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Results for “Parallel and high performance computing”

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 289 records · Page 16

A Study of Parallel Scalability and Dynamic Workload Balancing in GlennICE

The Glenn Icing Computational Environment (GlennICE) is a computational tool designed to calculate ice growth on complex three-dimensional geometries. It utilizes user-supplied computational fluid dynamics solutions for the geometry of interest. Key developments include advancements in convergence of collection efficiency, trajectory optimization, and refinement methodology. These improvements have significantly enhanced GlennICE’s efficiency for practical engineering applications. A recent study focused on benchmarking GlennICE’s scalability in a parallel environment using static scheduling. Findings indicated a potential twofold increase in efficiency through workload balance enhancements. This paper presents an analysis of the solver’s new workload balancing improvements, incorporating shared memory and dynamic scheduling routines. Results demonstrate a highly efficient and consistent algorithm across high-performance computing clusters.

Computational Icing↗

Low Temperature Performance of High-Speed Neural Network Circuits

Artificial neural networks, derived from their biological counterparts, offer a new and enabling computing paradigm specially suitable for such tasks as image and signal processing with feature classification/object recognition, global optimization, and adaptive control. When implemented in fully parallel electronic hardware, it offers orders of magnitude speed advantage. Basic building blocks of the new architecture are the processing elements called neurons implemented as nonlinear operational amplifiers with sigmoidal transfer function, interconnected through weighted connections called synapses implemented using circuitry for weight storage and multiply functions either in an analog, digital, or hybrid scheme.

artificial neural networks image processing signal↗

Computer modification reduces time of performing iterative division

Time reduction in performing iterative division results from using a serial-by-parallel divider employing a look-ahead feature that predetermines the sign relationships of several iterations before the computer cycle begins. This method can be employed in any data handling system performing high-speed division.

Source record↗

Galerkin/Runge-Kutta discretizations for semilinear parabolic equations

A new class of fully discrete Galerkin/Runge-Kutta methods is constructed and analyzed for semilinear parabolic initial boundary value problems. Unlike any classical counterpart, this class offers arbitrarily high, optimal order convergence. In support of this claim, error estimates are proved, and computational results are presented. Furthermore, it is noted that special Runge-Kutta methods allow computations to be performed in parallel so that the final execution time can be reduced to that of a low order method.

Keeling, Stephen L.↗

The NAS parallel benchmarks

A new set of benchmarks has been developed for the performance evaluation of highly parallel supercomputers in the framework of the NASA Ames Numerical Aerodynamic Simulation (NAS) Program. These consist of five 'parallel kernel' benchmarks and three 'simulated application' benchmarks. Together they mimic the computation and data movement characteristics of large-scale computational fluid dynamics applications. The principal distinguishing feature of these benchmarks is their 'pencil and paper' specification-all details of these benchmarks are specified only algorithmically. In this way many of the difficulties associated with conventional benchmarking approaches on highly parallel systems are avoided.

Bailey, D. H.↗

Validation of a High-Order Prefactored Compact Code on Nonlinear Flows with Complex Geometries

A finite-difference time domain solution of the airfoil gust problem is obtained using a high-accuracy nonlinear computational aeroacoustics code. For computational efficiency, the equations are cast in chain-rule curvilinear form, and a structured multiblock solver is used in parallel. In order to fully investigate the performance of this solver, a test matrix of eight problems are computed (two airfoil geometries, two gust frequencies, and two gust configurations). These results are compared to solutions obtained by the GUST3D frequency-domain solver both on the airfoil surface and in the far field. Grid density and domain size studies are included.

Hixon, R.↗

A computational-grid based system for continental drainage network extraction using SRTM digital elevation models

We describe a new effort for the computation of elevation derivatives using the Shuttle Radar Topography Mission (SRTM) results. Jet Propulsion Laboratory's (JPL) SRTM has produced a near global database of highly accurate elevation data. The scope of this database enables computing precise stream drainage maps and other derivatives on Continental scales. We describe a computing architecture for this computationally very complex task based on NASA's Information Power Grid (IPG), a distributed high performance computing network based on the GLOBUS infrastructure. The SRTM data characteristics and unique problems they present are discussed. A new algorithm for organizing the conventional extraction algorithms [1] into a cooperating parallel grid is presented as an essential component to adapt to the IPG computing structure. Preliminary results are presented for a Southern California test area, established for comparing SRTM and its results against those produced using the USGS National Elevation Data (NED) model.

stream extraction↗

Preliminary Evaluation of MapReduce for High-Performance Climate Data Analysis

MapReduce is an approach to high-performance analytics that may be useful to data intensive problems in climate research. It offers an analysis paradigm that uses clusters of computers and combines distributed storage of large data sets with parallel computation. We are particularly interested in the potential of MapReduce to speed up basic operations common to a wide range of analyses. In order to evaluate this potential, we are prototyping a series of canonical MapReduce operations over a test suite of observational and climate simulation datasets. Our initial focus has been on averaging operations over arbitrary spatial and temporal extents within Modern Era Retrospective- Analysis for Research and Applications (MERRA) data. Preliminary results suggest this approach can improve efficiencies within data intensive analytic workflows.

Duffy, Daniel Q.↗

Parallel Aircraft Trajectory Optimization with Analytic Derivatives

Trajectory optimization is an integral component for the design of aerospace vehicles, but emerging aircraft technologies have introduced new demands on trajectory analysis that current tools are not well suited to address. Designing aircraft with technologies such as hybrid electric propulsion and morphing wings requires consideration of the operational behavior as well as the physical design characteristics of the aircraft. The addition of operational variables can dramatically increase the number of design variables which motivates the use of gradient based optimization with analytic derivatives to solve the larger optimization problems. In this work we develop an aircraft trajectory analysis tool using a Legendre-Gauss-Lobatto based collocation scheme, providing analytic derivatives via the OpenMDAO multidisciplinary optimization framework. This collocation method uses an implicit time integration scheme that provides a high degree of sparsity and thus several potential options for parallelization. The performance of the new implementation was investigated via a series of single and multi-trajectory optimizations using a combination of parallel computing and constraint aggregation. The computational performance results show that in order to take full advantage of the sparsity in the problem it is vital to parallelize both the non-linear analysis evaluations and the derivative computations themselves. The constraint aggregation results showed a significant numerical challenge due to difficulty in achieving tight convergence tolerances. Overall, the results demonstrate the value of applying analytic derivatives to trajectory optimization problems and lay the foundation for future application of this collocation based method to the design of aircraft with where operational scheduling of technologies is key to achieving good performance.

aircraft↗

Measurement and Computation of Supersonic Flow in a Lobed Diffuser-Mixer for Trapped Vortex Combustors

The trapped vortex combustor (TVC) pioneered by Air Force Research Laboratories (AFRL) is under consideration as an alternative to conventional gas turbine combustors. The TVC has demonstrated excellent operational characteristics such as high combustion efficiency, low NO(x) emissions, effective flame stabilization, excellent high-altitude relight capability, and operation in the lean-burn or rich burn-quick quench-lean burn (RQL) modes of combustion. It also has excellent potential for lowering the engine combustor weight. This performance at low to moderate combustor mach numbers has stimulated interest in its ability to operate at higher combustion mach number, and for aerospace, this implies potentially higher flight mach numbers. To this end, a lobed diffuser-mixer that enhances the fuel-air mixing in the TVC combustor core was designed and evaluated, with special attention paid to the potential shock system entering the combustor core. For the present investigation, the lobed diffuser-mixer combustor rig is in a full annular configuration featuring sixfold symmetry among the lobes, symmetry within each lobe, and plain parallel, symmetric incident flow. During hardware cold-flow testing, significant discrepancies were found between computed and measured values for the pitot-probe-averaged static pressure profiles at the lobe exit plane. Computational fluid dynamics (CFD) simulations were initiated to determine whether the static pressure probe was causing high local flow-field disturbances in the supersonic flow exiting the diffuser-mixer and whether shock wave impingement on the pitot probe tip, pressure ports, or surface was the cause of the discrepancies. Simulations were performed with and without the pitot probe present in the modeling. A comparison of static pressure profiles without the probe showed that static pressure was off by nearly a factor of 2 over much of the radial profile, even when taking into account potential axial displacement of the probe by up to 0.25 in. (0.64 cm). Including the pitot probe in the CFD modeling and data interpretation lead to good agreement between measurement and prediction. Graphical inspection of the results showed that the shock waves impinging on the probe surface were highly nonuniform, with static pressure varying circumferentially among the pressure ports by over 10 percent in some cases. As part of the measurement methodology, such measurements should be routinely supplemented with CFD analyses that include the pitot probe as part of the flow-path geometry.

Brankovic, Andreja↗

Supersonic Transport Analysis on the IBM Parallel System SP2

Several studies of supersonic transport (SST) configurations have been undertaken by members of the High Speed Aerodynamics branch at NASA Ames. These computational investigations involved the analysis of shapes to study the sonic boom signatures, aerodynamic performance characteristics, as well as studies of nacelle/airframe integration. A variety of different computer codes were employed including both structured and unstructured codes. The AIRPLANE code has been used extensively in these investigations. This computer code solves the Euler equations for inviscid flow by exploiting an explicit finite volume method on a mesh of tetrahedral cells. AIRPLANE is capable of handling complete aircraft configurations including nacelles and diverters. An example of a generic SST configuration is shown and a comparison of computed and experimental force coefficients is presented. Most of the computations in support of the SST investigations have been run on the YMP and C-90 computers currently installed at NASA Ames. Additional information is contained in the original extended abstract.

Jameson, Antony↗

A real time microcomputer implementation of sensor failure detection for turbofan engines

An algorithm was developed which detects, isolates, and accommodates sensor failures using analytical redundancy. The performance of this algorithm was demonstrated on a full-scale F100 turbofan engine. The algorithm was implemented in real-time on a microprocessor-based controls computer which includes parallel processing and high order language programming. Parallel processing was used to achieve the required computational power for the real-time implementation. High order language programming was used in order to reduce the programming and maintenance costs of the algorithm implementation software. The sensor failure algorithm was combined with an existing multivariable control algorithm to give a complete control implementation with sensor analytical redundancy. The real-time microprocessor implementation of the algorithm which resulted in the successful completion of the algorithm engine demonstration, is described.

Delaat, John C.↗

Flight Simulation

Advanced Rotorcraft Technology, (ART), Mountain View, CA, developed FLIGHTLAB, a design/analysis tool and pilot simulation system for rotary wing aircraft, based on a research project conducted by ART, the Army Aerodynamics Directorate and Ames Research Center on using parallel processing in simulation models. The experiments showed that a new software architecture could provide real time simulations of high performance rotorcraft that closely matched actual flight at substantially lower cost than the mainframe computers previously needed for the simulations.

Source record↗

Parallelization of a three-dimensional compressible transition code

The compressible, three-dimensional, time-dependent Navier-Stokes equations are solved on a 20 processor Flex/32 computer. The code is a parallel implementation of an existing code operational on the Cray-2 at NASA Ames, which performs direct simulations of the initial stages of the transition process of wall-bounded flow at supersonic Mach numbers. Spectral collocation in all three spatial directions (Fourier along the plate and Chebyshev normal to it) ensures high accuracy of the flow variables. By hiding most of the parallelism in low-level routines, the casual user is shielded from most of the nonstandard coding constructs. Speedups of 13 out of a maximum of 16 are achieved on the largest computational grids.

Erlebacher, G.↗

Parallel and Distributed System Simulation

This exploratory study initiated our research into the software infrastructure necessary to support the modeling and simulation techniques that are most appropriate for the Information Power Grid. Such computational power grids will use high-performance networking to connect hardware, software, instruments, databases, and people into a seamless web that supports a new generation of computation-rich problem solving environments for scientists and engineers. In this context we looked at evaluating the NetSolve software environment for network computing that leverages the potential of such systems while addressing their complexities. NetSolve's main purpose is to enable the creation of complex applications that harness the immense power of the grid, yet are simple to use and easy to deploy. NetSolve uses a modular, client-agent-server architecture to create a system that is very easy to use. Moreover, it is designed to be highly composable in that it readily permits new resources to be added by anyone willing to do so. In these respects NetSolve is to the Grid what the World Wide Web is to the Internet. But like the Web, the design that makes these wonderful features possible can also impose significant limitations on the performance and robustness of a NetSolve system. This project explored the design innovations that push the performance and robustness of the NetSolve paradigm as far as possible without sacrificing the Web-like ease of use and composability that make it so powerful.

Dongarra, Jack↗

Investigating the Mobility of Light Autonomous Tracked Vehicles using a High Performance Computing Simulation Capability

This paper is concerned with the physics-based simulation of light tracked vehicles operating on rough deformable terrain. The focus is on small autonomous vehicles, which weigh less than 100 lb and move on deformable and rough terrain that is feature rich and no longer representable using a continuum approach. A scenario of interest is, for instance, the simulation of a reconnaissance mission for a high mobility lightweight robot where objects such as a boulder or a ditch that could otherwise be considered small for a truck or tank, become major obstacles that can impede the mobility of the light autonomous vehicle and negatively impact the success of its mission. Analyzing and gauging the mobility and performance of these light vehicles is accomplished through a modeling and simulation capability called Chrono::Engine. Chrono::Engine relies on parallel execution on Graphics Processing Unit (GPU) cards.

tracked vehicles↗

High Performance Access to Archival Data Stored in HDF4 and HDF5 on Cloud Object Stores Without Reformatting the Files

Cloud computing offers numerous advantages for users of extensive Earth science data collections. These benefits encompass direct online access to data files and granules from any location, scalable access supporting parallel computing workflows, and flexible computing tools enabling innovative experimentation with processing techniques. However, older archival file formats designed for distinct computing systems hinder efficient access to decade-long time-series data when compared to data stored in modern cloud-optimized formats like Web Object Stores (WOS), exemplified by Amazon Web Services’ Simple Storage Service (S3). We describe DMR++ (Dataset Metadata Response plus plus), a technology facilitating efficient access to HDF5 (Hierarchical Data Format, version 5) and HDF4 files stored on WOS systems without requiring data reformatting. DMR++ achieves performance comparable to technologies like Zarr while preserving the original file structure, a substantial benefit considering the vast quantity of archival files held by organizations such as NASA. Moreover, DMR++ typically outperforms cloud-optimized versions of HDF5. Essentially an XML (Extensible Markup Language) document usually stored alongside the described data, DMR++ can also be generated on-the-fly but is generally created during data staging to the WOS. Archival files that use HDF4/5 often store large arrays of numerical data. The data in these files is often compressed, typically reducing their size by a factor of four or more. To achieve efficient access to portions of those arrays, they are 'chunked' into smaller sub-arrays, each individually compressed. The chunk size is a compromise, where spinning disks can efficiently access data in smaller chunks while S3 favors larger chunks. A simple optimization of aggregating smaller chunks that are stored adjacently, transferring them in a single access and then individually decompressing them will improve performance. NASA data pose an additional challenge: special Application Programmer Interface (API) libraries are often needed to compute some variables. These libraries are incompatible with WOS environments. Our solution involves storing computed values in the DMR++ document or a companion file, making them accessible like other variables and eliminating the need for specialized APIs. We outline specific optimizations for both satellite grid and swath data stored in HDF4-EOS2 (Earth Observing System).

James Gallagher↗

A real time microcomputer implementation of sensor failure detection for turbofan engines

An algorithm was developed that detects, isolates, and accommodates sensor failures using analytical redundancy. The performance of this algorithm has been demonstrated on a full-scale F100 turbofan engine. The algorithm was implemented in real-time on a microprocessor-based controls computer which includes parallel processing and high order language programming. Parallel processing was used to achieve the required computational power for the real-time implementation. High order language programming was used in order to reduce the programming and maintenance costs of the algorithm implementation software. The sensor failure algorithm was combined with an existing multivariable control algorithm to give a complete control implementation with sensor analytical redundancy. The real-time microprocessor implementation of the algorithm, which resulted in the successful completion of the algorithm engine demonstration, is described.

Delaat, John C.↗