Reports on the initial experimental evaluation of ROPE (reusability-oriented parallel programming environment), a software component reuse system. ROPE helps the designer find and understand components by using a new ...
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Reports on the initial experimental evaluation of ROPE (reusability-oriented parallel programming environment), a software component reuse system. ROPE helps the designer find and understand components by using a new classification method called structured relational classification. ROPE is part of a development environment for parallel programs which uses a declarative/hierarchical graphical programming interface. This interface allows use of components with different levels of abstraction, ranging from design units to actual code modules. ROPE supports reuse of all the component types defined in the development environment. Programs developed with the aid of ROPE were found to have error rates far less than those developed without ROPE.
This paper presents the implementation of multitasking functions of DYNIX Sequent computers on the UNIX operating system. The Sequent computers are shared memory multiprocessor computers running the DYNIX operating sy...
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This paper presents the implementation of multitasking functions of DYNIX Sequent computers on the UNIX operating system. The Sequent computers are shared memory multiprocessor computers running the DYNIX operating system. These functions support data and function partitioning. They let the user implement subprograms by the processors of a Sequent computer in parallel. The functions can synchronize, lock, and unlock data and program segments. As a result, the simulator allows the users to develop their multitasking programs on a uniprocessor computer such as a SUN workstation, and later port them to a Sequent computer. Further, the simulator adds a level of abstraction on top of UNIX for concurrent programming. The functions of the simulator allow the user to handle the communication and synchronization of the processes in a program at a higher level of abstraction, while concentrating on the design of multitasking algorithms. The simulator is applied to a parallel selection algorithm. (C) 1998 John Wiley & Sons, Ltd.
Java's support for parallel and distributed processing makes the language attractive for metacomputing applications, such as parallel applications that run on geographically distributed (wide-area) systems. To obt...
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Java's support for parallel and distributed processing makes the language attractive for metacomputing applications, such as parallel applications that run on geographically distributed (wide-area) systems. To obtain actual experience with a Java-centric approach to metacomputing, we have built and used a highperformance wide-area Java system, called Manta, Manta implements the Java Remote Method Invocation (RMI) model using different communication protocols (active messages and TCP/IP) for different networks. The paper shows how wide-area parallel applications can be expressed and optimized using Java RMI, Also, it presents performance results of several applications on a wide-area system consisting of four Myrinet-based clusters connected by ATM WANs, We finally discuss alternative programming models, namely object replication, JavaSpaces, and MPI for Java, Copyright (C) 2000 John Wiley & Sons, Ltd.
Component-oriented programming has been applied to address the requirements of large-scale applications from computational sciences and engineering that present high performance computing (HPC) requirements. However, ...
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Component-oriented programming has been applied to address the requirements of large-scale applications from computational sciences and engineering that present high performance computing (HPC) requirements. However, parallelism continues to be a challenging requirement in the design of CBHPC (Component-Based High Performance Computing) platforms. This paper presents strong evidence about the efficacy and the efficiency of HPE (Hash programming Environment), a CBHPC platform that provides full support for parallel programming, on the development, deployment and execution of numerical simulation code onto cluster computing platforms. (C) 2012 Elsevier Inc. All rights reserved.
This paper presents an object-oriented interface for parallel programming, and an algorithm for automatic translation into parallel programs. The programming interface consists of a restricted subset of the object-ori...
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This paper presents an object-oriented interface for parallel programming, and an algorithm for automatic translation into parallel programs. The programming interface consists of a restricted subset of the object-oriented language C++. parallelism is defined explicitly at the abstract level of object definitions and method invocations within a single C++ program. The translator algorithm first generates a machine-independent communication graph and proceeds with the creation of the parallel programs, which are demonstrated for transputer systems with the HELIOS operating system. The necessary communication statements are generated automatically.
We discuss a programming methodology based on the use of multilinear algebra to design and implement parallel algorithms for linear computations. In particular, we review techniques for implementing expressions involv...
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We discuss a programming methodology based on the use of multilinear algebra to design and implement parallel algorithms for linear computations. In particular, we review techniques for implementing expressions involving the tensor product. We then show how the tensor product can be used to formulate Strassen's matrix multiplication algorithm. We report on our experience using this formulation and these techniques to implement a parallel version of Strassen's matrix multiplication algorithm on the Encore Multimax.
parallel computing on interconnected workstations is becoming a viable and attractive proposition due to the rapid growth in speeds of interconnection networks and processors. In the case of workstation clusters, ther...
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parallel computing on interconnected workstations is becoming a viable and attractive proposition due to the rapid growth in speeds of interconnection networks and processors. In the case of workstation clusters, there is always a considerable amount of unused computing capacity available in the network. However, heterogeneity in architectures and operating systems, load variations on machines, variations in machine availability, and failure susceptibility of networks and workstations complicate the situation for the programmer. In this context, new programming paradigms that reduce the burden involved in programming for distribution, load adaptability, heterogeneity, and fault tolerance gain importance. This paper identifies the issues involved in parallel computing on a network of workstations. The Anonymous Remote Computing (ARC) paradigm is proposed to address the issues specific to parallel programming on workstation systems. ARC differs from the conventional communicating process model by treating a program as one single entity consisting of several loosely coupled remote instruction blocks instead of treating it as a collection of processes. The ARC approach results in distribution transparency and heterogeneity transparency. At the same time, it provides fault tolerance and load adaptability to parallel programs on workstations. ARC is developed in a two-tiered architecture consisting of high level language constructs and low level ARC primitives. The paper describes an implementation of the ARC kernel supporting ARC primitives.
The study of tumor growth biology with computer-based models is currently an area of active research. Different simulation techniques can be used to describe the complexity of any real tumor behavior, among these, &qu...
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The study of tumor growth biology with computer-based models is currently an area of active research. Different simulation techniques can be used to describe the complexity of any real tumor behavior, among these, "cellular automata"-based simulations provide an accurate tumor growth graphical representation while, at the same time, keep simpler the implementation of the automata as computer programs. Several authors have recently published relevant proposals, based on the latter approach, to solve tumor growth representation problem through the development of some strategies for accelerating the simulation model. These strategies achieve computational performance of cellular-models representation by the appropriate selection of data types, and the clever use of supporting data structures. However, as of today, multithreaded processing techniques and multicore processors have not been used to program cellular growth models with generality. This paper presents a new model that incorporates parallel programming for multi and manycore processors, and implements any synchronization requirement necessary to implement the solution. The proposed parallel model has been proved using Java and C++ program implementations on two different platforms: chipset Intel i5-4440 and one node of 16-processors cluster of our university. The improvement resulting from the introduction of parallelism into the model is analyzed in this paper, comparing it with the standard sequential simulation model currently used by researchers in mathematical oncology.
parallel programming has become increasingly popular in the computer educational field over the past few years. Although parallel programs obtain the short execution time and the high throughput, learning how to write...
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parallel programming has become increasingly popular in the computer educational field over the past few years. Although parallel programs obtain the short execution time and the high throughput, learning how to write a well-structured and high-performance parallel program is still one of the challenges for most of students. How to let students learn parallel programming well is one of the important tasks that educators should resolve. This paper presents the learning of parallel programming using software refactoring methodologies and tools. Manual and automated refactoring are introduced to show how the learning is improved respectively. With manual refactoring, students learn how to perform the data or task decomposition and how to write a well-structured parallel software via customized programs and some benchmarks in JGF benchmark suite;with automated refactoring, students can transform the parallel parts quickly, and then evaluate the performance of a parallel software. Two automated refactoring tools are developed for educational purposes. Some of the experiences are also shared during conducting the course. (C) 2017 Wiley Periodicals, Inc.
This paper describes the design and implementation of a modular distributed architecture for distributed autonomous control of modular robot systems using parallel programming in industrial robotic manufacturing appli...
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This paper describes the design and implementation of a modular distributed architecture for distributed autonomous control of modular robot systems using parallel programming in industrial robotic manufacturing applications. The control system has an overall hierarchical structure, and parallel structure in its lower levels. The lower levels are composed of several autonomous units;each unit is equipped with a microprocessor-based controller, and has its own control functions with sensors, actuators, and communication interfaces as an intelligent autonomous sensing and actuating device. Operations of these autonomous actuators are integrated through a communication network of serial bus type. An autonomous actuator is a basic unit for distributed motion control of a robotic mechanism. Because of the hardware and software modularity, they have the advantages such as reduction of system costs, application flexibility, system reliability, and system extensibility. A microcontroller-based flexible and extensible architecture is proposed, and the features of distributed microcontroller implementation are discussed. For a two degrees of freedom robotic mechanism, a mobile robot with two coaxial independently driving wheels, position and velocity control algorithms to follow a planned path cooperatively are implemented, and the performance of the proposed architecture is experimentally evaluated. (C) 2003 Elsevier Science B.V. All rights reserved.
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