High performance computing of explicit schemes for electrofusion jointing process based on message-passing paradigm

The research focused on heterogeneous cluster workstations comprising of a number of CPUs in single and shared architecture platform. The problem statements under consideration involved one dimensional parabolic equations. The thermal process of electrofusion jointing was also discussed. Numerical schemes of explicit type such as AGE, Brian, and Charlies Methods were employed. The parallelization of these methods were based on the domain decomposition technique. Some parallel performance measurement for these methods were also addressed. Temperature profile of the one dimensional radial model of the electrofusion process were also given

Practical experience using a computational model for the design of heterogeneous distributed software

Heterogeneous cluster environments are becoming an increasing popular platform for executing parallel applications. Efficient heterogeneous programs must account for the differences inherent in such an environment. We propose the HBSP(1) model of computation as a framework for developing applications for heterogeneous clusters of workstations. The utility of the model is demonstrated through the design and analysis of the scatter and one-to-all broadcast algorithms. Extensive experimentation illustrates the benefits of using the model for heterogeneous program development. By hiding the non-uniformity of the underlying system, the HBSP(1) model provides a framework that embraces the heterogeneity of the underlying system

Adaptive and secured resource management in distributed and Internet systems

The effectiveness of computer system resource management has been always determined by two major factors: (1) workload demands and management objectives, (2) the updates of the computer technology. These two factors are dynamically changing, and resource management systems must be timely adaptive to the changes. This dissertation attempts to address several important and related resource management issues.;We first study memory system utilization in centralized servers by improving memory performance of sorting algorithms, which provides fundamental understanding on memory system organizations and its performance optimizations for data-intensive workloads. to reduce different types of cache misses, we restructure the mergesort and quicksort algorithms by integrating tiling, padding, and buffering techniques and by repartitioning the data set. Our study shows substantial performance improvements from our new methods.;We have further extended the work to improve load sharing for utilizing global memory resources in distributed systems. Aiming at reducing the memory resource contention caused by page faults and I/O activities, we have developed and examined load sharing policies by considering effective usage of global memory in addition to CPU load balancing in both homogeneous and heterogeneous clusters.;Extending our research from clusters to Internet systems, we have further investigated memory and storage utilizations in Web caching systems. We have proposed several novel management schemes to restructure and decentralize the existing caching system by exploiting data locality at different levels of the global memory hierarchy and by effectively sharing data objects among the clients and their proxy caches.;Data integrity and communication anonymity issues are raised from our decentralized Web caching system design, which are also security concerns for general peer-to-peer systems. We propose an integrity protocol to ensure data integrity, and several protocols to achieve mutual communication anonymity between an information requester and a provider.;The potential impact and contributions of this dissertation are briefly stated as follows: (1) two major research topics identified in this dissertation are fundamentally important for the growth and development of information technology, and will continue to be demanding topics for a long term. (2) Our proposed cache-effective sorting methods bridge a serious gap between analytical complexity of algorithms and their execution complexity in practice due to the increasingly deep memory hierarchy in computer systems. This approach can also be used to improve memory performance at different levels of the memory hierarchy, such as I/O and file systems. (3) Our load sharing principle of giving a high priority to the requests of data accesses in memory and I/Os timely adapts the technology changes and effectively responds to the increasing demand of data-intensive applications. (4) Our proposed decentralized Web caching framework and its resource management schemes present a comprehensive case study to examine the P2P model. Our results and experiences can be used for related and further studies in distributed computing. (5) The proposed data integrity and communication anonymity protocols address limits and weaknesses of existing ones, and place a solid foundation for us to continue our work in this important area

An Agent-Based Approach to Self-Organized Production

The chapter describes the modeling of a material handling system with the production of individual units in a scheduled order. The units represent the agents in the model and are transported in the system which is abstracted as a directed graph. Since the hindrances of units on their path to the destination can lead to inefficiencies in the production, the blockages of units are to be reduced. Therefore, the units operate in the system by means of local interactions in the conveying elements and indirect interactions based on a measure of possible hindrances. If most of the units behave cooperatively ("socially"), the blockings in the system are reduced. A simulation based on the model shows the collective behavior of the units in the system. The transport processes in the simulation can be compared with the processes in a real plant, which gives conclusions about the consequencies for the production based on the superordinate planning.Comment: For related work see http://www.soms.ethz.c

Analytical Modeling of High Performance Reconfigurable Computers: Prediction and Analysis of System Performance.

The use of a network of shared, heterogeneous workstations each harboring a Reconfigurable Computing (RC) system offers high performance users an inexpensive platform for a wide range of computationally demanding problems. However, effectively using the full potential of these systems can be challenging without the knowledge of the system’s performance characteristics. While some performance models exist for shared, heterogeneous workstations, none thus far account for the addition of Reconfigurable Computing systems. This dissertation develops and validates an analytic performance modeling methodology for a class of fork-join algorithms executing on a High Performance Reconfigurable Computing (HPRC) platform. The model includes the effects of the reconfigurable device, application load imbalance, background user load, basic message passing communication, and processor heterogeneity. Three fork-join class of applications, a Boolean Satisfiability Solver, a Matrix-Vector Multiplication algorithm, and an Advanced Encryption Standard algorithm are used to validate the model with homogeneous and simulated heterogeneous workstations. A synthetic load is used to validate the model under various loading conditions including simulating heterogeneity by making some workstations appear slower than others by the use of background loading. The performance modeling methodology proves to be accurate in characterizing the effects of reconfigurable devices, application load imbalance, background user load and heterogeneity for applications running on shared, homogeneous and heterogeneous HPRC resources. The model error in all cases was found to be less than five percent for application runtimes greater than thirty seconds and less than fifteen percent for runtimes less than thirty seconds. The performance modeling methodology enables us to characterize applications running on shared HPRC resources. Cost functions are used to impose system usage policies and the results of vii the modeling methodology are utilized to find the optimal (or near-optimal) set of workstations to use for a given application. The usage policies investigated include determining the computational costs for the workstations and balancing the priority of the background user load with the parallel application. The applications studied fall within the Master-Worker paradigm and are well suited for a grid computing approach. A method for using NetSolve, a grid middleware, with the model and cost functions is introduced whereby users can produce optimal workstation sets and schedules for Master-Worker applications running on shared HPRC resources

Computing and data processing

The applications of computers and data processing to astronomy are discussed. Among the topics covered are the emerging national information infrastructure, workstations and supercomputers, supertelescopes, digital astronomy, astrophysics in a numerical laboratory, community software, archiving of ground-based observations, dynamical simulations of complex systems, plasma astrophysics, and the remote control of fourth dimension supercomputers

A Novel Approach for O (1) Parallel Sorting Algorithm

Sorting is an algorithm of the most relevant operations performed on computers. In particular, it is a crucial tool when it comes to processing huge volumes of data into the memory. There are different types of sorting algorithms: simple sorting algorithms(such as insertion, selection and bubble)  and parallel sorting(such as parallel merge sort, Odd-even sorting, Bitonic sort and O(1) parallel sorting ) algorithm. Parallel sorting is the process of using multiple processing units to collectively sort an unordered sequence of data. In this paper is devoted to the discovery of new approach to O (1) parallel sorting algorithm, in which redundant data didn't taken into consideration yet

A Grid Portal for an Undergraduate Parallel Programming Course

[Abstract] This paper describes an experience of designing and implementing a portal to support transparent remote access to supercomputing facilities to students enrolled in an undergraduate parallel programming course. As these facilities are heterogeneous, are located at different sites, and belong to different institutions, grid computing technologies have been used to overcome these issues. The result is a grid portal based on a modular and easily extensible software architecture that provides a uniform and user-friendly interface for students to work on their programming laboratory assignments.Universidade da Coruña; UDC-TIC03-057Xunta de Galicia; PGIDIT02TIC00103CTXunta de Galicia; PGIDIT04TIC105004PREuropean Commission; IST-2001-3224