Parallel Stream Surface Computation for Large Data Sets
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Various program analysis techniques are efficient at discovering failures and properties. However, it is often difficult to evaluate results, such as program traces. This calls for abstraction and visualization tools. We propose an approach based on UML sequence diagrams, addressing shortcomings of such diagrams for concurrency. The resulting visualization is expressive and provides all the necessary information at a glance.
A research program investigating the use of AI techniques to aid in the development of a tactical decision generator (TDG) for within visual range (WVR) air combat engagements is discussed. The application of AI programming and problem-solving methods in the development and implementation of a concurrent version of the computerized logic for air-to-air warfare simulations (CLAWS) program, a second-generation TDG, is presented. Concurrent computing environments and programming approaches are discussed, and the design and performance of prototype concurrent TDG system (Cube CLAWS) are presented. It is concluded that the Cube CLAWS has provided a useful testbed to evaluate the development of a distributed blackboard system. The project has shown that the complexity of developing specialized software on a distributed, message-passing architecture such as the Hypercube is not overwhelming, and that reasonable speedups and processor efficiency can be achieved by a distributed blackboard system. The project has also highlighted some of the costs of using a distributed approach to designing a blackboard system.
A research program investigating the use of artificial intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of a concurrent version of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS) program, a second generation TDG, is presented. Concurrent computing environments and programming approaches are discussed and the design and performance of a prototype concurrent TDG system are presented.
Several short summaries of the work performed during this reporting period are presented. Topics discussed in this document include: (1) resilient seeded errors via simple techniques; (2) knowledge representation for engineering design; (3) analysis of faults in a multiversion software experiment; (4) implementation of parallel programming environment; (5) symbolic execution of concurrent programs; (6) two computer graphics systems for visualization of pressure distribution and convective density particles; (7) design of a source code management system; (8) vectorizing incomplete conjugate gradient on the Cyber 203/205; (9) extensions of domain testing theory and; (10) performance analyzer for the pisces system.
Space rendezvous involving human occupants will be required in many phases of space flight. In order that rendezvous capability be concurrent with other phases of manned space flight to insure that such tasks as the rotation and addition of crews for manned space station, supply of stations and launching complexes for deep-space probes, and the emergency rescue of personnel may be carried out, it is desirable to determine the ability of a human pilot to control the rendezvous maneuver. The National Aeronautics and Space Administration has conducted a study program to determine vehicle requirements and control techniques for a number of proposed methods for performing piloted space rendezvous. The final step in each phase of the rendezvous study program has been a simulation of the man-machine combination to test its feasibility. Initially, an analytical study was conducted to determine a range of conditions that would exist at the beginning of the terminal phase of rendezvous (ref. 1). Piloted systems were investigated for rendezvous control using these initial conditions. One such study of piloted rendezvous in which all the required control information was displayed to the simulator pilot on instruments is presented in reference 2. While the control of the rendezvous maneuver by use of the instrument display was shown to be feasible, the sufficiently accurate measurement of the necessary information to operate the instrument was realized to be a difficult problem. Consideration was therefore given to the possibility of maneuvering range and range rate required for the control of the rendezvous from visual sightings made during the initial control application. To provide this capability, an analytical study was made. This analytical study, presented in reference 3, derived three techniques for obtaining range and range rate visually and conducted a simplified preliminary situation to test the three analytical techniques. The study reported herein is a continuation of the simulation work begun in reference 3, and is aimed at determining the ability of a pilot to use visual information to reduce or eliminate the need for some or all of the data that would normally be displayed on instruments.
Distributed concurrent visualization and computation in computational fluid dynamics (CFD) is not a new concept. Specialized applications such as Realtime Interactive Particle-tracer (RIP) and vendor specific tools like Distributed Graphics Language (DGL) have been in use for some time. This paper describes a current project underway at NASA Lewis Research Center to provide the CFD researcher with an easy method for incorporating distributed processing concepts into program development. Details on the FORTRAN capable interface to a set of network and visualization functions are presented along with some results from initial CFD case studies that employ these techniques.
A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS), a second generation TDG, is presented. The Knowledge-Based Systems used by CLAWS to aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of CLAWS versus a baseline TDG developed in FORTRAN to run in real-time in the Langley Differential Maneuvering Simulator (DMS), are presented. To date, these test results have shown significant performance gains with respect to the TDG baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify and maintain than the baseline FORTRAN TDG programs. Alternate computing environments and programming approaches, including the use of parallel algorithms and heterogeneous computer networks are discussed, and the design and performance of a prototype concurrent TDG system are presented.
In this paper we describe a multiuser collaboration infrastructure that enables multiple mission scientists to remotely and collaboratively interact with visualization and planning software, using wireless networked personal digital assistants(PDAs) and other mobile devices. During ground operations of planetary rover and lander missions, scientists need to meet daily to review downlinked data and plan science activities. For example, scientists use the Science Activity Planner (SAP) in the Mars Exploration Rover (MER) mission to visualize downlinked data and plan rover activities during the science meetings [1]. Computer displays are projected onto large screens in the meeting room to enable the scientists to view and discuss downlinked images and data displayed by SAP and other software applications. However, only one person can interact with the software applications because input to the computer is limited to a single mouse and keyboard. As a result, the scientists have to verbally express their intentions, such as selecting a target at a particular location on the Mars terrain image, to that person in order to interact with the applications. This constrains communication and limits the returns of science planning. Furthermore, ground operations for Mars missions are fundamentally constrained by the short turnaround time for science and engineering teams to process and analyze data, plan the next uplink, generate command sequences, and transmit the uplink to the vehicle [2]. Therefore, improving ground operations is crucial to the success of Mars missions. The multiuser collaboration infrastructure enables users to control software applications remotely and collaboratively using mobile devices. The infrastructure includes (1) human-computer interaction techniques to provide natural, fast, and accurate inputs, (2) a communications protocol to ensure reliable and efficient coordination of the input devices and host computers, (3) an application-independent middleware that maintains the states, sessions, and interactions of individual users of the software applications, (4) an application programming interface to enable tight integration of applications and the middleware. The infrastructure is able to support any software applications running under the Windows or Unix platforms. The resulting technologies not only are applicable to NASA mission operations, but also useful in other situations such as design reviews, brainstorming sessions, and business meetings, as they can benefit from having the participants concurrently interact with the software applications (e.g., presentation applications and CAD design tools) to illustrate their ideas and provide inputs.