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All sources NASA NTRS DOE OSTI

NASA NTRS1988

Implementing direct, spatially isolated problems on transputer networks

Parametric studies were performed on transputer networks of up to 40 processors to determine how to implement and maximize the performance of the solution of problems where no processor-to-processor data transfer is required for the problem solution (spatially isolated). Two types of problems are investigated a computationally intensive problem where the solution required the transmission of 160 bytes of data through the parallel network, and a communication intensive example that required the transmission of 3 Mbytes of data through the network. This data consists of solutions being sent back to the host processor and not intermediate results for another processor to work on. Studies were performed on both integer and floating-point transputers. The latter features an on-chip floating-point math unit and offers approximately an order of magnitude performance increase over the integer transputer on real valued computations. The results indicate that a minimum amount of work is required on each node per communication to achieve high network speedups (efficiencies). The floating-point processor requires approximately an order of magnitude more work per communication than the integer processor because of the floating-point unit's increased computing capacity.

Ellis, Graham K.↗

NASA NTRS1989

Approximation algorithms for planning and control

A control system operating in a complex environment will encounter a variety of different situations, with varying amounts of time available to respond to critical events. Ideally, such a control system will do the best possible with the time available. In other words, its responses should approximate those that would result from having unlimited time for computation, where the degree of the approximation depends on the amount of time it actually has. There exist approximation algorithms for a wide variety of problems. Unfortunately, the solution to any reasonably complex control problem will require solving several computationally intensive problems. Algorithms for successive approximation are a subclass of the class of anytime algorithms, algorithms that return answers for any amount of computation time, where the answers improve as more time is allotted. An architecture is described for allocating computation time to a set of anytime algorithms, based on expectations regarding the value of the answers they return. The architecture described is quite general, producing optimal schedules for a set of algorithms under widely varying conditions.

Boddy, Mark↗

NASA NTRS1994

VLSI neuroprocessors

Electronic and optoelectronic hardware implementations of highly parallel computing architectures address several ill-defined and/or computation-intensive problems not easily solved by conventional computing techniques. The concurrent processing architectures developed are derived from a variety of advanced computing paradigms including neural network models, fuzzy logic, and cellular automata. Hardware implementation technologies range from state-of-the-art digital/analog custom-VLSI to advanced optoelectronic devices such as computer-generated holograms and e-beam fabricated Dammann gratings. JPL's concurrent processing devices group has developed a broad technology base in hardware implementable parallel algorithms, low-power and high-speed VLSI designs and building block VLSI chips, leading to application-specific high-performance embeddable processors. Application areas include high throughput map-data classification using feedforward neural networks, terrain based tactical movement planner using cellular automata, resource optimization (weapon-target assignment) using a multidimensional feedback network with lateral inhibition, and classification of rocks using an inner-product scheme on thematic mapper data. In addition to addressing specific functional needs of DOD and NASA, the JPL-developed concurrent processing device technology is also being customized for a variety of commercial applications (in collaboration with industrial partners), and is being transferred to U.S. industries. This viewgraph p resentation focuses on two application-specific processors which solve the computation intensive tasks of resource allocation (weapon-target assignment) and terrain based tactical movement planning using two extremely different topologies. Resource allocation is implemented as an asynchronous analog competitive assignment architecture inspired by the Hopfield network. Hardware realization leads to a two to four order of magnitude speed-up over conventional techniques and enables multiple assignments, (many to many), not achievable with standard statistical approaches. Tactical movement planning (finding the best path from A to B) is accomplished with a digital two-dimensional concurrent processor array. By exploiting the natural parallel decomposition of the problem in silicon, a four order of magnitude speed-up over optimized software approaches has been demonstrated.

Kemeny, Sabrina E.↗

NASA NTRS1994

VLSI Neuroprocessors

computing↗

NASA NTRS1995

Sensitivity analysis in multipole-accelerated panel methods for potential flow

In the design of an airframe, the effect of changing the geometry on resulting computations is necessary for design optimization. The geometry is defined in terms of a series of design variables, including design variables to define the wing planform, tail, canard, pylon, and nacelle. Design optimization in this research is based on how these design variable affect the potential flow. The potential flow is computed as a function of the geometry and location of a series of panels describing the airframe, which are in turn a function of the design variables. Multipole accelerated panel methods improve the computational complexity of the problem and thus are an attractive approach. To utilize the methods in design optimization, it was necessary to define the appropriate sensitivity derivatives. The overhead incurred from finding the sensitivity derivatives in conjunction with the original computation should be small. This research developed the background for multipole-accelerated panel methods and the framework for finding sensitivity derivatives in the methods. Potential flow panel codes are commonly used for powered-lift aerodynamic predictions for three dimensional geometries. Given an airframe which has been discretized into a series of panels to define the airframe geometry, potential is computed as a function of the influence of all panels on all other panels. This is a computationally intensive problem for which efficient solutions are desired to improve the computational time and to allow greater resolution by use of more panels. One such solution is the use of hierarchical multipole methods which entail approximations of the effects of far-field terms. Hierarchical multipole methods have become prevalent in molecular dynamics and gravitational physics, and have been introduced into the fields of capacitance calculations, computational fluid dynamics, and electromagnetics. The methods utilize multipole expansions to describe the effect of bodies (i.e. particles, astrophysical bodies, panels, etc.) within a sphere on points distant from the sphere, where the influence diminishes as a function of distance. The expansions are exact with infinite series, however, for practical computations, the series are truncated and accuracy is selected based on the number of terms retained in the expansions. A hierarchical tree structure groups bodies together based on proximity to allow definition of multipole expansions for each group. The multipole expansions are then used to compute the effect of the bodies in a group on distant bodies.

Leathrum, James F., Jr.↗

NASA NTRS2002

Intelligent Systems for Aerospace Engineering: An Overview

Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

Krishnakumar, Kalmanje↗

NASA NTRS1989

NETRA: A parallel architecture for integrated vision systems. 1: Architecture and organization

Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is considered to be a system that uses vision algorithms from all levels of processing for a high level application (such as object recognition). A model of computation is presented for parallel processing for an IVS. Using the model, desired features and capabilities of a parallel architecture suitable for IVSs are derived. Then a multiprocessor architecture (called NETRA) is presented. This architecture is highly flexible without the use of complex interconnection schemes. The topology of NETRA is recursively defined and hence is easily scalable from small to large systems. Homogeneity of NETRA permits fault tolerance and graceful degradation under faults. It is a recursively defined tree-type hierarchical architecture where each of the leaf nodes consists of a cluster of processors connected with a programmable crossbar with selective broadcast capability to provide for desired flexibility. A qualitative evaluation of NETRA is presented. Then general schemes are described to map parallel algorithms onto NETRA. Algorithms are classified according to their communication requirements for parallel processing. An extensive analysis of inter-cluster communication strategies in NETRA is presented, and parameters affecting performance of parallel algorithms when mapped on NETRA are discussed. Finally, a methodology to evaluate performance of algorithms on NETRA is described.

Choudhary, Alok N.↗

NASA NTRS2004

QuakeSim and the Solid Earth Research Virtual Observatory

We are developing simulation and analysis tools in order to develop a solid Earth science framework for understanding and studying active tectonic and earthquake processes. The goal of QuakeSim and its extension, the Solid Earth Research Virtual Observatory (SERVO), is to study the physics of earthquakes using state-of-the-art modeling, data manipulation, and pattern recognition technologies. We are developing clearly defined accessible data formats and code protocols as inputs to simulations, which are adapted to high-performance computers. The solid Earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes. We are using Web (Grid) service technology to demonstrate the assimilation of multiple distributed data sources (a typical data grid problem) into a major parallel high-performance computing earthquake forecasting code. Such a linkage of Geoinformatics with Geocomplexity demonstrates the value of the Solid Earth Research Virtual Observatory (SERVO) Grid concept, and advances Grid technology by building the first real-time large-scale data assimilation grid.

virtual observatory↗

NASA NTRS2002

Parallel Computing Strategies for Irregular Algorithms

Parallel computing promises several orders of magnitude increase in our ability to solve realistic computationally-intensive problems, but relies on their efficient mapping and execution on large-scale multiprocessor architectures. Unfortunately, many important applications are irregular and dynamic in nature, making their effective parallel implementation a daunting task. Moreover, with the proliferation of parallel architectures and programming paradigms, the typical scientist is faced with a plethora of questions that must be answered in order to obtain an acceptable parallel implementation of the solution algorithm. In this paper, we consider three representative irregular applications: unstructured remeshing, sparse matrix computations, and N-body problems, and parallelize them using various popular programming paradigms on a wide spectrum of computer platforms ranging from state-of-the-art supercomputers to PC clusters. We present the underlying problems, the solution algorithms, and the parallel implementation strategies. Smart load-balancing, partitioning, and ordering techniques are used to enhance parallel performance. Overall results demonstrate the complexity of efficiently parallelizing irregular algorithms.

Biswas, Rupak↗

NASA NTRS1990

Unsteady transonic Navier-Stokes computations for an oscillating wing using single and multiple zones

Modern jet transports and maneuvering tactical fighters operating in the transonic regime often give rise to time-dependent fluid physics that interact with flexible structural components, e.g., vortical flow, shocks, and separation. Efficient computational fluid dynamic (CFD) methods are required to study such computationally intensive problems. In this work a numerical method is presented to address this problem. Time-dependent, compressible, Navier-Stokes equations are used to simulate unsteady transonic flow about a three-dimensional rigid wing undergoing a forced periodic motion in angle of attack. An efficient, implicit, diagonal algorithm is utilized because of its low operation count per time step compared to other methods that solve systems of block matrix equations. The formal time accuracy is addressed theoretically and demonstrated numerically by comparison of computational results with experimental data. A zonal grid approach, capable of treating complex geometries, is presented and its time accuracy is demonstrated by comparing a zonal computation with a single grid computation and experimental data.

Chaderjian, Neal M.↗

NASA NTRS1999

Efficient Parallelization of a Dynamic Unstructured Application on the Tera MTA

The success of parallel computing in solving real-life computationally-intensive problems relies on their efficient mapping and execution on large-scale multiprocessor architectures. Many important applications are both unstructured and dynamic in nature, making their efficient parallel implementation a daunting task. This paper presents the parallelization of a dynamic unstructured mesh adaptation algorithm using three popular programming paradigms on three leading supercomputers. We examine an MPI message-passing implementation on the Cray T3E and the SGI Origin2OOO, a shared-memory implementation using cache coherent nonuniform memory access (CC-NUMA) of the Origin2OOO, and a multi-threaded version on the newly-released Tera Multi-threaded Architecture (MTA). We compare several critical factors of this parallel code development, including runtime, scalability, programmability, and memory overhead. Our overall results demonstrate that multi-threaded systems offer tremendous potential for quickly and efficiently solving some of the most challenging real-life problems on parallel computers.

Oliker, Leonid↗

NASA NTRS1990

Hypercube-Computer Analysis Of Electromagnetic Scattering

Capabilities of hypercube and parallel processing demonstrated. Report describes use of Mark III Hypercube computer to analyze scattering of electromagnetic waves. Purpose of study to assess utility of parallel computing in such computation-intensive problems as large-scale electromagnetic scattering. Two electromagnetic codes based on different algorithms converted to run on Mark III Hypercube. First code implements finite-difference, time-domain solution of Maxwell's curl equations. Second code is Numerical Electromagnetics Code (NEC-2) which embodies frequency-domain method and developed to analyze electromagnetic responses of antennas and other metallic structures. On Mark III Hypercube with 32 active nodes, largest lattice contains about 2,048,000 unit cells.

Patterson, J. E.↗

NASA NTRS1989

Parallel Architectures and Parallel Algorithms for Integrated Vision Systems

Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is a system that uses vision algorithms from all levels of processing to perform for a high level application (e.g., object recognition). An IVS normally involves algorithms from low level, intermediate level, and high level vision. Designing parallel architectures for vision systems is of tremendous interest to researchers. Several issues are addressed in parallel architectures and parallel algorithms for integrated vision systems.

Choudhary, Alok Nidhi↗

NASA NTRS1991

Parallel Processing System

In order to process very high resolution image data from spacecraft sensors, Goddard Space Flight Center commissioned the development of a Massively Parallel Processor (MPP) based upon simultaneous processing of image picture elements (pixels) rather than serial processing. It resulted in a considerable increase in computational speed. MasPar Computer Corporation's MasPar MP-1 incorporates this technology, allowing users to attack a variety of computationally-intensive problems. The MP-1 is no longer manufactured but has been replaced by the MP-2, a more advanced model.

Source record↗

NASA NTRS2004

Intelligent Systems: Shaping the Future of Aeronautics and Space Exploration

Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become important for NASA's future roles in Aeronautics and Space Exploration. Intelligent systems will enable safe, cost and mission-effective approaches to air& control, system design, spacecraft autonomy, robotic space exploration and human exploration of Moon, Mars, and beyond. In this talk, we will discuss intelligent system technologies and expand on the role of intelligent systems in NASA's missions. We will also present several examples of which some are highlighted m this extended abstract.

Krishnakumar, Kalmanje↗

NASA NTRS2004

The QuakeSim Project: Numerical Simulations for Active Tectonic Processes

In order to develop a solid earth science framework for understanding and studying of active tectonic and earthquake processes, this task develops simulation and analysis tools to study the physics of earthquakes using state-of-the art modeling, data manipulation, and pattern recognition technologies. We develop clearly defined accessible data formats and code protocols as inputs to the simulations. these are adapted to high-performance computers because the solid earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes.

tectonic processes↗

NASA NTRS2010

An Improved Wake Vortex Tracking Algorithm for Multiple Aircraft

The accurate tracking of vortex evolution from Large Eddy Simulation (LES) data is a complex and computationally intensive problem. The vortex tracking requires the analysis of very large three-dimensional and time-varying datasets. The complexity of the problem is further compounded by the fact that these vortices are embedded in a background turbulence field, and they may interact with the ground surface. Another level of complication can arise, if vortices from multiple aircrafts are simulated. This paper presents a new technique for post-processing LES data to obtain wake vortex tracks and wake intensities. The new approach isolates vortices by defining "regions of interest" (ROI) around each vortex and has the ability to identify vortex pairs from multiple aircraft. The paper describes the new methodology for tracking wake vortices and presents application of the technique for single and multiple aircraft.

Switzer, George F.↗

NASA NTRS2014

Preliminary Analysis: Am-241 RHU/TEG Electric Power Source for Nanosatellites

The Februay 2013 Space Works Commercial report indicates a strong increase in nano/microsatellite (1-50 kg) launch demand globally in future years. Nanosatellites (NanoSats) are small spacecraft in the 1-10 kg range, which present a simple, low-cost option for developing quickly-deployable satellites. CubeSats, a special category of NanoSats, are even being considered for interplanetary missions. However, the small dimensions of CubeSats and the limited mass of the NanoSat class in general place limits of capability on their electrical power systems (especially where typical power sources such as solar panels are considered) and stored energy reserves; restricting the power budget and overall functionality. For example, leveraging NanoSat clusters for computationally intensive problems that are solved collectively becomes more challenging with power related restrictions on communication and data-processing. Further, interplanetary missions that would take NanoSats far from the sun, make the use of solar panels less effective as a power source as their required area would become quite large. To overcome these limitations, americium 241 (Am-241) has been suggested as a low power source option. The Idaho National Laboratory, Center for Space Nuclear Research reports that:  (Production) requires small quantities of isotope - 62.5 g of Pu-238; 250 g Am- 241 (for 5 We); Am-241 is available at around 1 kg/yr commercially; Am-241 produces 59 kev gammas which are stopped readily by tungsten so the radiation field is very low. Whereby, an Am-241 source could be placed in among the instruments and the waste heat used to heat the platform; and  amounts of isotope are so low that launch approval may be easier, especially with tungsten encapsulation. As further reported, Am-241 has a half-life that is approximately five times greater than that of Pu- 238 and it has been determined that the neutron yield of a 241-AmO(sub 2) source is approximately an order of magnitude lower than that of a 238-PuO(sub 2) source of equal mass and degree of (sup 16)O enrichment. Also it has been demonstrated that shielded heat sources fuelled by oxygen-enriched 238-PuO(sub 2) have masses that are up to 10 times greater than those fuelled by oxygenenriched 241-AmO(sub 2) with equivalent thermal power outputs and neutron dose rates at 1 m radii. For these reasons, Am-241 is well suited to missions that demand long duration electrical power output, such as deep spaceflight missions and similar missions that use radiation-hard electronics and instrumentation that are less susceptible to neutron radiation damage.

Robertson, Glen A.↗