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An engineering approach to automatic programming

An exploratory study of the automatic generation and optimization of symbolic programs using DECOM - a prototypical requirement specification model implemented in pure LISP was undertaken. It was concluded, on the basis of this study, that symbolic processing languages such as LISP can support a style of programming based upon formal transformation and dependent upon the expression of constraints in an object-oriented environment. Such languages can represent all aspects of the software generation process (including heuristic algorithms for effecting parallel search) as dynamic processes since data and program are represented in a uniform format.

Rubin, Stuart H.

Sparse Gaussian elimination with controlled fill-in on a shared memory multiprocessor

It is shown that in sparse matrices arising from electronic circuits, it is possible to do computations on many diagonal elements simultaneously. A technique for obtaining an ordered compatible set directly from the ordered incompatible table is given. The ordering is based on the Markowitz number of the pivot candidates. This technique generates a set of compatible pivots with the property of generating few fills. A novel heuristic algorithm is presented that combines the idea of an order-compatible set with a limited binary tree search to generate several sets of compatible pivots in linear time. An elimination set for reducing the matrix is generated and selected on the basis of a minimum Markowitz sum number. The parallel pivoting technique presented is a stepwise algorithm and can be applied to any submatrix of the original matrix. Thus, it is not a preordering of the sparse matrix and is applied dynamically as the decomposition proceeds. Parameters are suggested to obtain a balance between parallelism and fill-ins. Results of applying the proposed algorithms on several large application matrices using the HEP multiprocessor (Kowalik, 1985) are presented and analyzed.

Alaghband, Gita

Evolutionary tree reconstruction

It is described how Minimum Description Length (MDL) can be applied to the problem of DNA and protein evolutionary tree reconstruction. If there is a set of mutations that transform a common ancestor into a set of the known sequences, and this description is shorter than the information to encode the known sequences directly, then strong evidence for an evolutionary relationship has been found. A heuristic algorithm is described that searches for the simplest tree (smallest MDL) that finds close to optimal trees on the test data. Various ways of extending the MDL theory to more complex evolutionary relationships are discussed.

Cheeseman, Peter

VHP - An environment for the remote visualization of heuristic processes

A software system called VHP is introduced which permits the visualization of heuristic algorithms on both resident and remote hardware platforms. The VHP is based on the DCF tool for interprocess communication and is applicable to remote algorithms which can be on different types of hardware and in languages other than VHP. The VHP system is of particular interest to systems in which the visualization of remote processes is required such as robotics for telescience applications.

Crawford, Stuart L.

Automated Spacelab Stowage Expert System for SLS missions

Issues related to the development of the Automated Spacelab Stowage Expert System (ASSESS) are examined including the problem domain, design, and status. The ASSESS concept is designed to configure stowage items into Spacelab lockers with an expert-system approach in which knowledge is available for every item and locker and for the complete heuristics. ASSESS employs the Knowledge Engineering Environment for development, and graphic displays present data on the items, lockers, and general system status. The automatic and manual modes are presented; the former provides the capability for an automatic solution to the stowage of a set of items into Spacelab lockers based on stowage heuristics defined and/or set by the user. The approach and heuristics algorithms are shown to permit the effective practical solution of NP-hard problems.

Kao, C. Y.

Reducing the complexity of software systems - A strategic software perspective

The results of a combined management and technical initiative aimed at reducing the size and complexity associated with developing operations planning, scheduling, and resource management software systems are presented. The initiative has produced operations concepts, functional requirements, system architectures, a comprehensive lexicon, and software tools to revolutionize the traditional software technology and development practices for planning, scheduling, and resource management systems used in space operations control centers. Examples of technology and practices to reduce complexity include a method for projecting design consequences from an operations concept, a universal architecture for heuristic algorithms, an object-oriented framework for describing large classes of problems that parametrically adapt to all domain peculiarities, the identification of general approaches which respond to changes with minimum impact on systems implementations, and a management structure for prototyping to minimize the risks of ill-conceived designs.

Hornstein, Rhoda S.

Site partitioning for distributed redundant disk arrays

Distributed redundant disk arrays can be used in a distributed computing system or database system to provide recovery in the presence of temporary and permanent failures of single sites. In this paper, we look at the problem of partitioning the sites into redundant arrays in such way that the communication costs for maintaining the parity information are minimized. We show that the partitioning problem is NP-complete and we propose two heuristic algorithms for finding approximate solutions.

Mourad, Antoine N.

Efficient partitioning and assignment on programs for multiprocessor execution

The general problem studied is that of segmenting or partitioning programs for distribution across a multiprocessor system. Efficient partitioning and the assignment of program elements are of great importance since the time consumed in this overhead activity may easily dominate the computation, effectively eliminating any gains made by the use of the parallelism. In this study, the partitioning of sequentially structured programs (written in FORTRAN) is evaluated. Heuristics, developed for similar applications are examined. Finally, a model for queueing networks with finite queues is developed which may be used to analyze multiprocessor system architectures with a shared memory approach to the problem of partitioning. The properties of sequentially written programs form obstacles to large scale (at the procedure or subroutine level) parallelization. Data dependencies of even the minutest nature, reflecting the sequential development of the program, severely limit parallelism. The design of heuristic algorithms is tied to the experience gained in the parallel splitting. Parallelism obtained through the physical separation of data has seen some success, especially at the data element level. Data parallelism on a grander scale requires models that accurately reflect the effects of blocking caused by finite queues. A model for the approximation of the performance of finite queueing networks is developed. This model makes use of the decomposition approach combined with the efficiency of product form solutions.

Standley, Hilda M.

Array distribution in data-parallel programs

We consider distribution at compile time of the array data in a distributed-memory implementation of a data-parallel program written in a language like Fortran 90. We allow dynamic redistribution of data and define a heuristic algorithmic framework that chooses distribution parameters to minimize an estimate of program completion time. We represent the program as an alignment-distribution graph. We propose a divide-and-conquer algorithm for distribution that initially assigns a common distribution to each node of the graph and successively refines this assignment, taking computation, realignment, and redistribution costs into account. We explain how to estimate the effect of distribution on computation cost and how to choose a candidate set of distributions. We present the results of an implementation of our algorithms on several test problems.

Chatterjee, Siddhartha

Partitioning sparse matrices with eigenvectors of graphs

The problem of computing a small vertex separator in a graph arises in the context of computing a good ordering for the parallel factorization of sparse, symmetric matrices. An algebraic approach for computing vertex separators is considered in this paper. It is shown that lower bounds on separator sizes can be obtained in terms of the eigenvalues of the Laplacian matrix associated with a graph. The Laplacian eigenvectors of grid graphs can be computed from Kronecker products involving the eigenvectors of path graphs, and these eigenvectors can be used to compute good separators in grid graphs. A heuristic algorithm is designed to compute a vertex separator in a general graph by first computing an edge separator in the graph from an eigenvector of the Laplacian matrix, and then using a maximum matching in a subgraph to compute the vertex separator. Results on the quality of the separators computed by the spectral algorithm are presented, and these are compared with separators obtained from other algorithms for computing separators. Finally, the time required to compute the Laplacian eigenvector is reported, and the accuracy with which the eigenvector must be computed to obtain good separators is considered. The spectral algorithm has the advantage that it can be implemented on a medium-size multiprocessor in a straightforward manner.

Pothen, Alex

Site Partitioning for Redundant Arrays of Distributed Disks

Redundant arrays of distributed disks (RADD) can be used in a distributed computing system or database system to provide recovery in the presence of disk crashes and temporary and permanent failures of single sites. In this paper, we look at the problem of partitioning the sites of a distributed storage system into redundant arrays in such a way that the communication costs for maintaining the parity information are minimized. We show that the partitioning problem is NP-hard. We then propose and evaluate several heuristic algorithms for finding approximate solutions. Simulation results show that significant reduction in remote parity update costs can be achieved by optimizing the site partitioning scheme.

Mourad, Antoine N.

Optimizing Aerobot Exploration of Venus

Venus Flyer Robot (VFR) is an aerobot; an autonomous balloon probe designed for remote exploration of Earth's sister planet in 2003. VFR's simple navigation and control system permits travel to virtually any location on Venus, but it can survive for only a limited duration in the harsh Venusian environment. To help address this limitation, we develop: (1) a global circulation model that captures the most important characteristics of the Venusian atmosphere; (2) a simple aerobot model that captures thermal restrictions faced by VFR at Venus; and (3) one exact and two heuristic algorithms that, using abstractions (1) and (2), construct routes making the best use of VFR's limited lifetime. We demonstrate this modeling by planning several small example missions and a prototypical mission that explores numerous interesting sites recently documented in the plane tary geology literature.

SPACE EXPLORATION

Parallel Tetrahedral Mesh Adaptation with Dynamic Load Balancing

The ability to dynamically adapt an unstructured grid is a powerful tool for efficiently solving computational problems with evolving physical features. In this paper, we report on our experience parallelizing an edge-based adaptation scheme, called 3D_TAG. using message passing. Results show excellent speedup when a realistic helicopter rotor mesh is randomly refined. However. performance deteriorates when the mesh is refined using a solution-based error indicator since mesh adaptation for practical problems occurs in a localized region., creating a severe load imbalance. To address this problem, we have developed PLUM, a global dynamic load balancing framework for adaptive numerical computations. Even though PLUM primarily balances processor workloads for the solution phase, it reduces the load imbalance problem within mesh adaptation by repartitioning the mesh after targeting edges for refinement but before the actual subdivision. This dramatically improves the performance of parallel 3D_TAG since refinement occurs in a more load balanced fashion. We also present optimal and heuristic algorithms that, when applied to the default mapping of a parallel repartitioner, significantly reduce the data redistribution overhead. Finally, portability is examined by comparing performance on three state-of-the-art parallel machines.

Oliker, Leonid

Runway Operations Planning: A Two-Stage Solution Methodology

The airport runway is a scarce resource that must be shared by different runway operations (arrivals, departures and runway crossings). Given the possible sequences of runway events, careful Runway Operations Planning (ROP) is required if runway utilization is to be maximized. Thus, Runway Operations Planning (ROP) is a critical component of airport operations planning in general and surface operations planning in particular. From the perspective of departures, ROP solutions are aircraft departure schedules developed by optimally allocating runway time for departures given the time required for arrivals and crossings. In addition to the obvious objective of maximizing throughput, other objectives, such as guaranteeing fairness and minimizing environmental impact, may be incorporated into the ROP solution subject to constraints introduced by Air Traffic Control (ATC) procedures. Generating optimal runway operations plans was approached in with a 'one-stage' optimization routine that considered all the desired objectives and constraints, and the characteristics of each aircraft (weight class, destination, Air Traffic Control (ATC) constraints) at the same time. Since, however, at any given point in time, there is less uncertainty in the predicted demand for departure resources in terms of weight class than in terms of specific aircraft, the ROP problem can be parsed into two stages. In the context of the Departure Planner (OP) research project, this paper introduces Runway Operations Planning (ROP) as part of the wider Surface Operations Optimization (SOO) and describes a proposed 'two stage' heuristic algorithm for solving the Runway Operations Planning (ROP) problem. Focus is specifically given on including runway crossings in the planning process of runway operations. In the first stage, sequences of departure class slots and runwy crossings slots are generated and ranked based on departure runway throughput under stochastic conditions. In the second stage, the departure class slots are populated with specific flights from the pool of available aircraft, by solving an integer program. Preliminary results from the algorithm implementation on real-world traffic data are included.

Anagnostakis, Ioannis

User Centered, Application Independent Visualization of National Airspace Data

This paper describes an application independent software tool, IV4D, built to visualize animated and still 3D National Airspace System (NAS) data specifically for aeronautics engineers who research aggregate, as well as single, flight efficiencies and behavior. IV4D was origin ally developed in a joint effort between the National Aeronautics and Space Administration (NASA) and the Air Force Research Laboratory (A FRL) to support the visualization of air traffic data from the Airspa ce Concept Evaluation System (ACES) simulation program. The three mai n challenges tackled by IV4D developers were: 1) determining how to d istill multiple NASA data formats into a few minimal dataset types; 2 ) creating an environment, consisting of a user interface, heuristic algorithms, and retained metadata, that facilitates easy setup and fa st visualization; and 3) maximizing the user?s ability to utilize the extended range of visualization available with AFRL?s existing 3D te chnologies. IV4D is currently being used by air traffic management re searchers at NASA?s Ames and Langley Research Centers to support data visualizations.

Murphy, James R.

Detecting Edges in Images by Use of Fuzzy Reasoning

A method of processing digital image data to detect edges includes the use of fuzzy reasoning. The method is completely adaptive and does not require any advance knowledge of an image. During initial processing of image data at a low level of abstraction, the nature of the data is indeterminate. Fuzzy reasoning is used in the present method because it affords an ability to construct useful abstractions from approximate, incomplete, and otherwise imperfect sets of data. Humans are able to make some sense of even unfamiliar objects that have imperfect high-level representations. It appears that to perceive unfamiliar objects or to perceive familiar objects in imperfect images, humans apply heuristic algorithms to understand the images

Dominguez, Jesus A.

Modeling Deicing Operations in Departure Scheduling Using Fast Time Simulation

In winter snow conditions, aircraft need inspection for deicing service before takeoff. Deicing service is a procedure to remove frost, ice, slush, or snow from aircraft for safe operation. Deicing operations vary by airport in many ways. Some airports have designated deicing zones, whereas some use a closed runway or terminal area to perform the procedure. Nonetheless, deicing operations add extra workloads to controllers, and cause increased taxi traffic on the ground. NASA and Korea Aerospace Research Institute (KARI) have been collaborating to model deicing operations at Incheon International Airport (ICN). This paper describes the deicing model and the study of deicing operations in departure scheduling using fast time simulations. The deicing model uses a heuristic algorithm for deicing zone assignment. In the fast time simulations, the model uses probability distributions derived from actual operation data to model deicing request and deicing zone time. It is envisioned that such a deicing model can be useful in airport surface scheduling to provide decision support and improve traffic management performance in winter snow operations.

modeling and simulation

Modeling Deicing Operations in Departure Scheduling using Fast Time Simulation

In winter snow conditions, aircraft need inspection for deicing service before takeoff. Deicing service is a procedure to remove frost, ice, slush, or snow from aircraft for safe operation. Deicing operations vary by airport in many ways. Some airports have designated deicing zones, whereas some use a closed runway or terminal area to perform the procedure. Nonetheless, deicing operations add extra workloads to controllers, and cause increased taxi traffic on the ground. NASA and Korea Aerospace Research Institute (KARI) have been collaborating to model deicing operations at Incheon International Airport (ICN). This paper describes the deicing model and the study of deicing operations in departure scheduling using fast time simulations. The deicing model uses a heuristic algorithm for deicing zone assignment. In the fast time simulations, the model uses probability distributions derived from actual operation data to model deicing request and deicing zone time. It is envisioned that such a deicing model can be useful in airport surface scheduling to provide decision support and improve traffic management performance in winter snow operations.

surface operation