@MASTERSTHESIS{ 2020:2000744356,
 	title = {ORCA : a self-adaptive, multiprocessor system-on-chip platform},
 	year = {2020},
 	url = "http://tede2.pucrs.br/tede2/handle/tede/9344",
 	abstract = "The complex organization of multiprocessor systems-on-chips (MPSoCs) requires
 the smart management of systems? resources during runtime and the capability of systems
 to optimize their operation under abnormal situations such as temporary hardware unavailability.
 One of the approaches for resource management in MPSoCs is self-adaptation,
 which augment these systems with sensors, actuators, and decision logic components. In
 this thesis, we propose ORCA, a development platform to aid in designing self-adaptive
 systems. The platform provides abstractions to deal with self-adaptation complexity, based
 on previous work in the field, including a configurable hardware architecture, operating system,
 software libraries, and simulation environment. The hardware architecture consists of
 open-source hardware modules and implements a many-core approach based on a RISCV
 compatible processor core. That architecture can be emulated and simulated through
 ORCA-SIM, a simulation tool, also part of this work. The tool uses discrete-event simulation
 to speed up the simulation process, based on the URSA application programming interface,
 also part of this work. Software components are also discussed, including a library
 for hardware monitoring and energy consumption estimation, and a library for designing
 publish-subscribe systems. We present a compilation of results achieved in previous work
 and new experiments to cover the validation of the entire platform. For the latter, we focus
 the discussion on the design of a task reallocation mechanism based on self-adaptive
 components.",
 	publisher = {Pontif?cia Universidade Cat?lica do Rio Grande do Sul},
 	scholl = {Programa de P?s-Gradua??o em Ci?ncia da Computa??o},
 	note = {Escola Polit?cnica}
}