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All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Distributed and collaborative synthetic environments

Fast graphics workstations and increased computing power, together with improved interface technologies, have created new and diverse possibilities for developing and interacting with synthetic environments. A synthetic environment system is generally characterized by input/output devices that constitute the interface between the human senses and the synthetic environment generated by the computer; and a computation system running a real-time simulation of the environment. A basic need of a synthetic environment system is that of giving the user a plausible reproduction of the visual aspect of the objects with which he is interacting. The goal of our Shastra research project is to provide a substrate of geometric data structures and algorithms which allow the distributed construction and modification of the environment, efficient querying of objects attributes, collaborative interaction with the environment, fast computation of collision detection and visibility information for efficient dynamic simulation and real-time scene display. In particular, we address the following issues: (1) A geometric framework for modeling and visualizing synthetic environments and interacting with them. We highlight the functions required for the geometric engine of a synthetic environment system. (2) A distribution and collaboration substrate that supports construction, modification, and interaction with synthetic environments on networked desktop machines.

Bajaj, Chandrajit L.↗
NASA NTRS2002

Memory-Intensive Benchmarks: IRAM vs. Cache-Based Machines

The increasing gap between processor and memory performance has lead to new architectural models for memory-intensive applications. In this paper, we explore the performance of a set of memory-intensive benchmarks and use them to compare the performance of conventional cache-based microprocessors to a mixed logic and DRAM processor called VIRAM. The benchmarks are based on problem statements, rather than specific implementations, and in each case we explore the fundamental hardware requirements of the problem, as well as alternative algorithms and data structures that can help expose fine-grained parallelism or simplify memory access patterns. The benchmarks are characterized by their memory access patterns, their basic control structures, and the ratio of computation to memory operation.

Biswas, Rupak↗
NASA NTRS2010

A Machine-Checked Proof of A State-Space Construction Algorithm

This paper presents the correctness proof of Saturation, an algorithm for generating state spaces of concurrent systems, implemented in the SMART tool. Unlike the Breadth First Search exploration algorithm, which is easy to understand and formalise, Saturation is a complex algorithm, employing a mutually-recursive pair of procedures that compute a series of non-trivial, nested local fixed points, corresponding to a chaotic fixed point strategy. A pencil-and-paper proof of Saturation exists, but a machine checked proof had never been attempted. The key element of the proof is the characterisation theorem of saturated nodes in decision diagrams, stating that a saturated node represents a set of states encoding a local fixed-point with respect to firing all events affecting only the node s level and levels below. For our purpose, we have employed the Prototype Verification System (PVS) for formalising the Saturation algorithm, its data structures, and for conducting the proofs.

Catano, Nestor↗
NASA NTRS2010

Multiscale Simulations of Magnetic Island Coalescence

We describe a new interactive parallel Adaptive Mesh Refinement (AMR) framework written in the Python programming language. This new framework, PyAMR, hides the details of parallel AMR data structures and algorithms (e.g., domain decomposition, grid partition, and inter-process communication), allowing the user to focus on the development of algorithms for advancing the solution of a systems of partial differential equations on a single uniform mesh. We demonstrate the use of PyAMR by simulating the pairwise coalescence of magnetic islands using the resistive Hall MHD equations. Techniques for coupling different physics models on different levels of the AMR grid hierarchy are discussed.

Dorelli, John C.↗
NASA NTRS2012

Graphics Processing Unit Assisted Thermographic Compositing

Objective: To develop a software application utilizing general purpose graphics processing units (GPUs) for the analysis of large sets of thermographic data. Background: Over the past few years, an increasing effort among scientists and engineers to utilize the GPU in a more general purpose fashion is allowing for supercomputer level results at individual workstations. As data sets grow, the methods to work them grow at an equal, and often great, pace. Certain common computations can take advantage of the massively parallel and optimized hardware constructs of the GPU to allow for throughput that was previously reserved for compute clusters. These common computations have high degrees of data parallelism, that is, they are the same computation applied to a large set of data where the result does not depend on other data elements. Signal (image) processing is one area were GPUs are being used to greatly increase the performance of certain algorithms and analysis techniques. Technical Methodology/Approach: Apply massively parallel algorithms and data structures to the specific analysis requirements presented when working with thermographic data sets.

Ragasa, Scott↗
NASA NTRS2003

A Fast Implementation of the ISOCLUS Algorithm

Unsupervised clustering is a fundamental building block in numerous image processing applications. One of the most popular and widely used clustering schemes for remote sensing applications is the ISOCLUS algorithm, which is based on the ISODATA method. The algorithm is given a set of n data points in d-dimensional space, an integer k indicating the initial number of clusters, and a number of additional parameters. The general goal is to compute the coordinates of a set of cluster centers in d-space, such that those centers minimize the mean squared distance from each data point to its nearest center. This clustering algorithm is similar to another well-known clustering method, called k-means. One significant feature of ISOCLUS over k-means is that the actual number of clusters reported might be fewer or more than the number supplied as part of the input. The algorithm uses different heuristics to determine whether to merge lor split clusters. As ISOCLUS can run very slowly, particularly on large data sets, there has been a growing .interest in the remote sensing community in computing it efficiently. We have developed a faster implementation of the ISOCLUS algorithm. Our improvement is based on a recent acceleration to the k-means algorithm of Kanungo, et al. They showed that, by using a kd-tree data structure for storing the data, it is possible to reduce the running time of k-means. We have adapted this method for the ISOCLUS algorithm, and we show that it is possible to achieve essentially the same results as ISOCLUS on large data sets, but with significantly lower running times. This adaptation involves computing a number of cluster statistics that are needed for ISOCLUS but not for k-means. Both the k-means and ISOCLUS algorithms are based on iterative schemes, in which nearest neighbors are calculated until some convergence criterion is satisfied. Each iteration requires that the nearest center for each data point be computed. Naively, this requires O(kn) time, where k denotes the current number of centers. Traditional techniques for accelerating nearest neighbor searching involve storing the k centers in a data structure. However, because of the iterative nature of the algorithm, this data structure would need to be rebuilt with each new iteration. Our approach is to store the data points in a kd-tree data structure. The assignment of points to nearest neighbors is carried out by a filtering process, which successively eliminates centers that can not possibly be the nearest neighbor for a given region of space. This algorithm is significantly faster, because large groups of data points can be assigned to their nearest center in a single operation. Preliminary results on a number of real Landsat datasets show that our revised ISOCLUS-like scheme runs about twice as fast.

Memarsadeghi, Nargess↗
NASA NTRS1990

Assembly planning for large truss structures in space

The approach is based on a graph search algorithm. A relational data structure is used to represent a truss structure. There are four types of entities: units, faces, edges, and vertices. There are contain/contained relationships for every pair of entity types, as well as in-contact relationships between faces. A best-first algorithm constitutes the core of the planner. The cost function in the current implementation corresponds to a combination of the rigidity of the intermediate structures and the total distance to be traversed by the agent executing the assembly tasks.

Homem De Mello, L. S.↗
NASA NTRS1992

A real-time robot arm collision avoidance system

A data structure and update algorithm are presented for a prototype real-time collision avoidance safety system simulating a multirobot workspace. The data structure is a variant of the octree, which serves as a spatial index. An octree recursively decomposes 3D space into eight equal cubic octants until each octant meets some decomposition criteria. The N-objects octree, which indexes a collection of 3D primitive solids is used. These primitives make up the two (seven-degrees-of-freedom) robot arms and workspace modeled by the system. As robot arms move, the octree is updated to reflect their changed positions. During most update cycles, any given primitive does not change which octree nodes it is in. Thus, modification to the octree is rarely required. Cycle time for interpreting current arm joint angles, updating the octree to reflect new positions, and detecting/reporting imminent collisions averages 30 ms on an Intel 80386 processor running at 20 MHz.

Shaffer, Clifford A.↗
NASA NTRS1990

A real-time robot arm collision detection system

A data structure and update algorithm are presented for a prototype real time collision detection safety system for a multi-robot environment. The data structure is a variant of the octree, which serves as a spatial index. An octree recursively decomposes 3-D space into eight equal cubic octants until each octant meets some decomposition criteria. The octree stores cylspheres (cylinders with spheres on each end) and rectangular solids as primitives (other primitives can easily be added as required). These primitives make up the two seven degrees-of-freedom robot arms and environment modeled by the system. Octree nodes containing more than a predetermined number N of primitives are decomposed. This rule keeps the octree small, as the entire environment for the application can be modeled using a few dozen primitives. As robot arms move, the octree is updated to reflect their changed positions. During most update cycles, any given primitive does not change which octree nodes it is in. Thus, modification to the octree is rarely required. Incidents in which one robot arm comes too close to another arm or an object are reported. Cycle time for interpreting current joint angles, updating the octree, and detecting/reporting imminent collisions averages 30 milliseconds on an Intel 80386 processor running at 20 MHz.

Shaffer, Clifford A.↗
NASA NTRS1989

Parallel processors and nonlinear structural dynamics algorithms and software

The adaptation of a finite element program with explicit time integration to a massively parallel SIMD (single instruction multiple data) computer, the CONNECTION Machine is described. The adaptation required the development of a new algorithm, called the exchange algorithm, in which all nodal variables are allocated to the element with an exchange of nodal forces at each time step. The architectural and C* programming language features of the CONNECTION Machine are also summarized. Various alternate data structures and associated algorithms for nonlinear finite element analysis are discussed and compared. Results are presented which demonstrate that the CONNECTION Machine is capable of outperforming the CRAY XMP/14.

Belytschko, Ted↗
NASA NTRS1977

FLUT - A program for aeroelastic stability analysis

A computer program (FLUT) that can be used to evaluate the aeroelastic stability of aircraft structures in subsonic flow is described. The algorithm synthesizes data from a structural vibration analysis with an unsteady aerodynamics analysis and then performs a complex eigenvalue analysis to assess the system stability. The theoretical basis of the program is discussed with special emphasis placed on some innovative techniques which improve the efficiency of the analysis. User information needed to efficiently and successfully utilize the program is provided. In addition to identifying the required input, the flow of the program execution and some possible sources of difficulty are included. The use of the program is demonstrated with a listing of the input and output for a simple example.

Johnson, E. H.↗
NASA NTRS1974

Global parallel unification for large question-answering systems

An efficient means of storing data in a first-order predicate calculus theorem-proving system is described. The data structure is oriented for large scale question-answering (QA) systems. An algorithm is outlined which uses the data structure to unify a given literal in parallel against all literals in all clauses in the data base. The data structure permits a compact representation of data within a QA system. Some suggestions are made for heuristics which can be used to speed-up the unification algorithm in systems.

Auguston, J. G.↗
NASA NTRS1990

Unstructured mesh methods for CFD

Mesh generation methods for Computational Fluid Dynamics (CFD) are outlined. Geometric modeling is discussed. An advancing front method is described. Flow past a two engine Falcon aeroplane is studied. An algorithm and associated data structure called the alternating digital tree, which efficiently solves the geometric searching problem is described. The computation of an initial approximation to the steady state solution of a given poblem is described. Mesh generation for transient flows is described.

Peraire, J.↗
NASA NTRS1999

Object-Oriented Design for Sparse Direct Solvers

We discuss the object-oriented design of a software package for solving sparse, symmetric systems of equations (positive definite and indefinite) by direct methods. At the highest layers, we decouple data structure classes from algorithmic classes for flexibility. We describe the important structural and algorithmic classes in our design, and discuss the trade-offs we made for high performance. The kernels at the lower layers were optimized by hand. Our results show no performance loss from our object-oriented design, while providing flexibility, case of use, and extensibility over solvers using procedural design.

Dobrian, Florin↗
NASA NTRS2000

Fast Particle Methods for Multiscale Phenomena Simulations

We are developing particle methods oriented at improving computational modeling capabilities of multiscale physical phenomena in : (i) high Reynolds number unsteady vortical flows, (ii) particle laden and interfacial flows, (iii)molecular dynamics studies of nanoscale droplets and studies of the structure, functions, and evolution of the earliest living cell. The unifying computational approach involves particle methods implemented in parallel computer architectures. The inherent adaptivity, robustness and efficiency of particle methods makes them a multidisciplinary computational tool capable of bridging the gap of micro-scale and continuum flow simulations. Using efficient tree data structures, multipole expansion algorithms, and improved particle-grid interpolation, particle methods allow for simulations using millions of computational elements, making possible the resolution of a wide range of length and time scales of these important physical phenomena.The current challenges in these simulations are in : [i] the proper formulation of particle methods in the molecular and continuous level for the discretization of the governing equations [ii] the resolution of the wide range of time and length scales governing the phenomena under investigation. [iii] the minimization of numerical artifacts that may interfere with the physics of the systems under consideration. [iv] the parallelization of processes such as tree traversal and grid-particle interpolations We are conducting simulations using vortex methods, molecular dynamics and smooth particle hydrodynamics, exploiting their unifying concepts such as : the solution of the N-body problem in parallel computers, highly accurate particle-particle and grid-particle interpolations, parallel FFT's and the formulation of processes such as diffusion in the context of particle methods. This approach enables us to transcend among seemingly unrelated areas of research.

Koumoutsakos, P.↗
NASA NTRS2008

Multiple-Instance Regression with Structured Data

We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a set of bags with real-valued labels, each containing a set of unlabeled items, in which the relevance of each item to its bag label is unknown. The goal is to predict the labels of new bags from their contents. Unlike previous MIR methods, MI-ClusterRegress can operate on bags that are structured in that they contain items drawn from a number of distinct (but unknown) distributions. MI-ClusterRegress simultaneously learns a model of the bag's internal structure, the relevance of each item, and a regression model that accurately predicts labels for new bags. We evaluated this approach on the challenging MIR problem of crop yield prediction from remote sensing data. MI-ClusterRegress provided predictions that were more accurate than those obtained with non-multiple-instance approaches or MIR methods that do not model the bag structure.

learning↗
NASA NTRS2007

Discrete Data Transfer Technique for Fluid-Structure Interaction

This paper presents a general three-dimensional algorithm for data transfer between dissimilar meshes. The algorithm is suitable for applications of fluid-structure interaction and other high-fidelity multidisciplinary analysis and optimization. Because the algorithm is independent of the mesh topology, we can treat structured and unstructured meshes in the same manner. The algorithm is fast and accurate for transfer of scalar or vector fields between dissimilar surface meshes. The algorithm is also applicable for the integration of a scalar field (e.g., coefficients of pressure) on one mesh and injection of the resulting vectors (e.g., force vectors) onto another mesh. The author has implemented the algorithm in a C++ computer code. This paper contains a complete formulation of the algorithm with a few selected results.

Samareh, Jamshid A.↗