67,986 research outputs found
OpTiX-II: A Software Environment for MCDM based on Distributed and Parallel Computing
The intention of the paper is to give an introduction to the OpTiX-II Software Environment, which supports the parallel and distributed solution of decision problems which can be represented as mathematical nonlinear programming tasks. First, a brief summary of nonsequential solution concepts for this class of decision problems on multiprocessor systems will be given. The focus of attention will be put on coarse-grained parallelization and its implementation on multi-computer clusters. The conceptual design objectives for the OpTiX-II Software Environment will be presented as well as the implementation on a workstation cluster, a transputer system and a multiprocessor workstation (shared memory). The OpTiX-II system supports the steps from the formulation of decision problems to their solution on networks of (parallel) computers. In order to demonstrate the use of OpTiX-II, the solution of a decision problem from the field of structural design is discussed and some numerical test results are supplied
Teaching Parallel Programming Using Java
This paper presents an overview of the "Applied Parallel Computing" course
taught to final year Software Engineering undergraduate students in Spring 2014
at NUST, Pakistan. The main objective of the course was to introduce practical
parallel programming tools and techniques for shared and distributed memory
concurrent systems. A unique aspect of the course was that Java was used as the
principle programming language. The course was divided into three sections. The
first section covered parallel programming techniques for shared memory systems
that include multicore and Symmetric Multi-Processor (SMP) systems. In this
section, Java threads was taught as a viable programming API for such systems.
The second section was dedicated to parallel programming tools meant for
distributed memory systems including clusters and network of computers. We used
MPJ Express-a Java MPI library-for conducting programming assignments and lab
work for this section. The third and the final section covered advanced topics
including the MapReduce programming model using Hadoop and the General Purpose
Computing on Graphics Processing Units (GPGPU).Comment: 8 Pages, 6 figures, MPJ Express, MPI Java, Teaching Parallel
Programmin
Adapting the interior point method for the solution of LPs on serial, coarse grain parallel and massively parallel computers
In this paper we describe a unified scheme for implementing an interior point algorithm (IPM) over a range of computer architectures. In the inner iteration of the IPM a search direction is computed using Newton's method. Computationally this involves solving a sparse symmetric positive definite (SSPD) system of equations. The choice of direct and indirect methods for the solution of this system, and the design of data structures to take advantage of serial, coarse grain parallel and massively parallel computer architectures, are considered in detail. We put forward arguments as to why integration of the system within a sparse simplex solver is important and outline how the system is designed to achieve this integration
Parallel Performance of MPI Sorting Algorithms on Dual-Core Processor Windows-Based Systems
Message Passing Interface (MPI) is widely used to implement parallel
programs. Although Windowsbased architectures provide the facilities of
parallel execution and multi-threading, little attention has been focused on
using MPI on these platforms. In this paper we use the dual core Window-based
platform to study the effect of parallel processes number and also the number
of cores on the performance of three MPI parallel implementations for some
sorting algorithms
Architecture independent environment for developing engineering software on MIMD computers
Engineers are constantly faced with solving problems of increasing complexity and detail. Multiple Instruction stream Multiple Data stream (MIMD) computers have been developed to overcome the performance limitations of serial computers. The hardware architectures of MIMD computers vary considerably and are much more sophisticated than serial computers. Developing large scale software for a variety of MIMD computers is difficult and expensive. There is a need to provide tools that facilitate programming these machines. First, the issues that must be considered to develop those tools are examined. The two main areas of concern were architecture independence and data management. Architecture independent software facilitates software portability and improves the longevity and utility of the software product. It provides some form of insurance for the investment of time and effort that goes into developing the software. The management of data is a crucial aspect of solving large engineering problems. It must be considered in light of the new hardware organizations that are available. Second, the functional design and implementation of a software environment that facilitates developing architecture independent software for large engineering applications are described. The topics of discussion include: a description of the model that supports the development of architecture independent software; identifying and exploiting concurrency within the application program; data coherence; engineering data base and memory management
A review of High Performance Computing foundations for scientists
The increase of existing computational capabilities has made simulation
emerge as a third discipline of Science, lying midway between experimental and
purely theoretical branches [1, 2]. Simulation enables the evaluation of
quantities which otherwise would not be accessible, helps to improve
experiments and provides new insights on systems which are analysed [3-6].
Knowing the fundamentals of computation can be very useful for scientists, for
it can help them to improve the performance of their theoretical models and
simulations. This review includes some technical essentials that can be useful
to this end, and it is devised as a complement for researchers whose education
is focused on scientific issues and not on technological respects. In this
document we attempt to discuss the fundamentals of High Performance Computing
(HPC) [7] in a way which is easy to understand without much previous
background. We sketch the way standard computers and supercomputers work, as
well as discuss distributed computing and discuss essential aspects to take
into account when running scientific calculations in computers.Comment: 33 page
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