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At least 19 records

Multitasking domain decomposition fast Poisson solvers on the Cray Y-MP

The results of multitasking implementation of a domain decomposition fast Poisson solver on eight processors of the Cray Y-MP are presented. The object of this research is to study the performance of domain decomposition methods on a Cray supercomputer and to analyze the performance of different multitasking techniques using highly parallel algorithms. Two implementations of multitasking are considered: macrotasking (parallelism at the subroutine level) and microtasking (parallelism at the do-loop level). A conventional FFT-based fast Poisson solver is also multitasked. The results of different implementations are compared and analyzed. A speedup of over 7.4 on the Cray Y-MP running in a dedicated environment is achieved for all cases.

Chan, Tony F.

Adaptive allocation of decisionmaking responsibility between human and computer in multitask situations

As human and computer come to have overlapping decisionmaking abilities, a dynamic or adaptive allocation of responsibilities may be the best mode of human-computer interaction. It is suggested that the computer serve as a backup decisionmaker, accepting responsibility when human workload becomes excessive and relinquishing responsibility when workload becomes acceptable. A queueing theory formulation of multitask decisionmaking is used and a threshold policy for turning the computer on/off is proposed. This policy minimizes event-waiting cost subject to human workload constraints. An experiment was conducted with a balanced design of several subject runs within a computer-aided multitask flight management situation with different task demand levels. It was found that computer aiding enhanced subsystem performance as well as subjective ratings. The queueing model appears to be an adequate representation of the multitask decisionmaking situation, and to be capable of predicting system performance in terms of average waiting time and server occupancy. Server occupancy was further found to correlate highly with the subjective effort ratings.

Chu, Y.-Y.

Multitasking the code ARC3D

The CRAY multitasking system was developed in order to utilize all four processors and sharply reduce the wall clock run time. This paper describes the techniques used to modify the computational fluid dynamics code ARC3D for this run and analyzes the achieved speedup. The ARC3D code solves either the Euler or thin-layer N-S equations using an implicit approximate factorization scheme. Results indicate that multitask processing can be used to achieve wall clock speedup factors of over three times, depending on the nature of the program code being used. Multitasking appears to be particularly advantageous for large-memory problems running on multiple CPU computers.

Barton, John T.

Multitasking a three-dimensional Navier-Stokes algorithm on the Cray-2

A three-dimensional computational aerodynamics algorithm has been multitasked for efficient parallel execution on the Cray-2. It provides a means for examining the multitasking performance of a complete CFD application code. An embedded zonal multigrid scheme is used to solve the Reynolds-averaged Navier-Stokes equations for an internal flow model problem. The explicit nature of each component of the method allows a spatial partitioning of the computational domain to achieve a well-balanced task load for MIMD computers with vector-processing capability. Experiments have been conducted with both two- and three-dimensional multitasked cases. The best speedup attained by an individual task group was 3.54 on four processors of the Cray-2, while the entire solver yielded a speedup of 2.67 on four processors for the three-dimensional case. The multiprocessing efficiency of various types of computational tasks is examined, performance on two Cray-2s with different memory access speeds is compared, and extrapolation to larger problems is discussed.

Swisshelm, Julie M.

Multitasking

Multitasking is endemic in modern life and work: drivers talk on cell phones, office workers type while answering phone calls, students do homework while text messaging, nurses prepare injections while responding to doctor’s calls, and air traffic controllers direct aircraft in one sector while handling additional traffic in another. Whether in daily life or at work, we are constantly bombarded with multiple concurrent demands, and we have all somehow come to believe in the myth that we can, and in fact are expected to, easily address them all - without any repercussions. However, accumulating scientific evidence is now suggesting that multitasking increases the probability of human error. This talk presents a set of NASA studies that characterize concurrent demands in routine airline flight operations, in order to illustrate the ways operational task demands together with the proclivity to manage them all concurrently make human performance in this and in any domain vulnerable to potentially serious errors and to accidents.

multitasking

Human-computer interaction in multitask situations

Human-computer interaction in multitask decisionmaking situations is considered, and it is proposed that humans and computers have overlapping responsibilities. Queueing theory is employed to model this dynamic approach to the allocation of responsibility between human and computer. Results of simulation experiments are used to illustrate the effects of several system variables including number of tasks, mean time between arrivals of action-evoking events, human-computer speed mismatch, probability of computer error, probability of human error, and the level of feedback between human and computer. Current experimental efforts are discussed and the practical issues involved in designing human-computer systems for multitask situations are considered.

Rouse, W. B.

Multitasking and microtasking experience on the NA S Cray-2 and ACF Cray X-MP

The fast Fourier transform (FFT) kernel of the NAS benchmark program has been utilized to experiment with the multitasking library on the Cray-2 and Cray X-MP/48, and microtasking directives on the Cray X-MP. Some performance figures are shown, and the state of multitasking software is described.

Raiszadeh, Farhad

Multitasking for flows about multiple body configurations using the chimera grid scheme

The multitasking of a finite-difference scheme using multiple overset meshes is described. In this chimera, or multiple overset mesh approach, a multiple body configuration is mapped using a major grid about the main component of the configuration, with minor overset meshes used to map each additional component. This type of code is well suited to multitasking. Both steady and unsteady two dimensional computations are run on parallel processors on a CRAY-X/MP 48, usually with one mesh per processor. Flow field results are compared with single processor results to demonstrate the feasibility of running multiple mesh codes on parallel processors and to show the increase in efficiency.

Dougherty, F. C.

A personal computer-based, multitasking data acquisition system

A multitasking, data acquisition system was written to simultaneously collect meteorological radar and telemetry data from two sources. This system is based on the personal computer architecture. Data is collected via two asynchronous serial ports and is deposited to disk. The system is written in both the C programming language and assembler. It consists of three parts: a multitasking kernel for data collection, a shell with pull down windows as user interface, and a graphics processor for editing data and creating coded messages. An explanation of both system principles and program structure is presented.

Bailey, Steven A.

A multitasking behavioral control system for the Robotic All-Terrain Lunar Exploration Rover (RATLER)

An approach for a robotic control system which implements so called 'behavioral' control within a realtime multitasking architecture is proposed. The proposed system would attempt to ameliorate some of the problems noted by some researchers when implementing subsumptive or behavioral control systems, particularly with regard to multiple processor systems and realtime operations. The architecture is designed to allow synchronous operations between various behavior modules by taking advantage of a realtime multitasking system's intertask communications channels, and by implementing each behavior module and each interconnection node as a stand-alone task. The potential advantages of this approach over those previously described in the field are discussed. An implementation of the architecture is planned for a prototype Robotic All Terrain Lunar Exploration Rover (RATLER) currently under development and is briefly described.

Klarer, Paul

A Systematic Approach for Engagement Analysis Under Multitasking Environments

An overload condition can lead to high stress for an operator and further cause substantial drops in performance. On the other extreme, in automated systems, an operator may become underloaded; in which case, it is difficult for the operator to maintain sustained attention. When an unexpected event occurs, either internal or external to the automated system, a disengaged operation may neglect, misunderstand, or respond slowly/inappropriately to the situation. In this paper, we discuss a systematic approach monitor for extremes of cognitive workload and engagement in multitasking environments. Inferences of cognitive workload ar engagement are based on subjective evaluations, objective performance measures, physiological signals, and task analysis results. The systematic approach developed In this paper aggregates these types of information collected under the multitasking environment and can provide a real-time assessment or engagement.

Zhang, Guangfan

The Story of Multitasking

Multitasking is endemic in modern life and work: drivers talk on cell phones, office workers type while answering phone calls, students do homework while text messaging...but, nurses also prepare injections while responding to doctor's calls, and air traffic controllers direct aircraft in one sector while handling aircraft additional traffic in another. Whether in daily life or at work, we are constantly bombarded with multiple, concurrent interruptions and demands and we have all somehow come to believe in the myth that we can, and in fact are expected to, easily address them all - without any repercussions. Accumulating However, accumulating scientific evidence is now suggesting that multitasking increases the probability of human error. This talk presents a set of NASA studies that characterize concurrent demands in one work domain, routine airline cockpit operations, in order to illustrate the ways operational task demands together with the natural proclivity to manage them all concurrently make human performance in this and in any work domain vulnerable to potentially serious errors and to accidents.

Barshi, Immanuel

Modeling the human as a controller in a multitask environment

Modeling the human as a controller of slowly responding systems with preview is considered. Along with control tasks, discrete noncontrol tasks occur at irregular intervals. In multitask situations such as these, it has been observed that humans tend to apply piecewise constant controls. It is believed that the magnitude of controls and the durations for which they remain constant are dependent directly on the system bandwidth, preview distance, complexity of the trajectory to be followed, and nature of the noncontrol tasks. A simple heuristic model of human control behavior in this situation is presented. The results of a simulation study, whose purpose was determination of the sensitivity of the model to its parameters, are discussed.

Govindaraj, T.

On Choosing Between Two Probabilistic Choice Sub-models in a Dynamic Multitask Environment

An independent random utility model based on Thurstone's Theory of Comparative Judgment and a constant utility model based on Luce's Choice Axiom are reviewed in detail. Predictions from the two models are shown to be equivalent under certain restrictions on the distribution of the underlying random process. Each model is applied as a stochastic choice submodel in a dynamic, multitask, environment. Resulting choice probabilities are nearly identical, indicating that, despite their conceptual differences, neither model may be preferred over the other based solely on its predictive capability.

Soulsby, E. P.

Gigaflop performance on a CRAY-2: Multitasking a computational fluid dynamics application

The methodology is described for converting a large, long-running applications code that executed on a single processor of a CRAY-2 supercomputer to a version that executed efficiently on multiple processors. Although the conversion of every application is different, a discussion of the types of modification used to achieve gigaflop performance is included to assist others in the parallelization of applications for CRAY computers, especially those that were developed for other computers. An existing application, from the discipline of computational fluid dynamics, that had utilized over 2000 hrs of CPU time on CRAY-2 during the previous year was chosen as a test case to study the effectiveness of multitasking on a CRAY-2. The nature of dominant calculations within the application indicated that a sustained computational rate of 1 billion floating-point operations per second, or 1 gigaflop, might be achieved. The code was first analyzed and modified for optimal performance on a single processor in a batch environment. After optimal performance on a single CPU was achieved, the code was modified to use multiple processors in a dedicated environment. The results of these two efforts were merged into a single code that had a sustained computational rate of over 1 gigaflop on a CRAY-2. Timings and analysis of performance are given for both single- and multiple-processor runs.

Tennille, Geoffrey M.

General-purpose interface bus for multiuser, multitasking computer system

The architecture of a multiuser, multitasking, virtual-memory computer system intended for the use by a medium-size research group is described. There are three central processing units (CPU) in the configuration, each with 16 MB memory, and two 474 MB hard disks attached. CPU 1 is designed for data analysis and contains an array processor for fast-Fourier transformations. In addition, CPU 1 shares display images viewed with the image processor. CPU 2 is designed for image analysis and display. CPU 3 is designed for data acquisition and contains 8 GPIB channels and an analog-to-digital conversion input/output interface with 16 channels. Up to 9 users can access the third CPU simultaneously for data acquisition. Focus is placed on the optimization of hardware interfaces and software, facilitating instrument control, data acquisition, and processing.

Generazio, Edward R.

Multitasking the INS3D-LU code on the Cray Y-MP

This paper presents the results of multitasking the INS3D-LU code on eight processors. The code is a full Navier-Stokes solver for incompressible fluid in three dimensional generalized coordinates using a lower-upper symmetric-Gauss-Seidel implicit scheme. This code has been fully vectorized on oblique planes of sweep and parallelized using autotasking with some directives and minor modifications. The timing results for five grid sizes are presented and analyzed. The code has achieved a processing rate of over one Gflops.

Fatoohi, Rod

Dynamic decisions and work load in multitask supervisory control

A paradigm is developed for the problem of allocating in time a single resource to multiple simultaneous task demands which appear randomly, last for various periods, and offer varying rewards for service. Based upon a dynamic optimizing algorithm plus an estimator, and including response time and future discounting constraints, a model of the human decisionmaker is compared to experimental results for human subjects performing such a task at a computer-graphics terminal. Results indicate a reasonable fit, under various model parameters and task conditions, and suggest interesting hypotheses about the nature of human 'planning ahead' and mental work load.

Tulga, M. K.