Parallel Computing in Economics - An Overview of the Software Frameworks

This paper discusses problems related to parallel computing applied in economics. It introduces the paradigms of parallel computing and emphasizes the new trends in this field - a combination between GPU computing, multicore computing and distributed computing. It also gives examples of problems arising from economics where these parallel methods can be used to speed up the computation

08332 Executive Summary -- Distributed Verification and Grid Computing

The Dagstuhl Seminar on Distributed Verification and Grid Computing took place from 10.08.2008 to 14.08.2008 and brought together two groups of researchers to discuss their recent work and recent trends related to parallel verification of large scale computer systems on large scale grids. In total, 29 experts from 12 countries attended the seminar

Parallel Computers and Complex Systems

We present an overview of the state of the art and future trends in high performance parallel and distributed computing, and discuss techniques for using such computers in the simulation of complex problems in computational science. The use of high performance parallel computers can help improve our understanding of complex systems, and the converse is also true --- we can apply techniques used for the study of complex systems to improve our understanding of parallel computing. We consider parallel computing as the mapping of one complex system --- typically a model of the world --- into another complex system --- the parallel computer. We study static, dynamic, spatial and temporal properties of both the complex systems and the map between them. The result is a better understanding of which computer architectures are good for which problems, and of software structure, automatic partitioning of data, and the performance of parallel machines

Exploiting parallel computing with limited program changes using a network of microcomputers

Network computing and multiprocessor computers are two discernible trends in parallel processing. The computational behavior of an iterative distributed process in which some subtasks are completed later than others because of an imbalance in computational requirements is of significant interest. The effects of asynchronus processing was studied. A small existing program was converted to perform finite element analysis by distributing substructure analysis over a network of four Apple IIe microcomputers connected to a shared disk, simulating a parallel computer. The substructure analysis uses an iterative, fully stressed, structural resizing procedure. A framework of beams divided into three substructures is used as the finite element model. The effects of asynchronous processing on the convergence of the design variables are determined by not resizing particular substructures on various iterations

Mobile agent platforms in ubiquitous computing applications and systems (a literature review)

Technology revolution has been occurred rapidly over the last past thirty years According to the moor’s law power of microprocessors double every eighteen months. And also a parallel increase can be observed in some other technological sectors such as network communication, bandwidth, storage, capacity. These remarkable trends make us to predict that in future computer will become considerably smaller, cheaper and more pervasive. These result a creation of small things that can access the internet in order to optimize their intended purpose. It gives birth to new technology trend called “Ubiquitous computing”. Ubiquitous computing is an emerging technology that brings new dimensions to distributed computing. It uses a wide variety of smart, ubiquitous devices throughout an individual’s working and living environment. When it comes to ubiquitous computing, mobile objects and mobile agents are forerunners. Mobile agents are considered a very interesting and emerging technology to develop applications for mobile and distributed computing. Since they present a combination of unique features, such as their autonomy and capability to move to remote computers to process data there and save remote communications, they can be widely used in ubiquitous computing. Many mobile agent platforms have been developed since the late nineties. In this millennium era they are now influenced in many aspects of technology such as localization of technology, internet connection, voice recognition etc. This literature review focuses on Mobile agent platforms in ubiquitous computing applications and systems

Using Java for distributed computing in the Gaia satellite data processing

In recent years Java has matured to a stable easy-to-use language with the flexibility of an interpreter (for reflection etc.) but the performance and type checking of a compiled language. When we started using Java for astronomical applications around 1999 they were the first of their kind in astronomy. Now a great deal of astronomy software is written in Java as are many business applications. We discuss the current environment and trends concerning the language and present an actual example of scientific use of Java for high-performance distributed computing: ESA's mission Gaia. The Gaia scanning satellite will perform a galactic census of about 1000 million objects in our galaxy. The Gaia community has chosen to write its processing software in Java. We explore the manifold reasons for choosing Java for this large science collaboration. Gaia processing is numerically complex but highly distributable, some parts being embarrassingly parallel. We describe the Gaia processing architecture and its realisation in Java. We delve into the astrometric solution which is the most advanced and most complex part of the processing. The Gaia simulator is also written in Java and is the most mature code in the system. This has been successfully running since about 2005 on the supercomputer "Marenostrum" in Barcelona. We relate experiences of using Java on a large shared machine. Finally we discuss Java, including some of its problems, for scientific computing.Comment: Experimental Astronomy, August 201