Mapeamento dinâmico de aplicações para MPSOCS homogêneos

• Ano de defesa: 2011
• Autor(a) principal: Mandelli, Marcelo Grandi
• Orientador(a): Moraes, Fernando Gehm
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Pontifícia Universidade Católica do Rio Grande do Sul
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Computação
• Departamento: Faculdade de Informáca
• País: BR
• Palavras-chave em Português: INFORMÁTICA; MULTIPROCESSADORES; ARQUITETURA DE COMPUTADOR
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://tede2.pucrs.br/tede2/handle/tede/5150

The advance in manufacturing technology of integrated circuits enables smaller transistors, making possible the development of SoCs (System-on-Chip). Many applications require multi-processor SoCs in order to meet their performance requirements. A SoC containing several processing elements (PEs) is called MPSoC. An MPSoC can be classified as homogeneous, when all their PEs has the same architecture; or heterogeneous, when they have different architectures. . As communication infrastructure, the MPSoC can use NoCs as a way to interconnect the PEs. NoCs may be used to replace busses, due to their advantages of higher scalability and communication parallelism. One of the main problems related to MPSoC projects is to define a PE of the system that will run each task. This problem is called task mapping. The mapping can be classified into static, which occurs at design time, and dynamic that occurs at runtime. The dynamic mapping approach requires firstly the mapping of the initial tasks of an application (which does not depend on any other task). The other tasks, in this approach, are mapped dynamically when requested. The mapping can be also classified by the number of tasks running in a PE. The mapping is classified as single task, when only one task is executed by a PE, and as multitask, when multiple tasks can be executed in a same PE. This work proposes new single task and multitask dynamic task mapping heuristics, in order to reduce communication energy. Results are evaluated using the MPSoC HeMPS, which executes application code generated from a model-based simulation environment. These heuristics are compared with mapping heuristic presented in literature, obtaining, in the evaluated scenarios, an average communication energy reduction of 9.8%, for the single task approach, and 18.6%, for the multitask approach. This work also evaluates the inclusion of dynamic load on the system, which makes necessary the implementation of an initial tasks mapping heuristic. This heuristic is an innovative contribution, since a similar approach is not found in any other work in literature.