Made available in DSpace on 2016-08-17T14:53:21Z (GMT). No. of bitstreams: 1 Marcio Rodrigo Melo Martins.pdf: 1449274 bytes, checksum: c55738b6ff5f13795eaa87e218fa536c (MD5) Previous issue date: 2012-04-13 / FUNDAÇÃO DE AMPARO À PESQUISA E AO DESENVOLVIMENTO CIENTIFICO E TECNOLÓGICO DO MARANHÃO / An opportunistic grid computing environment takes advantage of idle computing cycles of regular computers and workstations that can be spread across several administrative domains for running high performance applications. Opportunistic grids are usually constructed from personal computers that do not need to be dedicated for executing grid applications. The grid workload must coexist with local applications executions, submitted by the nodes regular users. Thus, its execution environment is typically dynamic, heterogeneous and unpredictable failures occur frequently. In addition, the resources of an opportunistic grid can be used at any time for the execution of local tasks, making it difficult to preview the conclusion of the tasks running on the grid nodes. These characteristics hinder the successful execution of applications for which there are time restrictions related to its completion. This thesis presents a management mechanism specifically designed for opportunistic grid computing environments for handling the execution of applications with time deadlines set by users during their submission to the system. The proposed mechanism is based on a dynamic scheduling and rescheduling approach and was evaluated using a simulated model considering various typical scenarios of opportunistic grids. The results demonstrated the benefits of the proposed approach in comparison to traditional scheduling approaches applied in opportunistic grids. / Um ambiente de computação de grade oportunista aproveita ciclos ociosos de computadores e estações de trabalho que podem ser distribuídos por vários domínios administrativos para a execução de aplicações de alto desempenho. Grades oportunistas geralmente são construídas a partir de computadores pessoais que não precisam ser dedicados para a execução de aplicações em grade. Neste tipo de grade, a carga de trabalho deve coexistir com execuções de aplicações locais submetidos pelos usuários dos nós que a compõe. Assim, seu ambiente de execução é tipicamente dinâmico, heterogêneo e imprevisível e falhas ocorrem com frequência. Além disso, os recursos de uma grade oportunista podem ser usados a qualquer momento para a execução de tarefas locais, o que torna difícil prever a conclusão das tarefas em execução nos nós da grade. Essas características dificultam a execução bem sucedida de aplicações para as quais existem restrições de tempo relacionada com a sua conclusão. Este trabalho apresenta um mecanismo de gerenciamento da execução de aplicações projetado especificamente para ambientes de computação de grade oportunista cujas aplicações possuem prazos de execução (deadline) definidos pelos usuários durante sua submissão ao sistema. O mecanismo proposto é baseado em uma abordagem dinâmica de escalonamento e reescalonamento de aplicações e foi avaliado através de um modelo de simulação levando-se em consideração vários cenários típicos de grades oportunistas. Os resultados demonstraram os benefícios da abordagem proposta em comparação com abordagens de escalonamento de aplicações tradicionalmente utilizadas em grades oportunistas.

Network on Chip (NoC) architectures provide scalable platforms for designing Systems on Chip (SoC) with large number of cores. Developing products and applications using an NoC architecture offers many challenges and opportunities. A tool which can map an application or a set of applications to a given NoC architecture will be essential. In this thesis we first survey current techniques and we present our proposals for mapping and scheduling of concurrent applications to NoCs with multithreaded processors as computational resources. NoC platforms are basically a special class of Multiprocessor Embedded Systems (MPES). Conventional MPES architectures are mostly bus-based and, thus, are exposed to potential difficulties regarding scalability and reusability. There has been a lot of research on MPES development including work on mapping and scheduling of applications. Many of these results can also be applied to NoC platforms. Mapping and scheduling are known to be computationally hard problems. A large range of exact and approximate optimization algorithms have been proposed for solving these problems. The methods include Branch-and–Bound (BB), constructive and transformative heuristics such as List Scheduling (LS), Genetic Algorithms (GA) and various types of Mathematical Programming algorithms. Concurrent applications are able to capture a typical embedded system which is multifunctional. Concurrent applications can be executed on an NoC which provides a large computational power with multiple on-chip computational resources. Improving the time performances of concurrent applications which are running on Network on Chip (NoC) architectures is mainly correlated with the ability of mapping and scheduling methodologies to exploit the Thread Level Parallelism (TLP) of concurrent applications through the available NoC parallelism. Matching the architectural parallelism to the application concurrency for obtaining good performance-cost tradeoffs is  another aspect of the problem. Multithreading is a technique for hiding long latencies of memory accesses, through the overlapped execution of several threads. Recently, Multi-Threaded Processors (MTPs) have been designed providing the architectural infrastructure to concurrently execute multiple threads at hardware level which, usually, results in a very low context switching overhead. Simultaneous Multi-Threaded Processors (SMTPs) are superscalar processor architectures which adaptively exploit the coarse grain and the fine grain parallelism of applications, by simultaneously executing instructions from several thread contexts. In this thesis we make a case for using SMTPs and MTPs as NoC resources and show that such a multiprocessor architecture provides better time performances than an NoC with solely General-purpose Processors (GP). We have developed a methodology for task mapping and scheduling to an NoC with mixed SMTP, MTP and GP resources, which aims to maximize the time performance of concurrent applications and to satisfy their soft deadlines. The developed methodology was evaluated on many configurations of NoC-based platforms with SMTP, MTP and GP resources. The experimental results demonstrate that the use of SMTPs and MTPs in NoC platforms can significantly speed-up applications.