We are now working on extending it to handle more general time-varying data. We have also developed a new extension of our direct volume renderer that uses automatic decimation of the 3D grid, as opposed to an explicit hierarchy. We explored this alternative approach as being more appropriate for very large data sets, where the extra expense of a tree may be unacceptable. We also describe a new approach to direct volume rendering using hardware 3D textures and incorporates lighting effects. Volume rendering using hardware 3D textures is extremely fast, and machines capable of using this technique are becoming more moderately priced. While this technique, at present, is limited to use with regular grids, we are pursuing possible algorithms extending the approach to more general grid types. We have also begun to explore a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH '96. In our initial implementation, we automatically image the volume from 32 equi-distant positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation. We are studying whether this will give a quantitative measure of the effects of approximation. We have created new tools for exploring the differences between images produced by various rendering methods. Images created by our software can be stored in the SGI RGB format. Our idtools software reads in pair of images and compares them using various metrics. The differences of the images using the RGB, HSV, and HSL color models can be calculated and shown. We can also calculate the auto-correlation function and the Fourier transform of the image and image differences. We will explore how these image differences compare in order to find useful metrics for quantifying the success of various visualization approaches. In general, progress was consistent with our research plan for the second year of the grant.

Wilhelms, Jane↗

DOE OSTI2022

Race conditions and data partitioning: risks posed by common errors to reproducible parallel simulations

When parallel algorithms for simulation were introduced in the 1970s, their development and use interested only experts in parallel computation. This circumstance changed as multi-core processors became commonplace, putting a parallel computer into the hands of every modeler. A natural outcome is growing interest in parallel simulation among persons not intimately familiar with parallel computing. At the same time, parallel simulation tools continue to be developed with the implicit assumption that the modeler is knowledgeable about parallel programming. The unintended consequence is a rapidly growing number of users of parallel simulation tools that are unlikely to recognize when the interaction of race conditions, partitioning strategies, and simultaneous action in their simulation models make results non-reproducible, thereby calling into question the validity of conclusions drawn from the simulation data. Here, we illustrate the potential dangers of exposing parallel algorithms to users who are not experts in parallel computation with example models constructed using existing parallel simulation tools. By doing so, we hope to refocus tool developers on usability, even if this new focus incurs loss of some performance.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Quantum/AI Topology-Aware Latency-Adaptive HPC Workflow Scheduling Optimization

The growing demand for more powerful high-performance computing (HPC) systems has led to a steady rise in energy consumption by supercomputing worldwide. This study is focused on comparing our Application-Topology Mapper (ATMapper) to the popular Simple Linux Utility for Resource Management (SLURM) for the purpose of exploring methods that can further optimize job-scheduling within HPC systems. ATMapper is an Artificial-Intelligence based approach to job-scheduling that is currently being enhanced with quantum annealing (QA) to generate optimal schedules faster. We are applying QA to speedup our ATMapper process to achieve higher computing efficiency, thereby reducing HPC energy consumption. Here, we examine how four job-scheduling approaches perform in processor node assignment when using an example network architecture of 4 interconnected nodes. Using a specialized script, we are assessing the schedule of a computation flow with 11 interdependent tasks. The data movements among nodes were tracked to count for the number of interactions (network hops) between nodes needed to complete the tasks. The total number of hops and the job completion time were then used to quantify the efficiency of the different mapping approaches. In addition to SLURM, we also compare our ATMapper to the QA-enabled LBNL TIGER and the D-Wave Distributed Computing processor assignment approaches. The preliminary results showed that our topology-aware, latency-adaptive ATMapper is significantly more efficient when compared to the other scheduling approaches due to its load-imbalance network allocation. The scheduler displayed a computing efficiency of 53% by performing significantly fewer network hops than its alternatives. By reducing the number of hops, ATMapper was able to perform all 11 tasks by using only 3 nodes out of given 4. This research indicates the potential to use QA/AI for HPC job-scheduling. Later, we will test a SLURM simulator program to draw further comparisons on the effectiveness of ATMapper's scheduling approach. The results of this comparison will serve as a baseline for later improving SLURM's performance using a QA-enhanced ATMapper approach.

Caraveo, Braulio [University of Huston - Clear Lak↗

NASA NTRS2012

Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System

Modern hyperspectral imaging systems are able to acquire far more data than can be downlinked from a spacecraft. Onboard data compression helps to alleviate this problem, but requires a system capable of power efficiency and high throughput. Software solutions have limited throughput performance and are power-hungry. Dedicated hardware solutions can provide both high throughput and power efficiency, while taking the load off of the main processor. Thus a hardware compression system was developed. The implementation uses a field-programmable gate array (FPGA). The implementation is based on the fast lossless (FL) compression algorithm reported in Fast Lossless Compression of Multispectral-Image Data (NPO-42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which achieves excellent compression performance and has low complexity. This algorithm performs predictive compression using an adaptive filtering method, and uses adaptive Golomb coding. The implementation also packetizes the coded data. The FL algorithm is well suited for implementation in hardware. In the FPGA implementation, one sample is compressed every clock cycle, which makes for a fast and practical realtime solution for space applications. Benefits of this implementation are: 1) The underlying algorithm achieves a combination of low complexity and compression effectiveness that exceeds that of techniques currently in use. 2) The algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. 3) Hardware acceleration provides a throughput improvement of 10 to 100 times vs. the software implementation. A prototype of the compressor is available in software, but it runs at a speed that does not meet spacecraft requirements. The hardware implementation targets the Xilinx Virtex IV FPGAs, and makes the use of this compressor practical for Earth satellites as well as beyond-Earth missions with hyperspectral instruments.

Aranki, Nazeeh I.↗

DOE OSTI2018

Job Management with mpi_jm

About this book: This book constitutes the refereed post-conference proceedings of 13 workshops held at the 33rd International ISC High Performance 2018 Conference, in Frankfurt, Germany, in June 2018: HPC I/O in the Data Center, HPC-IODC 2018; Workshop on Performance and Scalability of Storage Systems, WOPSSS 2018; 13th Workshop on Virtualization in High-Performance Cloud Computing, VHPC 2018; Third International Workshop on In Situ Visualization, WOIV 2018; 4th International Workshop on Communication Architectures for HPC, Big Data, Deep Learning and Clouds at Extreme Scale, ExaComm 2018; International Workshop on OpenPOWER for HPC, IWOPH 2018; IXPUG Workshop: Many-Core Computing on Intel Processors; Workshop on Sustainable Ultrascale Computing Systems; Approximate and Transprecision Computing on Emerging Technologies, ATCET 2018; First Workshop on the Convergence of Large-Scale Simulation and Artificial Intelligence; Third Workshop for Open Source Supercomputing, OpenSuCo 2018; First Workshop on Interactive High-Performance Computing; Workshop on Performance Portable Programming Models for Accelerators, P^3MA 2018. The 53 full papers included in this volume were carefully reviewed and selected from 80 submissions. They cover all aspects of research, development, and application of large-scale, high performance experimental and commercial systems. Topics include HPC computer architecture and hardware; programming models, system software, and applications; solutions for heterogeneity, reliability, power efficiency of systems; virtualization and containerized environments; big data and cloud computing; and artificial intelligence.

Berkowitz, Evan↗

DOE OSTI2017

Considerations on the Use of Custom Accelerators for Big Data Analytics

Accelerators, including Graphic Processing Units (GPUs) for gen- eral purpose computation, many-core designs with wide vector units (e.g., Intel Phi), have become a common component of many high performance clusters. The appearance of more stable and reliable tools tools that can automatically convert code written in high-level specifications with annotations (such as C or C++) to hardware de- scription languages (High-Level Synthesis - HLS), is also setting the stage for a broader use of reconfigurable devices (e.g., Field Pro- grammable Gate Arrays - FPGAs) in high performance system for the implementation of custom accelerators, helped by the fact that new processors include advanced cache-coherent interconnects for these components. In this chapter, we briefly survey the status of the use of accelerators in high performance systems targeted at big data analytics applications. We argue that, although the progress in the use of accelerators for this class of applications has been sig- nificant, differently from scientific simulations there still are gaps to close. This is particularly true for the ”irregular” behaviors exhibited by no-SQL, graph databases. We focus our attention on the limits of HLS tools for data analytics and graph methods, and discuss a new architectural template that better fits the requirement of this class of applications. We validate the new architectural templates by mod- ifying the Graph Engine for Multithreaded System (GEMS) frame- work to support accelerators generated with such a methodology, and testing with queries coming from the Lehigh University Benchmark (LUBM). The architectural template enables better supporting the task and memory level parallelism present in graph methods by sup- porting a new control model and a enhanced memory interface. We show that out solution allows generating parallel accelerators, pro- viding speed ups with respect to conventional HLS flows. We finally draw conclusions and present a perspective on the use of reconfig- urable devices and Design Automation tools for data analytics.

Data Analytics↗

DOE OSTI2019

Biositing Webtool, v1

The webtool displays the following types of data: Wastewater treatment plants (WWTP) with anaerobic digestion Facilities with anaerobic digestion onsite other than WWTP Combustion plants. Manure locations. Manure (non points) Municipal solid waste locations Crop locations Processor residue (non points) District energy systems Mixed use developments (non points) Process heating and cooling locations Basic Usage Users can interact with the map in the following ways: Select the year of the analysis from a drop-down menu. Set the background layer as biomass availability or thermal consumption density from a drop-down menu. Select whether the facility of interest is an Anaerobic Digestion or a Therochemical facility from a drop-down menu. This filters the biomass data by moisture and only shows the relevant portions based on the facility selection. Select from a drop-down menu whether the biomass amounts will be shown as gross amounts or technical amounts. Set the radius for the search buffer in which the analysis will be performed. Click on any point data on the map to get more information. Click on the map, to given the signal of the query point location, from where the algorithmic process is going to initiate. This will show the available biomass locations and amounts that fall within the predefined buffer zone. Download the data in a csv format for the entire county or the selected biomass that is inside the predefined buffer. Report whether there are errors in the data to us and we will work to the best of our abilities to confirm and fix any issues. The outputs of the algorithmic process are going to appear on the screen after the computation is done. The outputs consist of the locations of all available biomass that are within the buffer zone from the clicked location. By clicking on any point the user can get more information on the nature and amounts of the biomass.

Scown, Corinne↗

DOE OSTI2015

Intelligent sensor and controller framework for the power grid

Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with the software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.

24 POWER TRANSMISSION AND DISTRIBUTION↗