Neste trabalho foi avaliada a utilização da grid computing em aspectos importantes para simulações em Física Computacional. Em particular, para aplicações de diagonalização de matrizes de grande porte. O projeto de código aberto Globus Toolkit foi utilizado para comparar o desempenho da biblioteca paralela de álgebra linear ScaLAPACK em duas versões baseadas na biblioteca de passagem de mensagens, a versão tradicional MPICH e a versão desenvolvida para um ambiente de grid computing MPICH-G2. Várias simulações com diagonalização de matrizes complexas de diversos tamanhos foram realizadas. Para um sistema com uma matriz de tamanho 8000 x 8000 distribuída em 8 processos, nos nós de 64 bits foi alcançado um speedup de 7,71 com o MPICH-G2. Este speedup é muito próximo do ideal que, neste caso, seria igual a 8. Foi constatado também que a arquitetura de 64 bits tem melhor desempenho que a de 32 bits nas simulações executadas para este tipo de aplicação / This work evaluates the use of grid computing in essential issues related to Computational Physics simulations. In particular, for applications with large scale matrix diagonalization. The Globus Toolkit open source project was used to compare the performance of the linear algebra parallel library ScaLAPACK in two different versions based on the message passing library, the traditional version MPICH and its version developed for a grid computing environment MPICH-G2. Several simulations within large scale diagonalization of complex matrix were performed. A 7.71 speedup was reached with the MPICH-G2 for a 8000 x 8000 size matrix distributed in 8 processes on 64 bits nodes. This was very close to the ideal speedup, that would be in this case, 8. It was also evidenced that the 64 bits architecture has better performance than the 32 bits on the performed simulations for this kind of application.

Neste trabalho foi avaliada a utilização da grid computing em aspectos importantes para simulações em Física Computacional. Em particular, para aplicações de diagonalização de matrizes de grande porte. O projeto de código aberto Globus Toolkit foi utilizado para comparar o desempenho da biblioteca paralela de álgebra linear ScaLAPACK em duas versões baseadas na biblioteca de passagem de mensagens, a versão tradicional MPICH e a versão desenvolvida para um ambiente de grid computing MPICH-G2. Várias simulações com diagonalização de matrizes complexas de diversos tamanhos foram realizadas. Para um sistema com uma matriz de tamanho 8000 x 8000 distribuída em 8 processos, nos nós de 64 bits foi alcançado um speedup de 7,71 com o MPICH-G2. Este speedup é muito próximo do ideal que, neste caso, seria igual a 8. Foi constatado também que a arquitetura de 64 bits tem melhor desempenho que a de 32 bits nas simulações executadas para este tipo de aplicação / This work evaluates the use of grid computing in essential issues related to Computational Physics simulations. In particular, for applications with large scale matrix diagonalization. The Globus Toolkit open source project was used to compare the performance of the linear algebra parallel library ScaLAPACK in two different versions based on the message passing library, the traditional version MPICH and its version developed for a grid computing environment MPICH-G2. Several simulations within large scale diagonalization of complex matrix were performed. A 7.71 speedup was reached with the MPICH-G2 for a 8000 x 8000 size matrix distributed in 8 processes on 64 bits nodes. This was very close to the ideal speedup, that would be in this case, 8. It was also evidenced that the 64 bits architecture has better performance than the 32 bits on the performed simulations for this kind of application.

The paper gives an overview on installation and usage of the Grid-enabled MPI implementation MPICH-G2. Performance results of MPICH-G2 in several environments are presented. / Die Arbeit gibt einen Überblick über die Installation und Nutzung der Grid-fähigen MPI-Implementation MPICH-G2. Performance-Ergebnisse von MPICH-G2 in verschiedenen Umgebungen werden gezeigt.

Grid computing is a field of research that combines many computers from distant locations to form one large computing resource. In order to be able to make use of the full potential of such a system there is a need to effectively manage resources on the Grid. There are numerous scheduling systems to perform this management for clusters of computers and a few scheduling systems for the Grid. These systems try for optimality (or close to optimality) with the goals of obtaining good throughput and minimizing job completion time. In this research, we examine issues that we believe have not been tackled in schedulers for the Grid. These issues revolve around the problem of coordinating resources belonging to separate administrative domains and scheduling in this context. In order for grid computing's vision of virtual organizations to be realized to its fullest extent, there is a need to implement and test schedulers that find resources and schedule tasks on them in a manner that is transparent to the user. These resources might be on a different administrative domain altogether and obtaining either resource or user account information on those resources might be difficult. Also, each organization might require their own policies and mechanisms to be enforced. Hence having a centralized scheduler is not feasible due to the pragmatics of the Grid. There are two basic aims to this thesis. The first aim is to design and implement a framework that takes administrative concerns into consideration during scheduling. The aim of the framework is to provide a lightweight, extensible, secure and scalable architecture under which multiple scheduling algorithms can be implemented. Second, we evaluate two prototypical of scheduling algorithms in the context of this framework. Scheduling algorithms are diverse and the applications are varied. Thus no single algorithm can obtain a good mapping for every application. We believe that different scheduling algorithms will be necessary to schedule different types of applications. In order to facilitate development of such algorithms, a framework in which it is easy to integrate other scheduling algorithms is necessary. The framework developed in this project is designed for such extensibility. / Master of Science

The main aim of the project is to launch multiple processes and have those processes communicate with each other using peer to peer communication to eliminate the problems of multiple processes running on a single server, and multiple processes running on inhomogeneous servers as well as the problems of scalability. This entire process is done using MPICH which is a high performance and portable implementation of Message Passing Interface standard. The project involves setting up the passwordless authentication between two local servers with the help of SSH connection. By establishing a peer to peer communication and by using a unique shell script which is written using MPICH and its derivatives, I am going to demonstrate the process of inter-process communication between the servers.

In this report we describe the conversion of a simple Master-Worker parallel program from global blocking communications to non-blocking communications. The program is MPI-based and has been run on different computer architectures. By moving the communication to the background the processors can use the former waiting time for computation. However we find that the computing time increases by the time the communication time decreases in the used MPICH implementation on a cluster of workstations. Also using non-global communication instead of the global communication slows the algorithm down on computers with optimized global communication routines like the Cray T3D.

This thesis summarizes our project in building and setting up a Beowulf cluster. The idea of the project was brought forward by the company CGI in Karlstad, Sweden. CGI’s wish is that the project will serve as a starting point for future research and development of a larger Beowulf cluster. The future work can be made by both employees at CGI and student exam projects from universities. The projects main purpose was to construct a cluster by using several credit card sized single board computers, in our case the Raspberry Pi 3. The process of installing, compiling and con- figuring software for the cluster is explained. The MPICH and TensorFlow software platforms are reviewed. A performance evaluation of the cluster with TensorFlow is given. A single Raspberry Pi 3 can perform neural network training at a rate of seven times slower than an Intel system (i5-5250U at 2.7 GHz and 8 GB RAM at 1600 MHz). The performance degraded significantly when the entire cluster was training. The precise cause of the performance degradation was not found, but is ruled out to be in software, either a programming error or a bug in TensorFlow.

The paper gives an overview on installation and usage of the Grid-enabled MPI implementation MPICH-G2. Performance results of MPICH-G2 in several environments are presented. / Die Arbeit gibt einen Überblick über die Installation und Nutzung der Grid-fähigen MPI-Implementation MPICH-G2. Performance-Ergebnisse von MPICH-G2 in verschiedenen Umgebungen werden gezeigt.

High quality software is a key component of various technology systems that are crucial to software producers, users, and society in general. Software application development today uses software from external sources, to achieve software implementation goals. Numerous methods, activities, and standards have been developed in order to realize quality software. Nevertheless, the pursuit for new methods of realizing and assuring quality in software is incessant. Researchers in the software engineering field are in pursuit of methods that can be on par with changing technology. Assessment of open-source software can be supported by a methodology that uses data from prior releases of a software product to predict the quality of a future release. The proposed methodology is validated using a case study of MPICH ? an open-source software product from the field of high-performance computing. A quantitative model and a module-order model have been developed that can predict the modules that are expected to have code-churn and the amount of code-churn in each module. Code-churn is defined as the amount of update activity that has been done to a software product in order to fix bugs. Further validation of the proposed methodology on other software and development of classification models for the quality factor code-churn are recommended as future work.

Je weiter die Zivilisation vorranschreitet, um so komplexer werden deren Errungenschaften. Die Herstellungsprozesse ziehen auch ein komplexes Management während der Produktion nach sich, da viele Menschen und Maschinen am Produktionsprozess beteiligt sind. Der Manager stellt hier einen "Single Point of Failure" dar. Das bedeutet, dass die erfolgreiche Produktion nun abhängig von der Qualität und der Fehlerfreiheit des Managers bzw. des leitetenden Personals ist. Um diesen Mangel zu beseitigen, lohnt es sich auch an dieser Stelle gewisse Prozesse zu automatisieren. Man erreicht dadurch einen höheren Grad an Fehlerfreiheit und Zuverlässigkeit. Um dies zu realisieren, werden unter anderem die Prinzipien des Workflow-Managements benutzt. Je komplexer ein Workflow wird, um so mehr Rechenleistung wird benötigt, um diesen in einem Workflow-Management-System auszuführen. Eine technische Möglichkeit dieses Problem zu lösen, stellt die Verteilung der Workflow-Management-Software dar. Verteilung bedeutet im gleichen Atemzug eine Verkomplizierung der Softwarearchitektur, wodurch sie wiederum komplizierter zu entwickeln ist. Komplexe Softwaresysteme ziehen komplexe Testprogramme und Simulationsumgebungen nach sich. Um die Entwicklung eines verteilten Workflow-Management-Systems zu unterstützen, wird in dieser Arbeit ein Simulationssystem für Workflow-Management-Systeme entworfen und implementiert. Es wird den Entwicklern eines verteilten Workflow-Management- Systems ein wertvolles Tool während der Implementierung der Software sein.