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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Temporal Precedence Checking for Switched Models and its Application to a Parallel Landing Protocol

This paper presents an algorithm for checking temporal precedence properties of nonlinear switched systems. This class of properties subsume bounded safety and capture requirements about visiting a sequence of predicates within given time intervals. The algorithm handles nonlinear predicates that arise from dynamics-based predictions used in alerting protocols for state-of-the-art transportation systems. It is sound and complete for nonlinear switch systems that robustly satisfy the given property. The algorithm is implemented in the Compare Execute Check Engine (C2E2) using validated simulations. As a case study, a simplified model of an alerting system for closely spaced parallel runways is considered. The proposed approach is applied to this model to check safety properties of the alerting logic for different operating conditions such as initial velocities, bank angles, aircraft longitudinal separation, and runway separation.

Duggirala, Parasara Sridhar↗
NASA NTRS2018

Applications of Parallel-Element, Embedded Mesh-Cap Acoustic Liner Concepts

This study explores progress achieved with 2DOF, 3DOF, and MDOF acoustic liners constructed with mesh caps embedded within a honeycomb core. These liner configurations offer potential for broadband noise reduction, and are suitable for conventional aircraft implementation. Samples for each configuration are tested in the NASA normal incidence tube and grazing flow impedance tube, with and without a wire mesh facesheet. Impedances based on these measured data compare favorably with those predicted using a transmission line impedance prediction model. Predicted impedances are then used as input for an aeroacoustic propagation code to compute axial acoustic pressure distributions in the grazing flow tube. These predicted distributions compare favorably with the corresponding measured distributions at frequencies away from the frequency of peak attenuation, but suffer slight degradation for frequencies very near the peak attenuation frequency, where the predicted results are sensitive to input impedance changes. As expected, the noise reduction frequency range increases as more degrees of freedom are included. Although the specific results achieved herein may differ from those that would be achieved with other 2DOF, 3DOF, and MDOF liners, this comparison highlights some of the key features that can be exploited in the design of parallel-element, embedded mesh-cap liners.

Jones, M. G.↗
NASA NTRS1994

Techniques and Tools for Performance Tuning of Parallel and Distributed Scientific Applications

Performance degradation in scientific computing on parallel and distributed computer systems can be caused by numerous factors. In this half-day tutorial we explain what are the important methodological issues involved in obtaining codes that have good performance potential. Then we discuss what are the possible obstacles in realizing that potential on contemporary hardware platforms, and give an overview of the software tools currently available for identifying the performance bottlenecks. Finally, some realistic examples are used to illustrate the actual use and utility of such tools.

Sarukkai, Sekhar R.↗
NASA NTRS1997

Opus: A Coordination Language for Multidisciplinary Applications

Data parallel languages, such as High Performance fortran, can be successfully applied to a wide range of numerical applications. However, many advanced scientific and engineering applications are multidisciplinary and heterogeneous in nature, and thus do not fit well into the data parallel paradigm. In this paper we present Opus, a language designed to fill this gap. The central concept of Opus is a mechanism called ShareD Abstractions (SDA). An SDA can be used as a computation server, i.e., a locus of computational activity, or as a data repository for sharing data between asynchronous tasks. SDAs can be internally data parallel, providing support for the integration of data and task parallelism as well as nested task parallelism. They can thus be used to express multidisciplinary applications in a natural and efficient way. In this paper we describe the features of the language through a series of examples and give an overview of the runtime support required to implement these concepts in parallel and distributed environments.

Chapman, Barbara↗
NASA NTRS1989

Development of parallel algorithms for electrical power management in space applications

The application of parallel techniques for electrical power system analysis is discussed. The Newton-Raphson method of load flow analysis was used along with the decomposition-coordination technique to perform load flow analysis. The decomposition-coordination technique enables tasks to be performed in parallel by partitioning the electrical power system into independent local problems. Each independent local problem represents a portion of the total electrical power system on which a loan flow analysis can be performed. The load flow analysis is performed on these partitioned elements by using the Newton-Raphson load flow method. These independent local problems will produce results for voltage and power which can then be passed to the coordinator portion of the solution procedure. The coordinator problem uses the results of the local problems to determine if any correction is needed on the local problems. The coordinator problem is also solved by an iterative method much like the local problem. The iterative method for the coordination problem will also be the Newton-Raphson method. Therefore, each iteration at the coordination level will result in new values for the local problems. The local problems will have to be solved again along with the coordinator problem until some convergence conditions are met.

Berry, Frederick C.↗
NASA NTRS1988

Electromagnetic scattering analysis on a hypercube parallel architecture

The applicability of a parallel architecture to the solution of large electromagnetic scattering problems is demonstrated. Two techniques, finite difference and the method of moments, are used to provide insight into the comparative speedups which can be attained for several algorithms. The flexibility of the hypercube architecture for different analysis algorithms is illustrated.

Patterson, Jean E.↗
DOE OSTI2016

Reaching bandwidth saturation using transparent injection parallelization

Although logically available, applications may not exploit enough instantaneous communication concurrency to maximize network utilization on HPC systems. This is exacerbated in hybrid programming models that combine single program multiple data with OpenMP or CUDA. We present the design of a “multi-threaded” runtime able to transparently increase the instantaneous network concurrency and to provide near saturation bandwidth, independent of the application configuration and dynamic behavior. The runtime offloads communication requests from application level tasks to multiple communication servers. The servers use system specific performance models to attain network saturation. Our techniques alleviate the need for spatial and temporal application level message concurrency optimizations. Experimental results show improved message throughput and bandwidth by as much as 150% for 4 KB messages on InfiniBand and by as much as 120% for 4 KB messages on Cray Aries. For more complex operations such as all-to-all collectives, we observe as much as 30% speedup. This translates into 23% speedup on 12,288 cores for a NAS FT implemented using FFTW. We observe as much as 76% speedup on 1500 cores for an already optimized UPC+OpenMP geometric multigrid application using hybrid parallelism. For the geometric multigrid GPU implementation, we observe as much as 44% speedup on 512 GPUs.

Chaimov, Nicholas↗
NASA NTRS1997

Efficient Parallel Kernel Solvers for Computational Fluid Dynamics Applications

Distributed-memory parallel computers dominate today's parallel computing arena. These machines, such as Intel Paragon, IBM SP2, and Cray Origin2OO, have successfully delivered high performance computing power for solving some of the so-called "grand-challenge" problems. Despite initial success, parallel machines have not been widely accepted in production engineering environments due to the complexity of parallel programming. On a parallel computing system, a task has to be partitioned and distributed appropriately among processors to reduce communication cost and to attain load balance. More importantly, even with careful partitioning and mapping, the performance of an algorithm may still be unsatisfactory, since conventional sequential algorithms may be serial in nature and may not be implemented efficiently on parallel machines. In many cases, new algorithms have to be introduced to increase parallel performance. In order to achieve optimal performance, in addition to partitioning and mapping, a careful performance study should be conducted for a given application to find a good algorithm-machine combination. This process, however, is usually painful and elusive. The goal of this project is to design and develop efficient parallel algorithms for highly accurate Computational Fluid Dynamics (CFD) simulations and other engineering applications. The work plan is 1) developing highly accurate parallel numerical algorithms, 2) conduct preliminary testing to verify the effectiveness and potential of these algorithms, 3) incorporate newly developed algorithms into actual simulation packages. The work plan has well achieved. Two highly accurate, efficient Poisson solvers have been developed and tested based on two different approaches: (1) Adopting a mathematical geometry which has a better capacity to describe the fluid, (2) Using compact scheme to gain high order accuracy in numerical discretization. The previously developed Parallel Diagonal Dominant (PDD) algorithm and Reduced Parallel Diagonal Dominant (RPDD) algorithm have been carefully studied on different parallel platforms for different applications, and a NASA simulation code developed by Man M. Rai and his colleagues has been parallelized and implemented based on data dependency analysis. These achievements are addressed in detail in the paper.

Sun, Xian-He↗
DOE OSTI2019

SAFIRE : Scalable and Accurate Fault Injection for Parallel Multi-threaded Applications

The software SAFIRE implements a fault injection tool to evaluate the impact of soft errors on parallel, multi-threaded applications. It implements instruction-level fault models that emulate soft errors by flipping bits in the register operands of executed machine instructions. SAFIRE is based on the LLVM compiler and utilizes novel techniques to optimize instruction instrumentation and fault injection. By detailed measurements, SAFIRE is multiple times faster than other state-of-the-art fault injection techniques, while having the same accuracy.

Georgakoudis, Giorgis↗
DOE OSTI2019

Performance portability study for massively parallel computational fluid dynamics application on scalable heterogeneous architectures

Patient-specific hemodynamic simulations have the possibility to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. Here, we introduce a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI+X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI+X programming on parallel heterogeneous systems. We report on the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

Employing Nested OpenMP for the Parallelization of Multi-Zone Computational Fluid Dynamics Applications

In this paper we describe the parallelization of the multi-zone code versions of the NAS Parallel Benchmarks employing multi-level OpenMP parallelism. For our study we use the NanosCompiler, which supports nesting of OpenMP directives and provides clauses to control the grouping of threads, load balancing, and synchronization. We report the benchmark results, compare the timings with those of different hybrid parallelization paradigms and discuss OpenMP implementation issues which effect the performance of multi-level parallel applications.

Ayguade, Eduard↗
NASA NTRS1998

Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications

This report contains the abstracts and technical papers from the Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications, held June 15-18, 1998, in Scottsdale, Arizona. The purpose of the workshop is to bring together software developers in meteorology and oceanography to discuss software engineering and code design issues for parallel architectures, including Massively Parallel Processors (MPP's), Parallel Vector Processors (PVP's), Symmetric Multi-Processors (SMP's), Distributed Shared Memory (DSM) multi-processors, and clusters. Issues to be discussed include: (1) code architectures for current parallel models, including basic data structures, storage allocation, variable naming conventions, coding rules and styles, i/o and pre/post-processing of data; (2) designing modular code; (3) load balancing and domain decomposition; (4) techniques that exploit parallelism efficiently yet hide the machine-related details from the programmer; (5) tools for making the programmer more productive; and (6) the proliferation of programming models (F--, OpenMP, MPI, and HPF).

OKeefe, Matthew↗
NASA NTRS1993

An integrated runtime and compile-time approach for parallelizing structured and block structured applications

Scientific and engineering applications often involve structured meshes. These meshes may be nested (for multigrid codes) and/or irregularly coupled (called multiblock or irregularly coupled regular mesh problems). A combined runtime and compile-time approach for parallelizing these applications on distributed memory parallel machines in an efficient and machine-independent fashion was described. A runtime library which can be used to port these applications on distributed memory machines was designed and implemented. The library is currently implemented on several different systems. To further ease the task of application programmers, methods were developed for integrating this runtime library with compilers for HPK-like parallel programming languages. How this runtime library was integrated with the Fortran 90D compiler being developed at Syracuse University is discussed. Experimental results to demonstrate the efficacy of our approach are presented. A multiblock Navier-Stokes solver template and a multigrid code were experimented with. Our experimental results show that our primitives have low runtime communication overheads. Further, the compiler parallelized codes perform within 20 percent of the code parallelized by manually inserting calls to the runtime library.

Agrawal, Gagan↗
NASA NTRS1993

Massively parallel neurocomputing for aerospace applications

An innovative hybrid, analog-digital charge-domain technology, for the massively parallel VLSI implementation of certain large scale matrix-vector operations, has recently been introduced. It employs arrays of Charge Coupled/Charge Injection Device cells holding an analog matrix of charge, which process digital vectors in parallel by means of binary, non-destructive charge transfer operations. The impact of this technology on massively parallel processing is discussed. Fundamentally new classes of algorithms, specifically designed for this emerging technology, as applied to signal processing, are derived.

Fijany, Amir↗
NASA NTRS1993

Massively Parallel Neurocomputing for Aerospace Applications

An innovative hybrid, analog-digital charge-domain technology, for the massively parallel VLSI implementation of certain large scale matrix-vector operations, has recently been introduced. It employs arrays of Charge Coupled/Charge Injection Device cells holding an analog matrix of charge, which process digital vectors in parallel by means of binary, non-destructive charge transfer operations. The impact of this technology on massively parallel processing is discussed.

massively↗