Research in Structures and Dynamics, 1984

A symposium on advanced and trends in structures and dynamics was held to communicate new insights into physical behavior and to identify trends in the solution procedures for structures and dynamics problems. Pertinent areas of concern were (1) multiprocessors, parallel computation, and database management systems, (2) advances in finite element technology, (3) interactive computing and optimization, (4) mechanics of materials, (5) structural stability, (6) dynamic response of structures, and (7) advanced computer applications

Multi objective particle swarm optimization: algorithms and applications

Ph.DDOCTOR OF PHILOSOPH

Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis

Deep Neural Networks (DNNs) are becoming an important tool in modern computing applications. Accelerating their training is a major challenge and techniques range from distributed algorithms to low-level circuit design. In this survey, we describe the problem from a theoretical perspective, followed by approaches for its parallelization. We present trends in DNN architectures and the resulting implications on parallelization strategies. We then review and model the different types of concurrency in DNNs: from the single operator, through parallelism in network inference and training, to distributed deep learning. We discuss asynchronous stochastic optimization, distributed system architectures, communication schemes, and neural architecture search. Based on those approaches, we extrapolate potential directions for parallelism in deep learning

Advances in Evolutionary Algorithms

With the recent trends towards massive data sets and significant computational power, combined with evolutionary algorithmic advances evolutionary computation is becoming much more relevant to practice. Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field

Third CLIPS Conference Proceedings, volume 2

Expert systems are computer programs which emulate human expertise in well defined problem domains. The C Language Integrated Production System (CLIPS) is an expert system building tool, developed at the Johnson Space Center, which provides a complete environment for the development and delivery of rule and/or object based expert systems. CLIPS was specifically designed to provide a low cost option for developing and deploying expert system applications across a wide range of hardware platforms. The development of CLIPS has helped to improve the ability to deliver expert system technology throughout the public and private sectors for a wide range of applications and diverse computing environments. The Third Conference on CLIPS provided a forum for CLIPS users to present and discuss papers relating to CLIPS applications, uses, and extensions

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments

Optimizer-Assisted Load Balancing Techniques For Multicomputer Database-Management Systems

Although load balancing incurs processing costs, and therefore can have a profound influence on the optimized execution plan of a query, none of the existing parallelizing query optimizers consider this factor. In this paper, we address this issue by introducing the cost of load balancing as a new factor for query optimization. Specifically, we implemented three new optimizers for multiway join queries that take the load balancing issue into consideration. To evaluate the efficiency of these schemes, we also implemented a simulator for the parallel execution of multiway joins. To provide more faith, our simulation model was validated by comparing the simulation results to those produced by the actual implementation of the same algorithms running on a multicomputer system. This simulator was used in our study to compare the new techniques to a more conventional system in which load balancing is performed at runtime, but it is not a factor for query optimization. Our extensive simulation results confirm that the new methods, indeed, provide very significant savings. Most interestingly, the best scheme displays a performance which is essentially immune from the skew effect. Furthermore, we observed that these new optimizers can consistently achieve the same level of performance gain regardless of the CPU power, I/O, and communication capabilities of the computing system. This indicates that our approaches are generally useful for all hardware platforms. (C) 1995 Academic Press, Inc

Development and application of real-time and interactive software for complex system

Soft materials have attracted considerable interest in recent years for predicting the characteristics of phase separation and self-assembly in nanoscale structures. A popular method for demonstrating and simulating the dynamic behaviour of particles (e.g. particle tracking) and to consider effects of simulation parameters is cell dynamic simulation (CDS). This is a cellular computerisation technique that can be used to investigate different aspects of morphological topographies of soft material systems. The acquisition of quantitative data from particles is a critical requirement in order to obtain a better understanding and of characterising their dynamic behaviour. To achieve this objective particle tracking methods considering quantitative data and focusing on different properties and components of particles is essential. Despite the availability of various types of particle tracking used in experimental work, there is no method available to consider uniform computational data. In order to achieve accurate and efficient computational results for cell dynamic simulation method and particle tracking, two factors are essential: computing/calculating time-scale and simulation system size. Consequently, finding available computing algorithms and resources such as sequential algorithm for implementing a complex technique and achieving precise results is critical and rather expensive. Therefore, it is highly desirable to consider a parallel algorithm and programming model to solve time-consuming and massive computational processing issues. Hence, the gaps between the experimental and computational works and solving time consuming for expensive computational calculations need to be filled in order to investigate a uniform computational technique for particle tracking and significant enhancements in speed and execution times. The work presented in this thesis details a new particle tracking method for integrating diblock copolymers in the form of spheres with a shear flow and a novel designed GPU-based parallel acceleration approach to cell dynamic simulation (CDS). In addition, the evaluation of parallel models and architectures (CPUs and GPUs) utilising the mixtures of application program interface, OpenMP and programming model, CUDA were developed. Finally, this study presents the performance enhancements achieved with GPU-CUDA of approximately ~2 times faster than multi-threading implementation and 13~14 times quicker than optimised sequential processing for the CDS computations/workloads respectively

Optimizer-Assisted Load Balancing Techniques For Multicomputer Database Management Systems

Although load balancing incurs processing costs, and therefore can have a profound influence on the optimized execution plan of a query, none of the existing parallelizing query optimizers consider this factor. In this paper, we address this issue by introducing the cost of load balancing as a new factor for query optimization. Specifically, we implemented three new optimizers for multiway join queries that take the load balancing issue into consideration. To evaluate the efficiency of these schemes, we also implemented a simulator for the parallel execution of multiway joins. To provide more faith, our simulation model was validated by comparing the simulation results to those produced by the actual implementation of the same algorithms running on a multicomputer system. This simulator was used in our study to compare the new techniques to a more conventional system in which load balancing is performed at runtime, but it is not a factor for query optimization. Our extensive simulation results confirm that the new methods, indeed, provide very significant savings. Most interestingly, the best scheme displays a performance which is essentially immune from the skew effect. Furthermore, we observed that these new optimizers can consistently achieve the same level of performance gain regardless of the CPU power, I/O, and communication capabilities of the computing system. This indicates that our approaches are generally useful for all hardware platforms. © 1995 Academic Press, Inc