PPgSC/UFRN PROGRAMA DE PÓS-GRADUAÇÃO EM SISTEMAS E COMPUTAÇÃO ADMINISTRAÇÃO DO CCET Téléphone/Extension: (84)3342-2225/115 https://posgraduacao.ufrn.br/ppgsc

Banca de DEFESA: HIAGO MAYK GOMES DE ARAÚJO ROCHA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
DISCENTE : HIAGO MAYK GOMES DE ARAÚJO ROCHA
DATA : 19/07/2019
HORA: 09:00
LOCAL: DIMAp
TÍTULO:

Mapping and Routing Problem: Hybrid Bioinspired Optimization Solution


PALAVRAS-CHAVES:

Multiprocessor System-on-Chip, Network-on-Chip, Performance, Task Mapping, Routing Algorithm, Math-Heuristic.


PÁGINAS: 110
GRANDE ÁREA: Ciências Exatas e da Terra
ÁREA: Ciência da Computação
SUBÁREA: Sistemas de Computação
ESPECIALIDADE: Arquitetura de Sistemas de Computação
RESUMO:

The advances of integrated circuit fabrication technology, allowed by the reduction of transistors size, make possible the creation of multiprocessed complex systems inside a single chip, named Multiprocessors System of Chip (MPSoC). To allow communication among the different cores, one of the main communication model used currently is the Network on Chip (NoC) which shows more scalability than traditional bus solution.  In spite of the expected potential performance improvement due to task parallelism, to achieve a real performance improvement it is necessary an efficient available resource management in the system, such as processing cores and communication links. This management is related, among other aspects, to how tasks are mapped in the MPSoC cores and which NoC channels are used to provide communication routes for tasks. In the literature, these aspects are handled individually, even though, they are highly correlated. Based on this principle, in this work, it is presented a mathematical formulation of the Mapping and Routing Problem (PMR) that combines both problems. Additionally, in order to find optimized mapping solutions, this work presents three proposals of static mapping and one of the dynamic mapping.In the static mapping context, it is presented bioinspired hybrid optimization strategies (Genetic, Memetic and Transgenetic). These strategies present a general approach to find mapping solution and internally, it is used an exact routing fitness function evaluation based on the proposed model.In the dynamic mapping context, it is proposed an algorithm that uses the Transgenetic operator to provide the task allocation by demand at run time. The algorithms were implemented and its results were simulated using a NoC simulation tool. In order to compare to state of art, three algorithms from literature were also implemented and simulated. The results show that approaches able to capture more deeply the features of the architecture are more efficient. More specifically, the Transgenetic algorithm presents the best results for latency and energy. Furthermore, it was possible to use the Transgenetic aspects to propose a dynamic solution that can be used when the system does not know the application behavior.


MEMBROS DA BANCA:
Presidente - 1882699 - MONICA MAGALHAES PEREIRA
Interno - 1694485 - MARCIO EDUARDO KREUTZ
Externa ao Programa - 2859606 - SILVIA MARIA DINIZ MONTEIRO MAIA
Externo à Instituição - ANTONIO CARLOS SCHNEIDER BECK FILHO - UFRGS
Notícia cadastrada em: 02/05/2019 08:15
SIGAA | Superintendência de Tecnologia da Informação - (84) 3342 2210 | Copyright © 2006-2024 - UFRN - sigaa11-producao.info.ufrn.br.sigaa11-producao